Transcript
00:00:00 Well, the source of energy at the origin of life
00:00:01 is the reaction between carbon dioxide and hydrogen.
00:00:04 And amazingly, most of these reactions are exergonic,
00:00:08 which is to say they release energy.
00:00:10 If you have hydrogen and CO2,
00:00:13 and you put them together in a falcon tube
00:00:15 and you warm it up to say 50 degrees centigrade,
00:00:17 and you put in a couple of catalysts and you shake it,
00:00:19 nothing’s gonna happen.
00:00:21 But thermodynamically, that is less stable.
00:00:24 Two gases, hydrogen and CO2, is less stable than cells.
00:00:28 What should happen is you get cells coming out.
00:00:31 Why doesn’t that happen?
00:00:32 It’s because of the kinetic barriers.
00:00:34 That’s where you need the spark.
00:00:38 The following is a conversation with Nick Lane,
00:00:40 a biochemist at University College London
00:00:43 and author of some of my favorite books
00:00:46 on biology, science, and life ever written,
00:00:49 including his two most recent titled
00:00:51 “‘Transformer,’ The Deep Chemistry of Life and Death,”
00:00:54 and the vital question, why is life the way it is?
00:01:00 This is the Lex Friedman podcast.
00:01:02 To support it, please check out our sponsors
00:01:04 in the description.
00:01:05 And now, dear friends, here’s Nick Lane.
00:01:09 Let’s start with perhaps the most mysterious,
00:01:11 the most interesting question that we little humans
00:01:16 can ask of ourselves.
00:01:18 How did life originate on Earth?
00:01:20 You could ask anybody working on the subject,
00:01:24 and you’ll get a different answer from all of them.
00:01:26 They will be pretty passionately held opinions,
00:01:30 and their opinions grounded in science,
00:01:34 but they’re still really, at this point, their opinions,
00:01:36 because there’s so much stuff to know
00:01:38 that all we can ever do is get a small slice of it,
00:01:42 and it’s the context which matters.
00:01:44 So I can give you my answer.
00:01:46 My answer is from a biologist’s point of view.
00:01:50 That has been missing from the equation over decades,
00:01:54 which is, well, what does life do on Earth?
00:01:57 Why is it this way?
00:01:58 Why is it made of cells?
00:01:59 Why is it made of carbon?
00:02:01 Why is it powered by electrical charges on membranes?
00:02:06 There’s all these interesting questions about cells
00:02:09 that if you then look to see,
00:02:10 well, is there an environment on Earth,
00:02:12 on the early Earth four billion years ago,
00:02:14 that kind of matches the requirements of cells?
00:02:16 Well, there is one.
00:02:17 There’s a very obvious one.
00:02:18 It’s basically created by whenever you have
00:02:21 a wet, rocky planet, you get these hydrothermal vents,
00:02:24 which generate hydrogen gas in bucket loads,
00:02:28 and electrical charges on kind of cell like pores
00:02:32 that can drive the kind of chemistry that life does.
00:02:35 So it seems so beautiful and so obvious
00:02:40 that I’ve spent the last 10 years or more
00:02:43 trying to do experiments.
00:02:45 It turns out to be difficult, of course.
00:02:47 Everything’s more difficult than you ever thought
00:02:48 it was gonna be, but it looks, I would say,
00:02:51 more true rather than less true over that 10 year period.
00:02:53 I think I have to take a step back every now and then
00:02:56 and think, hang on a minute, where’s this going?
00:02:59 I’m happy it’s going in a sensible direction.
00:03:02 And I think then you have these other interesting dilemmas.
00:03:06 I mean, I’m often accused of being too focused
00:03:10 on life on Earth, too kind of narrow minded
00:03:14 and inward looking, you might say.
00:03:17 I’m talking about carbon, I’m talking about cells,
00:03:18 and maybe you or plenty of people can say to me,
00:03:21 ah, yeah, but life can be anything.
00:03:23 I have no imagination.
00:03:24 And maybe they’re right.
00:03:26 But unless we can say why life here is this way,
00:03:29 and if those reasons are fundamental reasons,
00:03:32 or if they’re just trivial reasons,
00:03:33 then we can’t answer that question.
00:03:36 So I think they’re fundamental reasons,
00:03:38 and I think we need to worry about them.
00:03:40 Yeah, there might be some deep truth to the puzzle
00:03:42 here on Earth that will resonate
00:03:44 with other puzzles elsewhere that will,
00:03:48 solving this particular puzzle
00:03:50 will give us that deeper truth.
00:03:52 So what, to this puzzle, you said vents, hydrogen,
00:03:58 wet, so chemically, what is the potion here?
00:04:04 How important is oxygen?
00:04:06 You wrote a book about this.
00:04:07 Yeah, and I actually just came straight here
00:04:09 from a conference where I was chairing a session
00:04:11 on whether oxygen matters or not in the history of life.
00:04:13 Of course it matters, but it matters most
00:04:16 to the origin of life to be not there.
00:04:20 As I see it, we have this, I mean,
00:04:23 life is made of carbon, basically, primarily,
00:04:27 organic molecules with carbon, carbon bonds.
00:04:30 And the building block, the Lego brick
00:04:32 that we take out of the air or take out of the oceans
00:04:34 is carbon dioxide.
00:04:36 And to turn carbon dioxide into organic molecules,
00:04:39 we need to strap on hydrogen.
00:04:42 And so we need, and this is basically
00:04:43 what life is doing, it’s hydrogenating carbon dioxide.
00:04:47 It’s taking the hydrogen, the bubbles out of the earth
00:04:49 in these hydrothermal vents, and it sticks it on CO2.
00:04:53 And it’s kind of really as simple as that.
00:04:56 And actually, thermodynamically,
00:04:58 there’s the thing that I find most troubling
00:05:01 is that if you do these experiments in the lab,
00:05:03 the molecules you get are exactly the molecules
00:05:06 that we see at the heart of biochemistry
00:05:07 in the heart of life.
00:05:08 Is there something to be said about the earliest origins
00:05:14 of that little potion, that chemical process?
00:05:21 What really is the spark there?
00:05:24 There isn’t a spark.
00:05:28 There is a continuous chemical reaction.
00:05:31 And there is kind of a spark,
00:05:33 but it’s a continuous electrical charge
00:05:35 which helps drive that reaction.
00:05:37 There’s a literally spark.
00:05:39 Well, the charge at least, but yes.
00:05:41 I mean, a spark in that sense is,
00:05:43 we tend to think of in terms of Frankenstein,
00:05:46 we tend to think in terms of electricity
00:05:48 and one moment you zap something and it comes alive.
00:05:52 And what does that really mean?
00:05:53 It’s come alive and now what’s sustaining it?
00:05:56 Well, we are sustained by oxygen,
00:05:59 by this continuous chemical reaction.
00:06:02 And if you put a plastic bag on your head,
00:06:03 then you’ve got a minute or something before it’s all over.
00:06:07 So some way of being able to leverage a source of energy.
00:06:11 Well, the source of energy at the origin of life
00:06:12 is the reaction between carbon dioxide and hydrogen.
00:06:15 And amazingly, most of these reactions are exergonic,
00:06:19 which is to say they release energy.
00:06:21 If you have hydrogen and CO2
00:06:24 and you put them together in a falcon tube
00:06:26 and you warm it up to say 50 degrees centigrade
00:06:28 and you put in a couple of catalysts and you shake it,
00:06:31 nothing’s gonna happen.
00:06:32 But thermodynamically, that is less stable.
00:06:35 Two gases, hydrogen and CO2, is less stable than cells.
00:06:39 What should happen is you get cells coming out.
00:06:43 So why doesn’t that happen?
00:06:45 It’s because of the kinetic barriers.
00:06:47 That’s where you need the spark.
00:06:49 Is it possible that life originated
00:06:52 multiple times on Earth?
00:06:54 The way you describe it, you make it sound so easy.
00:06:57 There’s a long distance to go from the first bits
00:07:01 of prebiotic chemistry to, say, molecular machines
00:07:04 like ribosomes.
00:07:05 Is that the first thing that you would say is life?
00:07:09 Like if I introduce you, the two of you at a party,
00:07:12 you would say that’s a living thing?
00:07:15 I would say as soon as we introduce genes, information,
00:07:19 into systems that are growing anyway,
00:07:22 so I would talk about growing protocells,
00:07:25 as soon as we introduce even random bits of information
00:07:30 into there, I’m thinking about RNA molecules, for example,
00:07:35 doesn’t have to have any information in it.
00:07:36 It can be a completely random sequence.
00:07:38 But if it’s introduced into a system which is in any case
00:07:41 growing and doubling itself and reproducing itself,
00:07:43 then any changes in that sequence that allow it
00:07:46 to do so better or worse are now selected
00:07:48 by perfectly normal natural selection.
00:07:51 But it’s a system.
00:07:52 So that’s when it becomes alive to my mind.
00:07:54 That’s encompassed into like an object
00:08:00 that keeps information and evolves that information
00:08:03 over time or changes that information over time
00:08:06 in response to the.
00:08:07 So it’s always part of a cell system
00:08:10 from the very beginning.
00:08:11 So is your sense that it started only once
00:08:14 because it’s difficult or is it possibly started
00:08:16 in multiple locations on Earth?
00:08:18 It’s possible it started multiple occasions.
00:08:22 There’s two provisos to that.
00:08:23 One of them is oxygen makes it impossible really
00:08:28 for life to start.
00:08:29 So as soon as we’ve got oxygen in the atmosphere,
00:08:31 then life isn’t gonna keep starting over.
00:08:34 So I often get asked by people,
00:08:36 why can’t we have life starting?
00:08:37 If it’s so easy, why can’t life start in these vents now?
00:08:40 And the answer is if you want hydrogen to react with CO2
00:08:43 and there’s oxygen there, hydrogen reacts
00:08:45 with oxygen instead.
00:08:46 It’s just, you get an explosive reaction that way.
00:08:48 It’s rocket fuel.
00:08:50 So it’s never gonna happen.
00:08:51 But for the origin of life earlier than that,
00:08:54 all we know is that there’s a single common ancestor
00:08:57 for all of life.
00:08:58 There could have been multiple origins
00:09:00 and they all just disappeared.
00:09:02 But there’s a very interesting deep split in life
00:09:06 between bacteria and what are called archaea,
00:09:09 which look just the same as bacteria.
00:09:12 And they’re not quite as diverse, but nearly.
00:09:14 And they are very different in their biochemistry.
00:09:18 And so any explanation for the origin of life
00:09:19 has to account as well for why they’re so different
00:09:22 and yet so similar.
00:09:24 And that makes me think that life probably
00:09:27 did arise only once.
00:09:29 Can you describe the difference that’s interesting there?
00:09:31 Well, how they’re similar, how they’re different?
00:09:34 Well, they’re different in their membranes primarily.
00:09:38 They’re different in things like DNA replication.
00:09:40 They use completely different enzymes
00:09:41 and the genes behind it for replicating DNA.
00:09:44 So they both have membranes, both have DNA replication.
00:09:47 Yes.
00:09:48 The process of that is different.
00:09:50 They both have DNA.
00:09:52 The genetic code is identical in them both.
00:09:54 The way in which it’s transcribed into RNA,
00:09:58 into the copy of a gene,
00:10:00 and the way that that’s then translated into a protein,
00:10:03 that’s all basically the same in both of these groups.
00:10:05 So they clearly share a common ancestor.
00:10:08 It’s just that they’re different
00:10:09 in fundamental ways as well.
00:10:10 And if you think about, well,
00:10:11 what kind of processes could drive that divergence
00:10:15 very early on?
00:10:18 I can think about it in terms of membranes,
00:10:19 in terms of the electrical charges on membranes.
00:10:22 And it’s that that makes me think that there was probably,
00:10:25 there were probably many unsuccessful attempts
00:10:27 but only one really successful attempt.
00:10:30 Can you explain why that divergence
00:10:31 makes you think there’s one common ancestor?
00:10:36 Okay, can you describe that intuition?
00:10:38 I’m a little bit unclear about why the divert,
00:10:40 like the leap from the divergence means there’s one.
00:10:43 Do you mean like the divergence indicates
00:10:47 that there was a big invention at that time from one source?
00:10:52 If you’d got, as I imagine it,
00:10:54 you have a common ancestor living in a hydrothermal vent.
00:10:59 Let’s say there are millions of vents
00:11:01 and millions of potential common ancestors
00:11:04 living in all of those vents,
00:11:06 but only one of them makes it out first.
00:11:09 Then you could imagine that that cell
00:11:11 is then gonna kind of take over the world
00:11:12 and wipe out everything else.
00:11:14 And so what you would see would be
00:11:16 a single common ancestor for all of life.
00:11:18 But with lots of different vent systems
00:11:21 all kind of vying to create the first life forms,
00:11:24 you might say.
00:11:25 So this thing is a cell, a single cell organism.
00:11:28 We’re always talking about populations of cells, but yes.
00:11:32 These are single celled organisms.
00:11:33 But the fundamental life form is a single cell, right?
00:11:37 So like, or, so they’re always together
00:11:41 but they’re alone together.
00:11:44 Yeah.
00:11:44 There’s a machinery in each one individual component
00:11:47 that if left by itself would still work, right?
00:11:50 Yes, yes, yes.
00:11:51 It’s the unit of selection is a single cell.
00:11:54 But selection operates over generations
00:11:56 and changes over generations in populations of cells.
00:11:59 So it would be impossible to say that a cell
00:12:01 is the unit of selection in the sense that
00:12:04 unless you have a population, you can’t evolve,
00:12:06 you can’t change.
00:12:07 Right, but there was one Chuck Norris,
00:12:12 it’s an American reference cell
00:12:15 that made it out of the vents, right?
00:12:17 Or like the first one.
00:12:19 So imagine then that there’s one cell gets out
00:12:22 and it takes over the world.
00:12:23 It gets out in the water, it’s like floating around.
00:12:25 We’re deep in the ocean somewhere.
00:12:27 Yeah.
00:12:28 But actually two cells got out
00:12:31 and they appear to have got out from the same vent
00:12:35 because they both share the same code and everything else.
00:12:38 So unless all the, you know,
00:12:40 we’ve got a million different common ancestors
00:12:42 in all these different vents.
00:12:44 So either they all have the same code
00:12:47 and two cells spontaneously merge from different places
00:12:49 or two different cells, fundamentally different cells
00:12:54 came from the same place.
00:12:55 So either way, what are the constraints that say,
00:12:59 not just one came out or not half a million came out,
00:13:01 but two came out.
00:13:03 That’s kind of a bit strange.
00:13:05 So how did they come out?
00:13:06 Well, they come out because what are you doing inside a vent
00:13:09 is you’re relying on the electrical charges down there
00:13:12 to power this reaction between hydrogen and CO2
00:13:15 to make yourself grow.
00:13:16 And when you leave the vent, you’ve got to do that yourself.
00:13:19 You’ve got to power up your own membrane.
00:13:21 And so the question is,
00:13:22 well, how do you power up your own membrane?
00:13:24 And the answer is, well, you need to pump.
00:13:27 You need to pump ions to give an electrical charge
00:13:29 on the membrane.
00:13:30 So what do the pumps look like?
00:13:32 Well, the pumps look different in these two groups.
00:13:35 It’s as if they both emerged from a common ancestor.
00:13:37 As soon as you’ve got that ancestor,
00:13:39 things move very quickly and divergently.
00:13:43 Why does the DNA replication look different?
00:13:45 Well, it’s joined to the membrane.
00:13:47 The membranes are different.
00:13:48 The DNA replication is different
00:13:49 because it’s joined to a different kind of membrane.
00:13:52 So there’s interesting, this is detail, you may say,
00:13:55 but it’s also fundamental
00:13:57 because it’s about the two big divergent groups
00:13:59 of life on Earth that seem to have diverged really early on.
00:14:02 And it all started from one organism.
00:14:06 And then that organism just start replicating
00:14:09 the heck out of itself with some mutation of the DNA.
00:14:14 So like there’s some, there’s a competition
00:14:17 through the process of evolution.
00:14:19 They’re not like trying to beat each other up.
00:14:21 They’re just, they’re just trying to live.
00:14:24 Just replicate us.
00:14:25 Yeah.
00:14:26 Well, you know, let’s not minimize there.
00:14:28 Yeah.
00:14:29 They’re just trying to chill.
00:14:30 They’re trying to relax up.
00:14:32 There’s no, but there’s no sense of trying to survive.
00:14:35 They’re replicating.
00:14:36 I mean, there’s no sense
00:14:37 in which they’re trying to do anything.
00:14:39 They’re just kind of an outgrowth of the Earth,
00:14:42 you might say.
00:14:42 Of course, the aliens would describe us humans
00:14:44 in that same way.
00:14:45 They might be right.
00:14:47 This primitive life.
00:14:48 It’s just ants that are hairless,
00:14:52 mostly hairless.
00:14:53 Overgrown ants.
00:14:54 Overgrown ants.
00:14:55 Okay.
00:14:56 What do you think about the idea of panspermia
00:14:59 that the theory that life did not originate on Earth
00:15:03 and was planted here from outer space?
00:15:06 Or pseudopanspermia, which is like the basic ingredients,
00:15:10 the magic that you mentioned was planted here
00:15:12 from elsewhere in space?
00:15:14 I don’t find them helpful.
00:15:16 That’s not to say they’re wrong.
00:15:18 So, pseudotranspermia, the idea that the chemicals,
00:15:22 the amino acids, the nucleotides
00:15:23 are being delivered from space.
00:15:24 Well, we know that happens.
00:15:25 It’s unequivocal.
00:15:27 They’re delivered on meteorites, comets, and so on.
00:15:30 So what do they do next?
00:15:31 That’s, to me, the question.
00:15:33 Well, what do they do is they stock a soup.
00:15:35 Presumably, they land in a pond or in an ocean
00:15:37 or wherever they land.
00:15:39 And then you end up with a best possible case scenario
00:15:42 is you end up with a soup of nucleotides
00:15:43 and amino acids.
00:15:44 And then you have to say, so now what happens?
00:15:46 And the answer is, oh, well, they have to go,
00:15:48 bloop, become alive.
00:15:50 So how did they do that?
00:15:51 And you may as well say then a miracle happened.
00:15:54 I don’t believe in soup.
00:15:57 I think what we have in event is a continuous conversion,
00:16:00 a continuous growth, a continuous reaction,
00:16:02 a continuous converting a flow of molecules
00:16:05 into more of yourself, you might say,
00:16:07 even if it’s a small bit.
00:16:08 So you’ve got a kind of continuous self organization
00:16:13 and growth from the very beginning.
00:16:14 You never have that in a soup.
00:16:17 Isn’t the entire universe and living organisms
00:16:20 in the universe, isn’t it just soup all the way down?
00:16:25 Isn’t it all soup?
00:16:25 No, no, I mean, soup almost by definition
00:16:27 doesn’t have a structure.
00:16:29 But soup is a collection of ingredients
00:16:32 that are like randomly interacting.
00:16:34 Yeah, but they’re not random.
00:16:36 They’re not, I mean, we have chemistry going on here.
00:16:38 We have metal grains forming, which are, you know,
00:16:41 effective oil water interactions.
00:16:43 Okay, so it feels like there’s a direction to a process,
00:16:45 like a directed process.
00:16:47 There are directions to processes, yeah.
00:16:49 And if you’re starting with CO2
00:16:52 and you’ve got two reactive fluids being brought together
00:16:55 and they react, what are they gonna make?
00:16:57 Well, they make carboxylic acids,
00:16:59 which include the fatty acids
00:17:01 that make up the cell membranes.
00:17:03 And they form directly into bilayer membranes.
00:17:06 They form like soap bubbles.
00:17:07 It’s spontaneous organization caused by the nature
00:17:11 of the molecules.
00:17:12 And those things are capable of growing
00:17:14 and are capable in effect of being selected
00:17:16 even before there are genes.
00:17:18 We have this, so we have a lot of order
00:17:20 and that order is coming from thermodynamics.
00:17:22 And the thermodynamics is always about increasing
00:17:25 the entropy of the universe.
00:17:27 But if you have oil and water and they’re separating,
00:17:30 you’re increasing the entropy of the universe,
00:17:32 even though you’ve got some order,
00:17:33 which is the soap and the water are not missable.
00:17:36 Now, to come back to your first question
00:17:39 about panspermia properly,
00:17:43 that just pushes the question somewhere else.
00:17:45 That just, even if it’s true,
00:17:46 maybe life did start on Earth by panspermia.
00:17:49 So what are the principles
00:17:52 that govern the emergence of life on any planet?
00:17:55 It’s an assumption that life started here.
00:17:57 And it’s an assumption that it started
00:18:01 in a hydrothermal vent or it started
00:18:02 in a terrestrial geothermal system.
00:18:04 The question is, can we work out a testable sequence
00:18:07 of events that would lead from one to the other one
00:18:10 and then test it and see if there’s any truth in it or not?
00:18:12 With panspermia, you can’t do any of that.
00:18:14 But the fundamental question of panspermia is,
00:18:17 do we have the machine here on Earth to build life?
00:18:23 Is the vents enough?
00:18:25 Is oxygen and hydrogen and whatever the heck else we want
00:18:31 and some source of energy and heat,
00:18:34 is that enough to build life?
00:18:36 Yes.
00:18:37 Well, that’s, of course you would say that as a human.
00:18:41 Yeah.
00:18:42 But there could be aliens right now
00:18:44 chuckling at that idea.
00:18:46 Maybe you need some special sauce,
00:18:50 special elsewhere sauce.
00:18:52 So your sense is we have everything here.
00:18:54 I mean, this is precisely the question.
00:18:57 I like to, when I’m talking in schools,
00:18:59 I like to start out with the idea
00:19:00 of we can make a time machine.
00:19:03 We go back four billion years
00:19:05 and we go to these environments that people talk about.
00:19:07 We go to a deep sea hydrothermal vent,
00:19:09 we go to a kind of Yellowstone Park type place environment
00:19:14 and we find some slime that looks like we can test it.
00:19:18 It’s made of organic molecules.
00:19:20 It’s got a structure which is not obviously cells,
00:19:22 but you know, is this a stepping stone
00:19:25 on the way to life or not?
00:19:26 Yeah.
00:19:27 How do we know?
00:19:29 Unless we’ve got an intellectual framework
00:19:31 that says this is a stepping stone and that’s not a step.
00:19:34 You know, we’d never know.
00:19:35 We wouldn’t know which environment to go to,
00:19:36 what to look for, how to say this.
00:19:38 So all we can ever hope for,
00:19:39 because we’re never gonna build that time machine,
00:19:41 is to have an intellectual framework
00:19:43 that can explain step by step, experiment by experiment,
00:19:46 how we go from a sterile inorganic planet
00:19:49 to living cells as we know them.
00:19:52 And in that framework, every time you have a choice,
00:19:55 it could be this way or it could be that way,
00:19:57 or there’s lots of possible forks down that road.
00:20:02 Did it have to be that way?
00:20:03 Could it have been the other way?
00:20:05 And would that have given you life
00:20:06 with very different properties?
00:20:08 And so if you come up with a, you know,
00:20:11 it’s a long hypothesis, because as I say,
00:20:12 we’re going from really simple prebiotic chemistry
00:20:15 all the way through to genes and molecular machines.
00:20:17 That’s a long, long pathway.
00:20:20 And nobody in the field would agree on the order
00:20:22 in which these things happened,
00:20:23 which is not a bad thing,
00:20:24 because it means that you have to go out
00:20:25 and do some experiments and try and demonstrate
00:20:27 that it’s possible or not possible.
00:20:29 It’s so freaking amazing that it happened though.
00:20:37 It feels like there’s a direction to the thing.
00:20:41 Can you try to answer from a framework perspective
00:20:47 of what is life?
00:20:49 So you said there’s some order and yet there’s complexity.
00:20:57 So it’s not perfectly ordered.
00:20:59 It’s not boring.
00:21:00 There’s still some fun in it.
00:21:02 And it also feels like the processes have a direction
00:21:06 through the selection mechanism.
00:21:07 They seem to be building something,
00:21:10 always better, always improving.
00:21:14 I mean, maybe it’s…
00:21:15 I mean, that’s a perception.
00:21:16 That’s our romanticization of things are always better.
00:21:20 Things are getting better, we’d like to believe that.
00:21:22 I mean, you think about the world
00:21:24 from the point of view of bacteria
00:21:25 and bacteria are the first things to emerge
00:21:28 from whatever environment they came from.
00:21:30 And they dominated the planet very, very quickly.
00:21:32 And they haven’t really changed.
00:21:34 Four billion years later, they look exactly the same.
00:21:36 So about four billion years ago,
00:21:38 bacteria started to really run the show.
00:21:42 And then nothing happened for a while.
00:21:44 Nothing happened for two billion years.
00:21:47 Then after two billion years,
00:21:48 we see another single event origin, if you like,
00:21:51 of our own type of cell, the eukaryotic cells.
00:21:53 So cells with a nucleus and lots of stuff going on inside.
00:21:57 Another singular origin.
00:21:58 It only happened once in the history of life on earth.
00:22:01 Maybe it happened multiple times and there’s no evidence.
00:22:03 Everything just disappeared,
00:22:04 but we have to at least take it seriously
00:22:07 that there’s something that stops bacteria
00:22:10 from becoming more complex because they didn’t.
00:22:13 That’s a fact that they emerged four billion years ago.
00:22:17 And something happened two billion years ago,
00:22:19 but the bacteria themselves didn’t change.
00:22:21 They remain bacterial.
00:22:22 So there is no trajectory, necessary trajectory
00:22:26 towards great complexity in human beings at the end of it.
00:22:28 It’s very easy to imagine that without photosynthesis
00:22:31 arising or without eukaryotes arising,
00:22:33 that a planet could be full of bacteria and nothing else.
00:22:36 We’ll get to that because that’s a brilliant invention.
00:22:39 And there’s a few brilliant invention along the way.
00:22:41 But what is life?
00:22:44 If you were to show up on earth,
00:22:46 but to take that time machine,
00:22:47 and you said, asking yourself the question,
00:22:50 is this a stepping stone towards life?
00:22:52 As you step along, when you see the early bacteria,
00:22:57 how would you know it’s life?
00:22:59 And then this is really important question
00:23:01 when you go to other planets and look for life.
00:23:04 Like what is the framework of telling a difference
00:23:08 between a rock and a bacteria?
00:23:12 I mean, the question’s kind of both impossible to answer
00:23:15 and trivial at the same time.
00:23:16 And I don’t like to answer it
00:23:18 because I don’t think there is an answer.
00:23:19 I think we’re trying to describe the process of time.
00:23:22 Those are the most fun questions.
00:23:22 What do you mean there’s no answer?
00:23:23 No, there is no answer.
00:23:24 I mean, there’s lots of,
00:23:25 there are at least 40 or 50 different definitions
00:23:27 of life out there.
00:23:29 And most of them are, well, obviously bad
00:23:33 in one way or another.
00:23:34 I mean, there’s freaks.
00:23:37 I can never remember the exact words that people use,
00:23:39 but there’s a NASA working definition of life,
00:23:43 which more or less says a system,
00:23:46 which is capable of self sustaining system,
00:23:49 capable of evolution or something along those lines.
00:23:52 And I immediately have a problem
00:23:54 with the word self sustaining
00:23:56 because it’s sustained by the environment.
00:23:58 And I know what they’re getting at.
00:24:00 I know what they’re trying to say,
00:24:01 but I pick a hole in that.
00:24:03 And there’s always wags who say,
00:24:04 but you know, by that definition, a rabbit is not alive.
00:24:07 Only a pair of rabbits would be alive
00:24:09 because a single rabbit is incapable of copying itself.
00:24:12 There’s all kinds of pedantic, silly,
00:24:16 but also important objections to any hypothesis.
00:24:19 The real question is what is, you know,
00:24:22 we can argue all day or people do argue all day
00:24:24 about is a virus alive or not?
00:24:27 And it depends on the content.
00:24:29 Most biologists could not agree about that.
00:24:31 So then what about a jumping gene,
00:24:32 a retro element or something that is even simpler
00:24:34 than a virus, but it’s capable of converting
00:24:39 its environment into a copy of itself.
00:24:42 And that’s about as close, this is not a definition,
00:24:45 but this is a kind of a description of life
00:24:47 is that it’s able to parasitize the environment.
00:24:52 And that goes for plants as well as animals
00:24:53 and bacteria and viruses to make a relatively exact copy
00:24:58 of themselves, informationally exact copy of themselves.
00:25:04 By the way, it doesn’t really have to be
00:25:06 a copy of itself, right?
00:25:07 It just has to be, you have to create something
00:25:11 that’s interesting, the way evolution is.
00:25:16 So it is extremely powerful process of evolution,
00:25:19 which is basically make a copy of yourself
00:25:22 and sometimes mess up a little bit.
00:25:25 That seems to work really well.
00:25:26 I wonder if it’s possible to mess up big time
00:25:30 as a standard, as a default.
00:25:32 It’s called a hopeful monster and in principle it can.
00:25:36 Actually, it turns out, I would say that this is due
00:25:40 a reemergence, this is some amazing work
00:25:43 from Michael Levin, I don’t know if you came across him,
00:25:45 but if you haven’t interviewed him,
00:25:47 you should interview him about, yeah.
00:25:50 I’m talking to him in a few days.
00:25:53 Oh, fantastic.
00:25:54 So I mentioned, there’s two people that Andre,
00:25:59 if I may mention, Andre Kapathe is a friend
00:26:02 who’s really admired in the AI community,
00:26:04 said you absolutely must talk to Michael and to Nick.
00:26:09 So of course, I’m a huge fan of yours,
00:26:11 so I’m really fortunate that we can actually
00:26:14 make this happen.
00:26:14 Anyway, you were saying?
00:26:16 Well, Michael Levin is doing amazing work,
00:26:19 basically about the way in which electrical fields
00:26:22 control development and he’s done some work
00:26:25 with planarian worms, so flat worms,
00:26:27 where he’ll tell you all about this,
00:26:29 so I won’t say any more than the minimum,
00:26:30 but basically you can cut their head off
00:26:32 and they’ll redevelop a different, a new head.
00:26:35 But the head that they develop depends,
00:26:37 if you knock out just one iron pump in a membrane,
00:26:42 so you change the electrical circuitry just a little bit,
00:26:45 you can come up with a completely different head.
00:26:47 It can be a head which is similar to those
00:26:49 that diverged 150 million years ago
00:26:52 or it can be a head which no one’s ever seen before,
00:26:54 a different kind of head.
00:26:56 Now that is really, you might say, a hopeful monster.
00:26:59 This is a kind of leap into a different direction.
00:27:02 The only question for natural selection is does it work?
00:27:05 Is the change itself feasible as a single change?
00:27:08 And the answer is yes, it’s just a small change
00:27:09 to a single gene.
00:27:11 And the second thing is it gives rise
00:27:12 to a completely different morphology.
00:27:14 Does it work?
00:27:16 And if it works, that can easily be a shift.
00:27:21 But for it to be a speciation, for it to continue,
00:27:25 for it to give rise to a different morphology over time,
00:27:29 then it has to be perpetuated.
00:27:32 So that shift, that change in that one gene
00:27:37 has to work well enough that it is selected and it goes on.
00:27:41 And copied enough times to where you can really test it.
00:27:44 So the likelihood, it would be lost,
00:27:46 but there will be some occasions where it survives.
00:27:48 And yes, the idea that we can have sudden, fairly abrupt
00:27:51 changes in evolution, I think it’s time for a rebirth.
00:27:54 What about this idea that kind of trying to
00:27:58 mathematize a definition of life and saying how many steps,
00:28:04 the shortest amount of steps it takes to build the thing,
00:28:07 almost like an engineering view of it?
00:28:09 Ah, I like that view.
00:28:11 Because I think that in a sense, that’s not very far away
00:28:14 from what a hypothesis needs to do
00:28:17 to be a testable hypothesis for the origin of life.
00:28:19 You need to spell out, here’s each step,
00:28:22 and here’s the experiment to do for each step.
00:28:24 The idea that we can do it in the lab,
00:28:26 some people say, oh, we’ll have created life
00:28:29 within five years, but ask them what they mean by life.
00:28:34 We have a planet four billion years ago
00:28:36 with these vent systems across the entire surface
00:28:39 of the planet, and we have millions of years if we wanted.
00:28:41 I have a feeling that we’re not talking about
00:28:43 millions of years.
00:28:44 I have a feeling we’re talking about maybe millions
00:28:47 of nanoseconds or picoseconds.
00:28:49 We’re talking about chemistry, which is happening quickly.
00:28:53 But we still need to constrain those steps,
00:28:56 but we’ve got a planet doing similar chemistry.
00:29:00 You asked about a trajectory.
00:29:02 The trajectory is the planetary trajectory.
00:29:05 The planet has properties.
00:29:06 Basically, it’s got a lot of iron at the center of it.
00:29:08 It’s got a lot of electrons at the center of it.
00:29:10 It’s more oxidized on the outside,
00:29:12 partly because of the sun and partly because the heat
00:29:15 of volcanoes puts out oxidized gases.
00:29:17 So the planet is a battery.
00:29:19 It’s a giant battery, and we have a flow of electrons
00:29:23 going from inside to outside in these hydrothermal vents,
00:29:26 and that’s the same topology that a cell has.
00:29:29 A cell is basically just a micro version of the planet,
00:29:34 and there is a trajectory in all of that,
00:29:37 and there’s an inevitability that certain types
00:29:39 of chemical reaction are going to be favored over others,
00:29:42 and there’s an inevitability in what happens in water,
00:29:46 the chemistry that happens in water.
00:29:47 Some will be immiscible with water and will form membranes
00:29:51 and will form insoluble structures,
00:29:53 and nobody really understands water very well,
00:29:58 and it’s another big question.
00:30:00 For experiments on the origin of life, what do you put it in?
00:30:04 What kind of structure do we want to induce in this water?
00:30:07 Because the last thing it’s likely to be
00:30:08 is just kind of bulk water.
00:30:11 How fundamental is water to life, would you say?
00:30:14 I would say pretty fundamental.
00:30:17 I wouldn’t like to say it’s impossible for life
00:30:20 to start any other way, but water is everywhere.
00:30:26 Water’s extremely good at what it does,
00:30:27 and carbon works in water especially well.
00:30:31 So those things, and carbon is everywhere.
00:30:33 So those things together make me think probabilistically,
00:30:35 if we found a thousand life forms, 995 of them
00:30:39 would be carbon based and living in water.
00:30:41 Now the reverse question, if you found a puddle of water
00:30:45 elsewhere and some carbon, no, just a puddle of water.
00:30:50 Is a puddle of water a pretty damn good indication
00:30:53 that life either exists here or has once existed here?
00:31:00 No.
00:31:02 So it doesn’t work the other way.
00:31:04 I think you need a living planet.
00:31:07 You need a planet which is capable
00:31:09 of turning over its surface.
00:31:10 It needs to be a planet with water.
00:31:12 It needs to be capable of bringing those electrons
00:31:16 from inside to the outside.
00:31:18 It needs to turn over its surface.
00:31:19 It needs to make that water work and turn it into hydrogen.
00:31:22 So I think you need a living planet.
00:31:24 But once you’ve got the living planet,
00:31:25 I think the rest of it is kind of thermodynamics all the way.
00:31:29 So if you were to run Earth over a million times up
00:31:34 to this point, maybe beyond, to the end,
00:31:37 let’s run it to the end, what is it?
00:31:41 How much variety is there?
00:31:42 You kind of spoke to this trajectory
00:31:45 that the environment dictates chemically,
00:31:49 I don’t know in which other way, spiritually,
00:31:53 I don’t know, like dictates kind of the direction
00:31:57 of this giant machine that seems chaotic,
00:32:01 but it does seem to have order in the steps it’s taking.
00:32:06 How often will life, how often will bacteria emerge?
00:32:11 How often will something like humans emerge?
00:32:13 How much variety do you think there would be?
00:32:15 I think at the level of bacteria, not much variety.
00:32:19 I think we would get, that’s how many times
00:32:22 you say you want to run it, a million times.
00:32:24 I would say at least a few hundred thousand will get bacteria again.
00:32:28 Oh, wow, nice.
00:32:29 Because I think there’s some level of inevitability
00:32:31 that a wet rocky planet will give rise
00:32:33 through the same processes to something very close.
00:32:38 I think this is not something I’d have thought
00:32:40 a few years ago, but working with a PhD student
00:32:43 of mine, Stuart Harrison, he’s been thinking
00:32:45 about the genetic code, and we’ve just been publishing
00:32:47 on that, there are patterns that you can discern in the code,
00:32:51 or he has discerned in the code,
00:32:53 that if you think about them in terms of,
00:32:56 we start with CO2 and hydrogen,
00:32:57 and these are the first steps of biochemistry,
00:32:59 you come up with a code which is very similar
00:33:01 to the code that we see.
00:33:03 So it wouldn’t surprise me any longer
00:33:05 if we found life on Mars and it had a genetic code
00:33:07 that was not very different to the genetic code
00:33:09 that we have here, without it just being transferred across.
00:33:13 There’s some inevitability about the whole
00:33:16 of the beginnings of life, in my view.
00:33:18 That’s really promising, because if the basic chemistry
00:33:21 is tightly linked to the genetic code,
00:33:25 that means we can interact with other life
00:33:29 if it exists out there.
00:33:30 Well, that’s potentially.
00:33:32 That’s really exciting, if that’s the case.
00:33:34 Okay, but then bacteria.
00:33:36 We’ve got bacteria.
00:33:37 Yeah.
00:33:39 How easy is photosynthesis?
00:33:42 Much harder, I would say.
00:33:44 Let’s actually go there.
00:33:46 Let’s go through the inventions.
00:33:47 Yeah.
00:33:49 What is photosynthesis?
00:33:51 And why is it hard?
00:33:52 Well, there are different forms.
00:33:55 I mean, basically, you’re taking hydrogen
00:33:57 and you’re sticking it onto CO2,
00:33:59 and it’s powered by the sun.
00:34:00 Question is, where are you taking the hydrogen from?
00:34:02 And in photosynthesis that we know in plants,
00:34:05 it’s coming from water.
00:34:06 So you’re using the power of the sun to split water,
00:34:08 take out the hydrogen, stick it onto CO2,
00:34:11 and the oxygen is a waste product,
00:34:13 and you just throw it out, throw it away.
00:34:15 So it’s the single greatest planetary pollution event
00:34:19 in the whole history of the Earth.
00:34:21 The pollutant being oxygen.
00:34:22 Yes, yeah.
00:34:24 It also made possible animals.
00:34:26 You can’t have large, active animals
00:34:28 without an oxygenated atmosphere,
00:34:30 at least not in the sense that we know on Earth.
00:34:33 So that’s a really big invention
00:34:35 in the history of Earth. Huge invention, yes.
00:34:37 And it happened once.
00:34:38 There’s a few things that happen once on Earth,
00:34:40 and you’re always stuck with this problem.
00:34:42 Once it happened, did it become so good so quickly
00:34:44 that it precluded the same thing happening ever again?
00:34:48 Or are there other reasons?
00:34:49 And we really have to look at each one in turn
00:34:51 and think, why did it only happen once?
00:34:53 In this case, it’s really difficult to split water.
00:34:57 It requires a lot of power,
00:34:59 and that power, you’re effectively separating charge
00:35:01 across a membrane, and the way in which you do it,
00:35:04 if it doesn’t all rush back
00:35:05 and kind of cause an explosion right at the site,
00:35:08 requires really careful wiring.
00:35:10 And that wiring, it can’t be easy to get it right
00:35:14 because the plants that we see around us,
00:35:18 they have chloroplasts.
00:35:19 Those chloroplasts were cyanobacteria ones.
00:35:21 Those cyanobacteria are the only group of bacteria
00:35:23 that can do that type of photosynthesis.
00:35:25 So there’s plenty of opportunity.
00:35:28 So not even many bacteria.
00:35:29 So who invented photosynthesis?
00:35:32 The cyanobacteria, or their ancestors.
00:35:34 And there’s not many?
00:35:36 No other bacteria can do
00:35:37 what’s called oxygenic photosynthesis.
00:35:39 Lots of other bacteria can split.
00:35:42 I mean, you can take your hydrogen from somewhere else.
00:35:44 You can take it from hydrogen sulfide
00:35:45 bubbling out of a hydrothermal vent.
00:35:47 Grab your two hydrogens.
00:35:49 The sulfur is the waste now.
00:35:52 You can do it from iron.
00:35:53 You can take electrons.
00:35:54 So the early oceans were probably full of iron.
00:35:56 You can take an electron from ferrous iron,
00:35:59 so iron two plus and make it iron three plus,
00:36:01 which now precipitates as rust,
00:36:03 and you take a proton from the acidic early ocean,
00:36:07 stick it there.
00:36:08 Now you’ve got a hydrogen atom.
00:36:09 Stick it onto CO2.
00:36:10 You’ve just done the trick.
00:36:12 The trouble is you bury yourself in rusty iron.
00:36:16 And with sulfur, you can bury yourself in sulfur.
00:36:18 One of the reasons oxygenic photosynthesis
00:36:20 is so much better is that the waste product is oxygen,
00:36:23 which just bubbles away.
00:36:26 That seems like extremely unlikely,
00:36:29 and it’s extremely essential
00:36:30 for the evolution of complex organisms
00:36:33 because of all the oxygen.
00:36:36 Yeah, and that didn’t accumulate quickly either.
00:36:39 So it’s converting, what is it?
00:36:42 It’s converting energy from the sun
00:36:44 and the resource of water
00:36:46 into the resource needed for animals.
00:36:50 Both resources needed for animals.
00:36:52 We need to eat, and we need to burn the food,
00:36:54 and we’re eating plants,
00:36:57 which are getting their energy from the sun,
00:36:59 and we’re burning it with their waste product,
00:37:01 which is the oxygen.
00:37:02 So there’s a lot of kind of circularity in that,
00:37:04 but without an oxygenated planet,
00:37:07 you couldn’t really have predation.
00:37:12 You can have animals,
00:37:14 but you can’t really have animals
00:37:16 that go around and eat each other.
00:37:17 You can’t have ecosystems as we know them.
00:37:19 Well, let’s actually step back.
00:37:21 What about eukaryotic versus prokaryotic cells, prokaryotes?
00:37:25 What are each of those,
00:37:28 and how big of an invention is that?
00:37:31 I personally think that’s the single biggest invention
00:37:33 in the whole history of life.
00:37:34 Exciting.
00:37:35 So what are they?
00:37:36 Can you explain?
00:37:37 Yeah, so I mentioned bacteria and archaea.
00:37:40 These are both prokaryotes.
00:37:43 They’re basically small cells that don’t have a nucleus.
00:37:45 If you look at them under a microscope,
00:37:47 you don’t see much going on.
00:37:48 If you look at them under a super resolution microscope,
00:37:50 then they’re fantastically complex.
00:37:53 In terms of their molecular machinery, they’re amazing.
00:37:55 In terms of their morphological appearance
00:37:58 under a microscope, they’re really small and really simple.
00:38:03 The earliest life that we can physically see
00:38:04 on the planet are stromatolites,
00:38:06 which are made by things like cyanobacteria,
00:38:08 and they’re large superstructures.
00:38:11 Effectively, biofilms plated on top of each other,
00:38:14 and you end up with quite large structures
00:38:17 that you can see in the fossil record.
00:38:19 But they never came up with animals.
00:38:23 They never came up with plants.
00:38:24 They came up with multicellular things,
00:38:26 filamentous cyanobacteria, for example.
00:38:28 They’re just long strings of cells.
00:38:31 But the origin of the eukaryotic cell
00:38:34 seems to have been what’s called an endosymbiosis,
00:38:37 so one cell gets inside another cell.
00:38:39 And I think that that’s transformed
00:38:42 the energetic possibilities of life.
00:38:43 So what we end up with is a kind of supercharged cell,
00:38:48 which can have a much larger nucleus
00:38:50 with many more genes, all supported.
00:38:54 If you think about it, you could think about it
00:38:55 as multi bacterial power without the overhead.
00:38:58 So you’ve got a cell and it’s got bacteria living in it,
00:39:00 and those bacteria are providing it
00:39:02 with the energy currency it needs.
00:39:04 But each bacterium has a genome of its own,
00:39:07 which costs a fair amount of energy to express,
00:39:10 to kind of turn over and convert into proteins and so on.
00:39:15 What the mitochondria did,
00:39:16 which are these power packs in our own cells,
00:39:20 they were bacteria once,
00:39:22 and they threw away virtually all their genes.
00:39:24 They’ve only got a few left.
00:39:25 So mitochondria is, like you said,
00:39:27 is the bacteria that got inside a cell
00:39:30 and then throw away all this stuff it doesn’t need to,
00:39:32 survive inside the cell, and then kept what?
00:39:35 So what we end up with,
00:39:36 so it kept always a handful of genes.
00:39:38 In our own case, 37 genes.
00:39:41 But there’s a few protists, which are single celled things
00:39:44 that have got as many as 70 or 80 genes.
00:39:47 So it’s not always the same, but it’s always a small number.
00:39:51 And you can think of it as a paired down power pack
00:39:54 where the control unit has really been,
00:39:56 has been kind of paired down to almost nothing.
00:39:58 So you’re putting out the same power,
00:40:00 but the investment in the overheads is really paired down.
00:40:04 That means that you can support
00:40:05 a much larger nuclear genome.
00:40:08 So we’ve gone up in the number of genes,
00:40:10 but also the amount of power you have
00:40:12 to convert those genes into proteins.
00:40:14 We’ve gone up about fourfold in the number of genes,
00:40:17 but in terms of the size of genomes
00:40:19 and your ability to make the building blocks,
00:40:21 make the proteins, we’ve gone up 100,000 fold or more.
00:40:25 So it’s huge step change in the possibilities of evolution.
00:40:29 And it’s interesting then that the only two occasions
00:40:33 that complex life has arisen on Earth,
00:40:35 plants and animals,
00:40:38 fungi you could say are complex as well,
00:40:40 but they don’t form such complex morphology
00:40:42 as plants and animals.
00:40:44 Start with a single cell.
00:40:45 They start with an oocyte and a sperm
00:40:48 fused together to make a zygote.
00:40:50 So we start development with a single cell
00:40:52 and all the cells in the organism have identical DNA.
00:40:56 And you switch off in the brain,
00:40:58 you switch off these genes and you switch on those genes
00:41:00 and liver, you switch off those
00:41:01 and you switch on a different set.
00:41:04 And the standard evolutionary explanation for that
00:41:06 is that you’re restricting conflict.
00:41:08 You don’t have a load of genetically different cells
00:41:10 that are all fighting each other.
00:41:13 And so it works.
00:41:14 The trouble with bacteria, they form these biofilms
00:41:17 and they’re all genetically different.
00:41:18 And effectively they’re incapable
00:41:21 of that level of cooperation.
00:41:23 They would get in a fight.
00:41:26 Okay, so why is this such a difficult invention
00:41:31 of getting this bacteria inside
00:41:33 and becoming an engine which the mitochondria is?
00:41:37 Why do you assign it such great importance?
00:41:40 Is it great importance in terms of the difficulty
00:41:42 of how it was to achieve or great importance
00:41:44 in terms of the impact it had on life?
00:41:46 Both.
00:41:48 It had a huge impact on life
00:41:49 because if that had not happened,
00:41:52 you can be certain that life on earth
00:41:54 would be bacterial only.
00:41:56 And that took a really long time too.
00:41:58 It took 2 billion years.
00:41:59 And it hasn’t happened since to the best of our knowledge.
00:42:02 So it looks as if it’s genuinely difficult.
00:42:05 And if you think about it then
00:42:06 from just an informational perspective,
00:42:08 you think bacteria have got,
00:42:12 they structure their information differently.
00:42:15 So a bacterial cell has a small genome,
00:42:17 you might have 4,000 genes in it,
00:42:19 but a single E. coli cell has access
00:42:21 to about 30,000 genes potentially.
00:42:24 It’s got a kind of metagenome
00:42:26 where other E. coli out there
00:42:27 have got different gene sets
00:42:29 and they can switch them around between themselves.
00:42:31 And so you can generate a huge amount of variation
00:42:34 and they’ve got more,
00:42:36 an E. coli metagenome is larger than the human genome.
00:42:40 We own 20,000 genes or something.
00:42:43 So, and they’ve had 4 billion years of evolution
00:42:46 to work out what can I do
00:42:48 and what can’t I do with this metagenome?
00:42:51 And the answer is you’re stuck, you’re still bacteria.
00:42:54 So they have explored genetic sequence space
00:42:58 far more thoroughly than eukaryotes ever did
00:43:01 because they’ve had twice as long at least
00:43:03 and they’ve got much larger populations
00:43:05 and they never got around this problem.
00:43:08 So why can’t they?
00:43:09 It seems as if you can’t solve it with information alone.
00:43:12 So what’s the problem?
00:43:14 The problem is structure.
00:43:16 If the very first cells needed an electrical charge
00:43:21 on their membrane to grow and in bacteria,
00:43:23 it’s the outer membrane that surrounds the cell
00:43:26 which is electrically charged.
00:43:28 You try and scale that up
00:43:29 and you’ve got a fundamental design problem,
00:43:31 you’ve got an engineering problem.
00:43:33 And there are examples of it
00:43:35 and what we see in all these cases
00:43:37 is what’s known as extreme polyploidy,
00:43:38 which is to say they have tens of thousands of copies
00:43:41 of their complete genome,
00:43:42 which is energetically hugely expensive
00:43:45 and you end up with a large bacteria
00:43:49 with no further development.
00:43:52 What you need is to incorporate
00:43:55 these electrically charged power pack units inside
00:43:58 with their control units intact
00:44:01 and for them not to conflict so much with the host cell
00:44:03 that it all goes wrong.
00:44:05 Perhaps it goes wrong more often than not.
00:44:07 And then you change the topology of the cell.
00:44:10 Now you don’t necessarily have any more DNA
00:44:14 than a giant bacterium with extreme polyploidy,
00:44:16 but what you’ve got is an asymmetry.
00:44:19 You now have a giant nuclear genome
00:44:21 which surrounded by lots of subsidiary energetic genomes
00:44:25 that do all the, they’re the control units
00:44:27 that are doing all the control of energy generation.
00:44:32 Could this have been done gradually
00:44:33 or does it have to be done,
00:44:35 the power pack has to be all intact
00:44:38 and ready to go and working?
00:44:40 I mean, it’s a kind of step change
00:44:41 in the possibilities of evolution,
00:44:43 but it doesn’t happen overnight.
00:44:44 It’s gonna still require multiple, multiple generations.
00:44:47 So it could take millions of years.
00:44:50 It could take shorter times.
00:44:52 There’s another thing I would like to put the number of steps
00:44:54 and try and work out what’s required at each step.
00:44:56 And we are trying to do that with sex for example.
00:44:58 You can’t have a very large genome
00:45:00 unless you have sex at that point.
00:45:02 So what are the changes to go
00:45:03 from bacterial recombination to eukaryotic recombination?
00:45:07 What do you need to do?
00:45:09 Why do we go from passing around bits of DNA
00:45:12 as if it’s loose change to fusing cells together,
00:45:15 lining up the chromosomes,
00:45:16 recombining across the chromosomes,
00:45:18 and then going through two rounds of cell division
00:45:20 to produce your gametes?
00:45:22 All eukaryotes do it that way.
00:45:24 So again, why switch?
00:45:27 What are the drivers here?
00:45:28 So there’s a lot of time, there’s a lot of evolution,
00:45:31 but as soon as you’ve got cells living inside another cell,
00:45:34 what you’ve got is a new design.
00:45:36 You’ve got new potential that you didn’t have before.
00:45:39 So the cell living inside another cell, that design
00:45:44 allows for better storage of information,
00:45:48 better use of energy, more delegation,
00:45:52 like a hierarchical control of the whole thing.
00:45:55 And then somehow that leads to ability
00:45:58 to have multi cell organisms.
00:46:00 I’m not sure that you have hierarchical control necessarily,
00:46:03 but you’ve got a system where you can have
00:46:06 a much larger information storage depot in the nucleus.
00:46:09 You can have a much larger genome.
00:46:11 And that allows multicellularity, yes,
00:46:13 because it allows you, it’s a funny thing,
00:46:18 to have an animal where I have 70% of my genes
00:46:24 switched on in my brain,
00:46:25 and a different 50% switched on in my liver or something,
00:46:28 you’ve got to have all those genes in the egg cell
00:46:30 at the very beginning,
00:46:31 and you’ve got to have a program of development
00:46:35 which says, okay, you guys switch off those genes
00:46:37 and switch on those genes, and you guys, you do that.
00:46:40 But all the genes are there at the beginning.
00:46:42 That means you’ve got to have a lot of genes in one cell
00:46:44 and you’ve got to be able to maintain them.
00:46:45 And the problem with bacteria is they don’t get close
00:46:47 to having enough genes in one cell.
00:46:49 So if you were to try and make a multicellular organism
00:46:52 from bacteria, you’d bring different types
00:46:54 of bacteria together and hope they’ll cooperate.
00:46:56 And the reality is they don’t.
00:46:57 That’s really, really tough to do.
00:46:59 Yeah.
00:47:00 We know they don’t because it doesn’t exist.
00:47:02 We have the data as far as we know.
00:47:04 I’m sure there’s a few special ones
00:47:06 and they dead off quickly.
00:47:08 I’d love to know some of the most fun things
00:47:09 bacteria have done since.
00:47:12 Oh, there’s a few.
00:47:13 I mean, they can do some pretty funky things.
00:47:15 And this is broad brushstroke that I’m talking about.
00:47:18 Yes.
00:47:19 Generally speaking.
00:47:21 So how was, so another fun invention.
00:47:25 Us humans seem to utilize it well,
00:47:27 but you say it’s also very important early on is sex.
00:47:31 So what is sex?
00:47:34 Just asking for a friend.
00:47:36 And when was it invented and how hard was it to invent,
00:47:39 just as you were saying, and why was it invented?
00:47:42 Why, how hard was it and when?
00:47:45 I have a PhD student who’s been working on this
00:47:47 and we’ve just published a couple of papers on sex.
00:47:49 Yes, yes, yes.
00:47:50 What do you publish?
00:47:51 Does biology, is it biology, genetics, journals?
00:47:55 This is actually PNAS,
00:47:57 which is Proceedings of the National Academy.
00:48:00 Broad, big, big picture stuff.
00:48:02 Everyone’s interested in sex.
00:48:03 Yeah.
00:48:04 And the job of a biologist is to make sex dull.
00:48:07 Yes, yeah, that’s a beautiful way to put it.
00:48:10 Okay, so when was it invented?
00:48:13 It was invented with eukaryotes about two billion years ago.
00:48:16 All eukaryotes share the same basic mechanism
00:48:20 that you produce gametes, the gametes fuse together.
00:48:23 So a gamete is the egg cell and the sperm.
00:48:26 They’re not necessarily even different in size or shape.
00:48:29 So the simplest eukaryotes produce
00:48:31 what are called motile gametes.
00:48:32 They’re all like sperm and they all swim around.
00:48:34 They find each other, they fuse together.
00:48:36 They don’t have kind of much going on there beyond that.
00:48:39 And then these are haploid,
00:48:43 which is to say we all have two copies of our genome
00:48:46 and the gametes have only a single copy of the genome.
00:48:49 So when they fuse together, you now become diploid again,
00:48:51 which is to say you now have two copies of your genome.
00:48:55 And what you do is you line them all up
00:48:57 and then you double everything.
00:49:01 So now we have four copies of the complete genome.
00:49:03 And then we crisscross between all of these things.
00:49:05 So we take a bit from here and stick it on there
00:49:07 and a bit from here and we stick it on here.
00:49:09 That’s recombination.
00:49:11 And then we go through two rounds of cell division.
00:49:14 So we divide in half.
00:49:15 So now the two daughter cells have two copies
00:49:18 and we divide in half again.
00:49:19 Now we have some gametes,
00:49:21 each of which has got a single copy of the genome.
00:49:24 And that’s the basic ground plan
00:49:26 for what’s called meiosis and Syngami.
00:49:29 That’s basically sex.
00:49:31 And it happens at the level of single celled organisms.
00:49:33 And it happens pretty much the same way in plants
00:49:35 and pretty much the same way in animals and so on.
00:49:38 And it’s not found in any bacteria.
00:49:40 They switch things around using the same machinery
00:49:43 and they take up a bit of DNA from the environment.
00:49:44 They take out this bit and stick in that bit
00:49:46 and it’s the same molecular machinery they’re using to do it.
00:49:50 So what about the kind of, you said, find each other,
00:49:52 this kind of imperative, find each other.
00:49:56 What is that?
00:49:57 Like, is that?
00:49:58 Well, you’ve got a few cells together.
00:50:00 So the bottom line on all of this is bacteria.
00:50:04 I mean, it’s kind of simple when you’ve figured it out
00:50:07 and figuring it out, this is not me,
00:50:09 this is my PhD student, Marco Colnaghi.
00:50:13 And in effect, if you’re doing lateral,
00:50:16 you’re a Nicoli cell, you’ve got 4,000 genes.
00:50:19 You wanna scale up to a eukaryotic size.
00:50:22 I wanna have 20,000 genes.
00:50:25 And I need to maintain my genome
00:50:27 so it doesn’t get shot to pieces by mutations.
00:50:30 And I’m gonna do it by lateral gene transfer.
00:50:32 So I know I’ve got a mutation in a gene.
00:50:35 I don’t know which gene it is because I’m not sentient,
00:50:38 but I know I can’t grow.
00:50:40 I know all my regulation systems are saying,
00:50:42 something wrong here, something wrong, pick up some DNA,
00:50:44 pick up a bit of DNA from the environment.
00:50:47 If you’ve got a small genome,
00:50:49 the chances of you picking up the right bit of DNA
00:50:50 from the environment is much higher
00:50:52 than if you’ve got a genome of 20,000 genes.
00:50:54 To do that, you’ve effectively got to be picking up DNA
00:50:58 all the time, all day long and nothing else.
00:51:00 And you’re still gonna get the wrong DNA.
00:51:02 You’ve got to pick up large chunks.
00:51:03 And in the end, you’ve got to align them.
00:51:05 You’re forced into sex, to coin a phrase.
00:51:10 So you’re…
00:51:11 You’re forced.
00:51:12 So there is a kind of incentive.
00:51:18 If you wanna have a large genome,
00:51:20 you’ve got to prevent it mutating to nothing.
00:51:22 That will happen with bacteria.
00:51:23 This is another reason why bacteria
00:51:25 can’t have a large genome.
00:51:26 But as soon as you give them the power pack,
00:51:28 as soon as you give eukaryotic cells the power pack
00:51:30 that allows them to increase the size of their genome,
00:51:33 then you face the pressure
00:51:34 that you’ve got to maintain its quality.
00:51:36 You’ve got to stop it just mutating away.
00:51:38 What about sexual selection?
00:51:39 So the finding, like, I don’t like this one.
00:51:44 I don’t like this one.
00:51:45 This one seems all right.
00:51:47 Like, what’s the…
00:51:49 Is it…
00:51:50 At which point does it become less random?
00:51:52 It’s hard to know.
00:51:54 Because eukaryotes just kind of float around.
00:51:56 Just kind of have…
00:51:57 Yeah, I mean, is there sexual selection
00:51:59 in single celled eukaryotes?
00:52:00 There probably is.
00:52:01 It’s just that I don’t know very much about it.
00:52:02 By the time we get onto…
00:52:03 You don’t hang out with the eukaryotes.
00:52:05 Well, I do all the time, but…
00:52:07 But you can’t communicate with them yet.
00:52:09 Yeah, a peacock or something.
00:52:10 Yes.
00:52:12 The kind of standard answer,
00:52:14 this is not quite what I work on,
00:52:15 but the standard answer is that it’s female mate choice.
00:52:19 She is looking for good genes.
00:52:22 And if you can have a tail that’s like this
00:52:25 and still survive, still be alive,
00:52:28 not actually have been taken down by the nearest predator,
00:52:30 then you must’ve got pretty good genes
00:52:31 because despite this handicap, you’re able to survive.
00:52:36 So those are like human interpretable things,
00:52:38 like with a peacock.
00:52:39 But I wonder, I’m sure echoes of the same thing
00:52:43 are there with more primitive organisms.
00:52:46 Basically your PR, like how you advertise yourself
00:52:51 that you’re worthy of.
00:52:54 Absolutely.
00:52:54 So one big advertisement is the fact
00:52:56 that you survived it all.
00:52:58 Let me give you one beautiful example of an algal bloom.
00:53:03 And this can be a sign of bacteria.
00:53:05 It’s gonna be in bacteria.
00:53:07 So if suddenly you pump nitrate or phosphate
00:53:10 or something into the ocean and everything goes green,
00:53:13 you end up with all this algae growing there.
00:53:18 A viral infection or something like that
00:53:20 can kill the entire bloom overnight.
00:53:23 And it’s not that the virus takes out everything overnight.
00:53:26 It’s that most of the cells in that bloom kill themselves
00:53:29 before the virus can get onto them.
00:53:31 And it’s through a form of cell death
00:53:33 called programmed cell death.
00:53:35 And we do the same things.
00:53:36 It’s how we have the gaps between our fingers and so on.
00:53:39 It’s how we craft synapses in the brain.
00:53:43 It’s fundamental again to multicellular life.
00:53:47 They have the same machinery in these algal blooms.
00:53:51 How do they know who dies?
00:53:52 The answer is they will often put out a toxin.
00:53:56 And that toxin is kind of a challenge to you.
00:54:00 Either you can cope with the toxin or you can’t.
00:54:03 If you can cope with it, you form a spore
00:54:06 and you will go on to become the next generation.
00:54:09 You’re forming kind of a resistance spore.
00:54:11 You sink down a little bit, you get out of the way,
00:54:14 you’re out of the, you can’t be attacked by a virus
00:54:17 if you’re a spore or it’s not so easily.
00:54:19 Whereas if you can’t deal with that toxin,
00:54:21 you pull the plug and you trigger your death apparatus
00:54:25 and you kill yourself.
00:54:27 Oh, so it’s truly life and death selection.
00:54:29 Yeah, so it’s really, it’s a challenge.
00:54:31 And this is a bit like sexual selection.
00:54:33 It’s not so, they’re all pretty much genetically identical,
00:54:36 but they’ve had different life histories.
00:54:39 So have you had a tough day?
00:54:41 Did you happen to get infected by this virus?
00:54:44 Or did you run out of iron?
00:54:45 Or did you get a bit too much sun?
00:54:47 Whatever it may be, if this extra stress of the toxin
00:54:51 just pushes you over the edge,
00:54:52 then you have this binary choice.
00:54:53 Either you’re the next generation
00:54:55 or you kill yourself now using this same machinery.
00:54:57 It’s also actually exactly the way I approach dating,
00:55:00 but that’s probably why I’m single.
00:55:03 Okay, what about if we can step back, DNA?
00:55:07 Just mechanism of storing information.
00:55:10 RNA, DNA, how big of an invention was that?
00:55:13 That seems to be, that seems to be fundamental
00:55:16 to like something deep within what life is,
00:55:22 is the ability, as you said,
00:55:24 to kind of store and propagate information.
00:55:28 But then you also kind of infer that
00:55:29 with your and your students work,
00:55:31 that there’s a deep connection between the chemistry
00:55:35 and the ability to have this kind of genetic information.
00:55:39 So how big of an invention is it
00:55:41 to have a nice representation,
00:55:43 nice hard drive for info to pass on?
00:55:46 Huge, I suspect.
00:55:47 I mean, but when I was talking about the code,
00:55:50 you see the code in RNA as well.
00:55:52 And RNA almost certainly came first.
00:55:56 And there’s been an idea going back decades
00:55:58 called the RNA world,
00:55:59 because RNA in theory can copy itself
00:56:03 and can catalyze reactions.
00:56:04 So it kind of cuts out this chicken and egg loop.
00:56:07 So DNA as possible is not that special.
00:56:09 So RNA, RNA is the thing that does the work really.
00:56:13 And the code lies in RNA.
00:56:15 The code lies in the interactions
00:56:16 between RNA and amino acids.
00:56:18 And it still is there today in the ribosome, for example,
00:56:21 which is just kind of a giant ribozyme,
00:56:23 which is to say it’s an enzyme that’s made of RNA.
00:56:28 So getting to RNA, I suspect is probably not that hard,
00:56:34 but getting from RNA, how do you,
00:56:37 you know, there’s multiple different types of RNA now.
00:56:39 How do you distinguish?
00:56:42 This is something we’re actively thinking about.
00:56:43 How do you distinguish between,
00:56:45 you know, a random population of RNA?
00:56:47 Some of them go on to become messenger RNA.
00:56:50 This is the transcript of the code
00:56:52 of the gene that you want to make.
00:56:54 Some of them become transfer RNA,
00:56:56 which is kind of the unit that holds the amino acid
00:56:59 that’s going to be polymerized.
00:57:01 Some of them become ribosomal RNA,
00:57:04 which is the machine which is joining them all up together.
00:57:07 How do they discriminate themselves?
00:57:10 And, you know, is some kind of phase transition
00:57:12 going on there?
00:57:13 I don’t know.
00:57:14 It’s a difficult question.
00:57:16 And we’re now in the region of biology
00:57:18 where information is coming in.
00:57:19 But the thing about RNA is very, very good at what it does.
00:57:22 But the largest genome supported by RNA
00:57:25 are RNA viruses like HIV, for example.
00:57:28 They’re pretty small.
00:57:29 And so there’s a limit to how complex life could be
00:57:34 unless you come up with DNA,
00:57:36 which chemically is a really small change.
00:57:39 But how easy it is to make that change,
00:57:41 I don’t really know.
00:57:42 As soon as you’ve got DNA,
00:57:43 then you’ve got an amazingly stable molecule
00:57:46 for information storage.
00:57:48 And you can do absolutely anything.
00:57:50 But how likely that transition from RNA to DNA was,
00:57:53 I don’t know either.
00:57:54 How much possibility is there for variety
00:57:56 in ways to store information?
00:58:00 Because it seems to be very,
00:58:01 there’s specific characteristics
00:58:03 about the programming language of DNA.
00:58:06 Yeah, there’s a lot of work going on
00:58:08 on what’s called the xenodNA or RNA.
00:58:11 Can we replace the bases themselves,
00:58:15 the letters, if you like, in RNA or DNA?
00:58:18 Can we replace the backbone?
00:58:19 Can we replace, for example, phosphate with arsenate?
00:58:23 Can we replace the sugar ribose or deoxyribose
00:58:25 with a different sugar?
00:58:26 And the answer is yes, you can.
00:58:29 Within limits, there’s not an infinite space there.
00:58:34 Arsenate doesn’t really work
00:58:36 if the bonds are not as strong as phosphate.
00:58:38 It’s probably quite hard to replace phosphate.
00:58:42 It’s possible to do it.
00:58:43 The question to me is why is it this way?
00:58:47 Is it because there was some form of selection
00:58:50 that this is better than the other forms
00:58:52 and there were lots of competing forms
00:58:53 of information storage early on
00:58:55 and this one was the one that worked out?
00:58:56 Or was it kind of channeled that way,
00:58:58 that these are the molecules that you’re dealing with
00:59:01 and they work?
00:59:03 And I’m increasingly thinking it’s that way,
00:59:05 that we’re channeled towards ribose, phosphate,
00:59:08 and the bases that are used.
00:59:11 But there are 200 different letters
00:59:14 kicking around out there that could have been used.
00:59:17 It’s such an interesting question.
00:59:18 If you look in the programming world in computer science,
00:59:21 there’s a programming language called JavaScript,
00:59:24 which was written super quickly.
00:59:26 It’s a giant mess, but it took over the world.
00:59:29 And it was kind of a…
00:59:30 Sounds very biological.
00:59:31 It was kind of a running joke that like,
00:59:35 like surely this can’t be,
00:59:37 this is a terrible programming language.
00:59:39 It’s a giant mess.
00:59:40 It’s full of bugs.
00:59:41 It’s so easy to write really crappy code,
00:59:44 but it took over all a front end development
00:59:48 in the web browser.
00:59:49 If you have any kind of dynamic interactive website,
00:59:52 it’s usually running JavaScript.
00:59:54 And it’s now taking over much of the backend,
00:59:57 which is like the serious heavy duty computational stuff.
01:00:00 And it’s become super fast
01:00:02 with the different compilation engines that are running it.
01:00:06 So it’s like, it really took over the world.
01:00:08 It’s very possible that this initially crappy derided language
01:00:13 actually takes everything over.
01:00:14 And then the question is,
01:00:17 did human civilization always strive towards JavaScript?
01:00:21 Or was JavaScript just the first programming language
01:00:25 that ran on the browser and still sticky?
01:00:27 The first is the sticky one.
01:00:29 And so it wins over anything else because it was first.
01:00:32 And I don’t think that’s answerable, right?
01:00:34 But it’s good to ask that.
01:00:37 I suppose in the lab,
01:00:38 you can’t run it with programming languages,
01:00:43 but in biology you can probably do some kind of
01:00:47 small scale evolutionary test to try to infer,
01:00:53 which is which.
01:00:54 Yeah.
01:00:55 I mean, in a way we’ve got the hardware
01:00:57 and the software here.
01:00:58 And the hardware is maybe the DNA and the RNA itself.
01:01:02 And then the software perhaps is more about the code.
01:01:06 Did the code have to be this way?
01:01:07 Could it have been a different way?
01:01:09 People talk about the optimization of the code
01:01:11 and there’s some suggestion for that.
01:01:14 I think it’s weak actually.
01:01:16 But you could imagine you could come out
01:01:17 with a million different codes
01:01:18 and this would be one of the best ones.
01:01:22 Well, we don’t know this.
01:01:24 Well, I mean, people have tried to model it
01:01:27 based on the effect that mutations would have.
01:01:31 So no, you’re right.
01:01:32 We don’t know because that’s a single assumption
01:01:34 that a mutation is what’s being selected on there.
01:01:37 And there’s other possibilities too.
01:01:39 I mean, there does seem to be a resilience
01:01:41 and a redundancy to the whole thing.
01:01:43 It’s hard to mess up and the way you mess it up
01:01:47 often is likely to produce interesting results.
01:01:51 So it’s…
01:01:52 Are you talking about JavaScript or the genetic code now?
01:01:55 Yeah, well, I mean, it’s almost,
01:01:57 biology is underpinned by this kind of mess as well.
01:02:00 And you look at the human genome and it’s full of stuff
01:02:03 that is really either broken or dysfunctional
01:02:06 or was a virus once, whatever it may be.
01:02:08 And somehow it works.
01:02:09 And maybe we need a lot of this mess.
01:02:11 We know that some functional genes are taken from this mess.
01:02:15 So what about, you mentioned the predatory behavior.
01:02:19 Yeah.
01:02:20 We talked about sex.
01:02:21 What about violence, predator and prey dynamics?
01:02:26 When was that invented?
01:02:29 And poetic and biological ways of putting it,
01:02:33 how do you describe predator prey relationship?
01:02:37 Is it a beautiful dance or is it a violent atrocity?
01:02:43 Well, I guess it’s both, isn’t it?
01:02:44 I mean, when does it start?
01:02:45 It starts in bacteria.
01:02:46 You see these amazing predators.
01:02:49 Della Vibrio is one that Lynn Margulis
01:02:51 used to talk about a lot.
01:02:53 It’s got a kind of a drill piece
01:02:55 that drills through the wall
01:02:57 and the membrane of the bacterium.
01:02:58 And then it effectively eats the bacterium
01:03:00 from just inside the periplasmic space
01:03:03 and makes copies of itself that way.
01:03:04 So that’s straight predation.
01:03:06 There are predators among bacteria.
01:03:08 So predation in that, sorry to interrupt,
01:03:10 means you murder somebody
01:03:12 and use their body as a resource in some way.
01:03:17 Yeah.
01:03:18 But it’s not parasitic in that
01:03:21 you need them to be still alive.
01:03:23 No, no, I mean, predation is you kill them, really.
01:03:26 You murder.
01:03:27 Parasites, so you kind of live on them.
01:03:30 Okay, so, but it seems the predator is the really popular.
01:03:34 So what we see if we go back 560, 570 million years
01:03:42 before the Cambrian explosion,
01:03:44 there is what’s known as the Ediacaran fauna,
01:03:48 or sometimes they call Vendobionts,
01:03:50 which is a lovely name.
01:03:51 And it’s not obvious that they’re animals at all.
01:03:55 They’re stalked things.
01:03:56 They often have fronds that look a lot like leaves
01:03:59 with kind of fractal branching patterns on them.
01:04:01 And the thing is, they’re found,
01:04:05 sometimes geologists can figure out the environment
01:04:09 that they were in and say,
01:04:10 this is more than 200 meters deep
01:04:12 because there’s no sign of any waves.
01:04:14 There’s no storm damage down here, this kind of thing.
01:04:18 They were more than 200 meters deep,
01:04:19 so they’re definitely not photosynthetic.
01:04:21 These are animals and they’re filter feeders.
01:04:25 And we know sponges and corals and things
01:04:27 are filter feeding animals.
01:04:29 They’re stuck to the spot.
01:04:30 And little bits of carbon that come their way,
01:04:32 they filter it out and that’s what they’re eating.
01:04:36 So no predation involved in this,
01:04:38 beyond stuff just dies anyway.
01:04:40 And it feels like a very gentle, rather beautiful,
01:04:43 rather limited world, you might say.
01:04:45 There’s not a lot going on there.
01:04:48 And something changes.
01:04:51 Oxygen definitely changes during this period.
01:04:53 Other things may have changed as well.
01:04:55 But the next thing you really see in the fossil record
01:04:58 is the Cambrian explosion.
01:05:00 And what do we see there?
01:05:02 We’re now seeing animals that we would recognize.
01:05:04 They’ve got eyes, they’ve got claws, they’ve got shells.
01:05:07 They’re plainly killing things or running away and hiding.
01:05:14 And so we’ve gone from a rather gentle but limited world
01:05:18 to a rather vicious, unpleasant world that we recognize
01:05:23 and which leads to kind of arms races,
01:05:27 evolutionary arms races, which again is something
01:05:31 that when we think about a nuclear arms race,
01:05:32 we think, Jesus, we don’t want to go there.
01:05:34 It’s not done anybody any good.
01:05:37 In some ways, maybe it does do good.
01:05:40 I don’t want to make an argument for nuclear arms.
01:05:42 But predation as a mechanism forces organisms
01:05:48 to adapt to change to be better to escape or to kill.
01:05:52 If you need to eat, then you’ve got to eat.
01:05:55 And a cheetah’s not going to run at that speed
01:05:57 unless it has to because the zebra is capable of escaping.
01:06:03 So it leads to much greater feats of evolution
01:06:07 than would ever have been possible without it.
01:06:09 And in the end, to a much more beautiful world.
01:06:12 And so it’s not all bad by any means.
01:06:17 But the thing is you can’t have this
01:06:19 if you don’t have an oxygenated planet.
01:06:21 Because it’s all in the end, it’s about how much energy
01:06:24 can you extract from the food you eat.
01:06:26 And if you don’t have an oxygenated planet,
01:06:28 you can get about 10% out, not much more than that.
01:06:32 And if you’ve got an oxygenated planet,
01:06:34 you can get about 40% out.
01:06:35 And that means you can have,
01:06:37 instead of having one or two trophic levels,
01:06:40 you can have five or six trophic levels.
01:06:42 And that means things can eat things
01:06:44 that eat other things and so on.
01:06:45 And you’ve gone to a level of ecological complexity,
01:06:48 which is completely impossible in the absence of oxygen.
01:06:51 This reminds me of the Hunter S. Thompson quote,
01:06:54 that for every moment of triumph,
01:06:56 for every instance of beauty, many souls must be trampled.
01:07:02 The history of life on Earth, unfortunately,
01:07:05 is that of violence.
01:07:09 Just the trillions and trillions of multi cell organisms
01:07:13 that were murdered in the struggle for survival.
01:07:17 It’s a sorry statement, but yes, it’s basically true.
01:07:20 And that somehow is a catalyst
01:07:23 from an evolutionary perspective for creativity,
01:07:26 for creating more and more complex organisms
01:07:28 that are better and better at surviving.
01:07:30 I mean, survival of the fittest,
01:07:32 if you just go back to that old phrase,
01:07:33 means death of the weakest.
01:07:36 Now, what’s fit, what’s weak,
01:07:38 these are terms that don’t have much intrinsic meaning.
01:07:41 But the thing is, evolution only happens because of death.
01:07:45 One way to die is the constraints,
01:07:49 the scarcity of the resources in the environment,
01:07:52 but that seems to be not nearly as good of a mechanism
01:07:56 for death than other creatures
01:07:59 roaming about in the environment.
01:08:01 When I say environment, I mean like the static environment,
01:08:04 but then there’s the dynamic environment
01:08:05 of bigger things trying to eat you
01:08:08 and use you for your energy.
01:08:10 It forces you to come up with a solution
01:08:13 to your specific problem that is inventive
01:08:16 and is new and hasn’t been done before.
01:08:18 And so it forces, I mean, literally change,
01:08:22 literally evolution on populations.
01:08:26 They have to become different.
01:08:27 And it’s interesting that humans have channeled that
01:08:30 into more, I mean, I guess what humans are doing
01:08:34 is they’re inventing more productive
01:08:37 and safe ways of doing that.
01:08:39 You know, this whole idea of morality
01:08:41 and all those kinds of things,
01:08:43 I think they ultimately lead to competition
01:08:48 versus violence, because I think violence
01:08:51 can have a cold, brutal, inefficient aspect to it.
01:08:56 But if you channel that into more controlled competition
01:09:01 in the space of ideas, in the space of approaches to life,
01:09:05 maybe you can be even more productive than evolution is.
01:09:10 Because evolution is very wasteful.
01:09:12 Like the amount of murder required
01:09:14 to really test a good idea,
01:09:16 genetically speaking, is just a lot.
01:09:19 Many, many, many generations.
01:09:21 Morally, we cannot base society
01:09:24 on the way that evolution works.
01:09:26 That’s an invention, right?
01:09:27 But actually, in some respects we do,
01:09:29 which is to say, this is how science works.
01:09:31 We have competing hypotheses that have to get better,
01:09:34 otherwise they die.
01:09:35 It’s the way that society works.
01:09:36 You know, in ancient Greece, we had the Athens
01:09:41 and Sparta and city states,
01:09:42 and then we had the Renaissance and nation states,
01:09:45 and universities compete with each other.
01:09:48 Tremendous amount of companies competing
01:09:50 with each other all the time.
01:09:51 It drives innovation.
01:09:55 And if we want to do it without all the death
01:09:57 that we see in nature,
01:09:59 then we have to have some kind of societal level control
01:10:03 that says, well, there’s some limits, guys,
01:10:05 and these are what the limits are gonna be.
01:10:07 And society as a whole has to say,
01:10:08 right, we want to limit the amount of death here,
01:10:10 so you can’t do this and you can’t do that.
01:10:12 And you know, who makes up these rules,
01:10:14 and how do we know?
01:10:15 It’s a tough thing, but it’s basically
01:10:16 trying to find a moral basis
01:10:19 for avoiding the death of evolution and natural selection
01:10:22 and keeping the innovation and the richness of it.
01:10:27 And I forgot who said it, but that murder is illegal.
01:10:31 Probably Kurt Vonnegut.
01:10:33 Murder is illegal except when it’s done
01:10:35 to the sound of trumpets and at a large scale.
01:10:38 So we still have wars.
01:10:41 But we are struggling with this idea
01:10:44 that murder is a bad thing.
01:10:47 It’s so interesting how we’re channeling
01:10:49 the best of the evolutionary imperative
01:10:53 and trying to get rid of the stuff that’s not productive.
01:10:58 Trying to almost accelerate evolution.
01:11:00 The same kind of thing that makes evolution creative.
01:11:05 We’re trying to use that.
01:11:07 I think we naturally do it.
01:11:08 I mean, I don’t think we can help ourselves do it.
01:11:10 And you know, capitalism as a form
01:11:13 is basically about competition and differential rewards.
01:11:17 But we, society, and you know, we have a,
01:11:22 I keep using this word moral obligation,
01:11:25 but you know, we cannot operate as a society
01:11:28 if we go that way.
01:11:29 It’s interesting that we’ve had problems achieving balance.
01:11:35 So for example, in the financial crash in 2009,
01:11:39 do you let banks go to the wall or not?
01:11:41 This kind of question.
01:11:42 In evolution, certainly you let them go to the wall.
01:11:45 And in that sense, you don’t need the regulation
01:11:47 because they just die.
01:11:51 Whereas if we, as a society,
01:11:53 think about what’s required for society as a whole,
01:11:56 then you don’t necessarily let them go to the wall.
01:11:59 In which case you then have to impose
01:12:01 some kind of regulation that the bankers themselves will,
01:12:05 in an evolutionary manner, exploit.
01:12:08 Yeah, we’ve been struggling with this kind of idea
01:12:11 of capitalism, the cold brutality of capitalism
01:12:16 that seems to create so much beautiful things
01:12:18 in this world.
01:12:20 And then the ideals of communism
01:12:23 that seem to create so much brutal destruction in history.
01:12:26 We struggle with ideas of,
01:12:28 well, maybe we didn’t do it right.
01:12:30 How can we do things better?
01:12:31 And then the ideas are the things
01:12:33 where we’re playing with as opposed to people.
01:12:35 If a PhD student has a bad idea,
01:12:37 we don’t shoot the PhD student.
01:12:39 We just criticize their idea and hope they improve.
01:12:42 You have a very humane lab.
01:12:44 Yeah, I don’t know how you guys do it.
01:12:46 The way I run things, it’s always life and death.
01:12:49 Okay, so it is interesting about humans
01:12:52 that there is an inner sense of morality
01:12:54 which begs the question of how did homo sapiens evolve?
01:13:02 If we think about the invention of,
01:13:05 early invention of sex and early invention of predation,
01:13:10 what was the thing invented to make humans?
01:13:15 What would you say?
01:13:17 I mean, I suppose a couple of things I’d say.
01:13:19 Number one is you don’t have to wind the clock back
01:13:21 very far, five, six million years or so,
01:13:24 and let it run forwards again.
01:13:26 And the chances of humans as we know them
01:13:29 is not necessarily that high.
01:13:31 You know, imagine as an alien, you find planet Earth
01:13:34 and it’s got everything apart from humans on it.
01:13:36 It’s an amazing, wonderful, marvelous planet,
01:13:39 but nothing that we would recognize
01:13:41 as extremely intelligent life,
01:13:43 kind of space faring civilization.
01:13:45 So when we think about aliens,
01:13:46 we’re kind of after something like ourselves.
01:13:49 We’re after a space faring civilization.
01:13:51 We’re not after zebras and giraffes and lions and things,
01:13:55 amazing though they are.
01:13:57 But the additional kind of evolutionary steps
01:14:01 to go from large, complex mammals, monkeys, let’s say,
01:14:06 to humans doesn’t strike me as that long a distance.
01:14:12 It’s all about the brain.
01:14:14 And where’s the brain and morality coming from?
01:14:17 It seems to me to be all about groups,
01:14:19 human groups and interactions between groups.
01:14:22 The collective intelligence of it.
01:14:24 Yes, the interactions really.
01:14:26 And there’s a guy at UCL called Mark Thomas,
01:14:30 who’s done a lot of really beautiful work,
01:14:32 I think, on this kind of question.
01:14:33 So I talk to him every now and then,
01:14:34 so my views are influenced by him.
01:14:38 But a lot seems to depend on population density,
01:14:43 that the more interactions you have going on
01:14:45 between different groups, the more transfer of information,
01:14:49 if you like, between groups,
01:14:51 people moving from one group to another group,
01:14:53 almost like lateral gene transfer in bacteria,
01:14:57 the more expertise you’re able to develop and maintain,
01:15:01 the more culturally complex your society can become.
01:15:04 And groups that have become detached,
01:15:07 like on Easter Island, for example,
01:15:09 very often degenerate in terms of the complexity
01:15:12 of their civilization.
01:15:13 Is that true for complex organisms in general?
01:15:16 Population density is often productive.
01:15:19 Really matters, but in human terms,
01:15:23 I don’t know what the actual factors were
01:15:26 that were driving a large brain,
01:15:28 but you can talk about fire, you can talk about tool use,
01:15:32 you can talk about language,
01:15:34 and none of them seem to correlate especially well
01:15:36 with the actual known trajectory of human evolution
01:15:39 in terms of cave art and these kind of things.
01:15:42 That seems to work much better
01:15:45 just with population density
01:15:47 and number of interactions between different groups,
01:15:51 all of which is really about human interactions,
01:15:55 human human interactions and the complexity of those.
01:15:58 But population density is the thing
01:16:02 that increases the number of interactions,
01:16:04 but then there must have been inventions
01:16:09 forced by that number of interactions
01:16:12 that actually led to humans.
01:16:14 So like Richard Wrangham talks about that
01:16:18 it’s basically the beta males had to beat up the alpha male.
01:16:22 So that’s what collaboration looks like,
01:16:23 is they, when you’re living together,
01:16:28 our early ancestors don’t like the dictatorial aspect
01:16:33 of a single individual at the top of a tribe.
01:16:36 So they learned to collaborate
01:16:38 how to basically create a democracy of sorts,
01:16:42 a democracy that prevents, minimizes,
01:16:45 or lessens the amount of violence,
01:16:47 which essentially gives strength to the tribe
01:16:50 and make the war between tribes versus the dictator.
01:16:55 I mean, I think one of the most wonderful things
01:16:57 about humans is we’re all of those things.
01:17:00 I mean, we are deeply social as a species
01:17:03 and we’re also deeply selfish.
01:17:05 And it seems to me the conflict
01:17:06 between capitalism and communism,
01:17:08 it’s really just two aspects of human nature,
01:17:10 both of which are.
01:17:11 We have both and we have a constant kind of vying
01:17:15 between the two sides.
01:17:16 We really do care about other people beyond our families,
01:17:19 beyond our immediate people.
01:17:21 We care about society and the society that we live in.
01:17:24 And you could say that’s a drawing
01:17:27 towards socialism or communism.
01:17:28 On the other side, we really do care about ourselves.
01:17:30 We really do care about our families,
01:17:32 about working for something that we gain from.
01:17:34 And that’s the capitalist side of it.
01:17:35 They’re both really deeply ingrained in human nature.
01:17:38 In terms of violence and interactions between groups,
01:17:43 yes, all this dynamic of,
01:17:45 if you’re interacting between groups,
01:17:47 you can be certain that they’re gonna be burning each other
01:17:50 and all kinds of physical violent interactions as well,
01:17:53 which will drive the kind of cleverness
01:17:56 of how do you resist this?
01:17:57 Let’s build a tower.
01:17:59 What are we gonna do to prevent being overrun
01:18:02 by those marauding gangs from over there?
01:18:06 And you look outside humans
01:18:08 and you look at chimps and bonobos and so on,
01:18:10 and they’re very, very different structures to society.
01:18:13 Chimps tend to have an aggressive alpha male type structure
01:18:16 and bonobos, there’s basically a female society
01:18:21 where the males are predominantly excluded
01:18:22 and only brought in at the behest of the female.
01:18:25 We have a lot in common with both of those groups.
01:18:29 And there’s, again, tension there.
01:18:31 And probably chimps, more violence,
01:18:33 the bonobos, probably more sex.
01:18:35 That’s another tension.
01:18:36 How serious do we wanna be?
01:18:42 How much fun we wanna be?
01:18:44 Asking for a friend again,
01:18:45 what do you think happened to Neanderthals?
01:18:47 What did we cheeky humans do to the Neanderthals,
01:18:52 Homo sapiens?
01:18:53 Do you think we murdered them?
01:18:54 Was it, how do we murder them?
01:18:56 How do we outcompete them?
01:18:59 Or do we mate them?
01:19:01 I don’t know.
01:19:02 I mean, I think there’s unequivocal evidence
01:19:04 that we mated with them.
01:19:05 We always try to mate with everything.
01:19:07 Yes, pretty much.
01:19:09 There’s some interesting,
01:19:10 the first sequences that came along
01:19:12 were in mitochondrial DNA.
01:19:14 And that was back to about 2002 or thereabouts.
01:19:18 What was found was that Neanderthal mitochondrial DNA
01:19:21 was very different to human mitochondria.
01:19:23 Oh, that’s so interesting.
01:19:24 You could do a clock on it
01:19:25 and it said the divergent state
01:19:26 was about 600,000 years ago or something like that.
01:19:29 So not so long ago.
01:19:31 And then the first full genomes were sequenced
01:19:33 maybe 10 years after that.
01:19:36 And they showed plenty of signs of mating between.
01:19:39 So the mitochondrial DNA effectively says no mating.
01:19:43 And the nuclear genes say, yeah, lots of mating.
01:19:47 But we don’t know.
01:19:48 How’s that possible?
01:19:49 So can you explain the difference
01:19:50 between mitochondrial DNA and nucleus?
01:19:53 I’ve talked before about the mitochondria,
01:19:55 which are the power packs in cells.
01:19:57 These are the paired down control units is their DNA.
01:20:01 So it’s passed on by the mother only.
01:20:05 And in the egg cell,
01:20:07 we might have half a million copies of mitochondrial DNA.
01:20:10 There’s only 37 genes left and they do a,
01:20:15 it’s basically the control unit of energy production.
01:20:17 That’s what it’s doing.
01:20:18 It’s a basic old school machine that does.
01:20:21 And it’s got genes that were considered
01:20:23 to be effectively trivial
01:20:24 because they did a very narrowly defined job,
01:20:28 but they’re not trivial in the sense
01:20:30 that that narrowly defined job
01:20:31 is about everything that is being alive.
01:20:35 So they’re much easier to sequence.
01:20:38 You’ve got many more copies of these things
01:20:39 and you can sequence them very quickly.
01:20:42 But the problem is because they go down
01:20:43 only the maternal line from mother to daughter,
01:20:46 your mitochondrial DNA and mine is going nowhere.
01:20:49 It doesn’t matter.
01:20:50 Any kids we have, they get their mother’s mitochondrial DNA
01:20:53 except in very, very rare and strange circumstances.
01:20:59 And so it tells a different story
01:21:02 and it’s not a story which is easy to reconcile always.
01:21:06 And what it seems to suggest to my mind at least
01:21:10 is that there was one way traffic of genes
01:21:13 probably going from humans into Neanderthals
01:21:16 rather than the other way around.
01:21:18 Why did the Neanderthals disappear?
01:21:19 I don’t know.
01:21:20 I mean, I suspect that they were,
01:21:23 I suspect they were probably less violent,
01:21:25 less clever, less populous, less willing to fight.
01:21:31 I don’t know.
01:21:32 I mean, I think it probably drove them to extinction
01:21:34 at the margins of Europe.
01:21:37 And it’s interesting how much,
01:21:39 if we ran Earth over and over again,
01:21:41 how many of these branches of intelligent beings
01:21:45 that have figured out some kind of
01:21:49 how to leverage collective intelligence,
01:21:52 which ones of them emerge?
01:21:53 Which ones of them succeed?
01:21:55 Is it the more violent ones?
01:21:57 Is it the more isolated ones?
01:22:01 Like what dynamics result in more productivity?
01:22:03 And I suppose we’ll never know.
01:22:06 The more complex the organism,
01:22:07 the harder it is to run the experiment in the lab.
01:22:10 Yes.
01:22:12 And in some respects, maybe it’s best if we don’t know.
01:22:15 Yeah.
01:22:16 The truth might be very painful.
01:22:18 What about if we actually step back
01:22:20 a couple of interesting things that we humans do?
01:22:24 One is object manipulation and movement.
01:22:28 And of course, movement was something that was done,
01:22:32 that was another big invention,
01:22:33 being able to move around the environment.
01:22:36 And the other one is this sensory mechanism,
01:22:39 how we sense the environment.
01:22:41 One of the coolest high definition ones is vision.
01:22:45 How big are those inventions
01:22:47 in the history of life on Earth?
01:22:50 Vision, movement, I mean, again, extremely important,
01:22:55 going back to the origin of animals,
01:22:56 the Cambrian explosion where suddenly you’re seeing eyes
01:22:59 in the fossil record.
01:23:01 And you can, it’s not necessarily, again,
01:23:03 lots of people historically have said
01:23:05 what use is half an eye?
01:23:06 And you can go in a series of steps
01:23:10 from a light sensitive spot on a flat piece of tissue
01:23:17 to an eyeball with a lens and so on.
01:23:20 If you assume no more than, I don’t remember,
01:23:23 this was a specific model that I have in mind,
01:23:25 but it was 1% change or half a percent change
01:23:28 for each generation.
01:23:29 How long would it take to evolve an eye as we know it?
01:23:31 And the answer is half a million years.
01:23:34 It doesn’t have to take long.
01:23:35 That’s not how evolution works.
01:23:36 That’s not an answer to the question.
01:23:38 It just shows you can reconstruct the steps
01:23:41 and you can work out roughly how it can work.
01:23:44 So it’s not that big a deal to evolve an eye,
01:23:49 but once you have one, then there’s nowhere to hide.
01:23:51 And again, we’re back to predator prey relationships.
01:23:55 We’re back to all the benefits
01:23:56 that being able to see brings you.
01:23:58 And if you think philosophically what bats are doing
01:24:00 with eco location and so on, I have no idea,
01:24:04 but I suspect that they form an image of the world
01:24:06 in pretty much the same way that we do.
01:24:07 It’s just a matter of mental reconstruction.
01:24:10 So I suppose the other thing about sight,
01:24:11 there are single celled organisms that have got a lens
01:24:17 and a retina and a cornea and so on.
01:24:21 Basically they’ve got a camera type eye in a single cell.
01:24:24 They don’t have a brain.
01:24:27 What they understand about their world
01:24:29 is impossible to say, but they’re capable of coming up
01:24:32 with the same structures to do so.
01:24:34 So I suppose then is that once you’ve got things like eyes,
01:24:39 then you have a big driving pressure
01:24:41 on the central nervous system
01:24:42 to figure out what it all means.
01:24:44 And then we come around to your other point
01:24:45 about manipulation, sensory input, and so on
01:24:48 about now you have a huge requirement
01:24:52 to understand what your environment is and what it means
01:24:55 and how it reacts and how you should run away
01:24:57 and where you should stay put.
01:24:59 Actually on that point, let me,
01:25:00 I don’t know if you know the work of Donald Hoffman,
01:25:03 who uses the argument, the mechanism of evolution
01:25:11 to say that there’s not necessarily
01:25:14 a strong evolutionary value to seeing the world as it is.
01:25:23 So objective reality, that our perception actually
01:25:26 is very different from what’s objectively real.
01:25:29 We’re living inside an illusion
01:25:32 and we’re basically the entire set of species on earth,
01:25:37 I think, I guess, are competing in a space
01:25:40 that’s an illusion that’s distinct from,
01:25:41 that’s far away from physical reality as it is,
01:25:45 as defined by physics.
01:25:46 I’m not sure it’s an illusion so much as a bubble.
01:25:48 I mean, we have a sensory input,
01:25:50 which is a fraction of what we could have
01:25:51 a sensory input on, and we interpret it
01:25:55 in terms of what’s useful for us to know to stay alive.
01:25:58 So yes, it’s an illusion in that sense,
01:26:00 but the tree is physically there.
01:26:03 And if you walk into that tree, you know,
01:26:06 that there is, it’s not purely a delusion,
01:26:08 there’s some physical reality to it.
01:26:10 So it’s a sensory slice into reality as it is,
01:26:15 but because it’s just a slice,
01:26:17 you’re missing a big picture.
01:26:18 But he says that that slice doesn’t necessarily
01:26:21 need to be a slice.
01:26:23 It could be a complete fabrication
01:26:25 that’s just consistent amongst the species,
01:26:28 which is an interesting, or at least it’s a humbling
01:26:32 realization that our perception is limited
01:26:37 and our cognitive abilities are limited.
01:26:40 And at least to me, it’s argument from evolution,
01:26:44 I don’t know how much, how strong that is as an argument,
01:26:49 but I do think that life can exist in the mind.
01:26:54 In the same way that you can do a virtual reality video game
01:26:59 and you can have a vibrant life inside that place
01:27:02 and that place is not real in some sense,
01:27:05 but you could still have a vibrant,
01:27:07 all the same forces of evolution,
01:27:08 all the same competition, the dynamics of between humans
01:27:12 you can have, but I don’t know if,
01:27:19 I don’t know if there’s evidence for that being
01:27:21 the thing that happened on earth.
01:27:23 It seems that earth.
01:27:25 I think in either environment, I wouldn’t deny
01:27:27 that you could have exactly the world that you talk about
01:27:29 and it would be very difficult to,
01:27:33 the idea in matrix movies and so on
01:27:36 that the whole world is completely a construction
01:27:42 and we’re fundamentally deluded.
01:27:43 It’s difficult to say that’s impossible or couldn’t happen
01:27:47 or, and certainly we construct in our minds
01:27:51 what the outside world is, but we do it on input
01:27:53 and that input, I would hesitate to say it’s not real
01:27:57 because it’s precisely how we do understand the world.
01:28:00 We have eyes, but if you keep someone in,
01:28:04 apparently this kind of thing happens,
01:28:06 someone kept in a dark room for five years
01:28:08 or something like that, they never see properly again
01:28:10 because the neural wiring that underpins
01:28:15 how we interpret vision never developed.
01:28:18 You need, when you watch a child develop,
01:28:21 it walks into a table, it bangs his head on the table
01:28:23 and it hurts and now you’ve got two inputs.
01:28:28 You’ve got one pain from this sharp edge
01:28:30 and number two, you probably, you’ve touched it
01:28:32 and realized it’s there, it’s a sharp edge
01:28:33 and you’ve got the visual input
01:28:34 and you put the three things together and think,
01:28:36 I don’t wanna walk into a table again.
01:28:38 So you’re learning and it’s a limited reality,
01:28:42 but it’s a true reality and if you don’t learn
01:28:44 that properly, then you will get eaten,
01:28:45 you will get hit by a bus, you will not survive.
01:28:48 And same, if you’re in some kind of,
01:28:53 let’s say, computer construction of reality,
01:28:55 I’m not in my ground here, but if you construct the laws
01:28:59 that this is what reality is inside this,
01:29:03 then you play by those laws.
01:29:05 Yeah, I mean, as long as the laws are consistent.
01:29:07 So just like you said in the lab,
01:29:09 the interesting thing about the simulation question,
01:29:12 yes, it’s hard to know if we’re living inside a simulation,
01:29:15 but also, yes, it’s possible to do these kinds
01:29:18 of experiments in the lab now more and more.
01:29:21 To me, the interesting question is,
01:29:23 how realistic does a virtual reality game need to be
01:29:28 for us to not be able to tell the difference?
01:29:30 A more interesting question to me is,
01:29:33 how realistic or interesting
01:29:38 does a virtual reality world need to be
01:29:40 in order for us to want to stay there forever
01:29:43 or much longer than physical reality, prefer that place?
01:29:47 And also prefer it not as we prefer hard drugs,
01:29:52 but prefer it in a deep, meaningful way
01:29:55 in the way we enjoy life.
01:29:57 I mean, I suppose the issue with the matrix,
01:30:00 I imagine that it’s possible to dilute the mind sufficiently
01:30:05 that you genuinely, in that way,
01:30:07 do think that you are interacting with the real world
01:30:10 when in fact the whole thing’s a simulation.
01:30:14 How good does a simulation need to be to be able to do that?
01:30:17 Well, it needs to convince you
01:30:21 that all your sensory input is correct and accurate
01:30:24 and joins up and makes sense.
01:30:26 Now, that sensory input is not something
01:30:28 that we’re born with.
01:30:29 We’re born with a sense of touch.
01:30:31 We’re born with eyes and so on,
01:30:33 but we don’t know how to use them.
01:30:34 We don’t know what to make of them.
01:30:35 We go around, we bump into trees.
01:30:37 We cry a lot.
01:30:38 We’re in pain a lot.
01:30:39 We’re basically booting up the system
01:30:43 so that it can make head or tail
01:30:45 of the sensory input that it’s getting.
01:30:47 And that sensory input’s not just a one way flux of things.
01:30:49 It’s also, you have to walk into things.
01:30:51 You have to hear things.
01:30:52 You have to put it together.
01:30:53 Now, if you’ve got just babies in the matrix
01:30:58 who are slotted into this,
01:30:59 I don’t think they have that kind of sensory input.
01:31:02 I don’t think they would have any way
01:31:03 to make sense of New York as a world that they’re part of.
01:31:08 The brain is just not developed in that way.
01:31:10 Well, I can’t make sense of New York
01:31:12 in this physical reality either.
01:31:13 But yeah, I mean, but you said pain
01:31:16 and the walking into things.
01:31:17 Well, you can create a pain signal.
01:31:19 And as long as it’s consistent,
01:31:21 that certain things result in pain,
01:31:23 you can start to construct a reality.
01:31:25 There’s some, maybe you disagree with this,
01:31:28 but I think we are born almost with a desire
01:31:33 to be convinced by our reality,
01:31:35 like a desire to make sense of our reality.
01:31:38 Oh, I’m sure we are, yes.
01:31:40 So there’s an imperative.
01:31:41 So whatever that reality is given to us,
01:31:43 like the table hurts, fire is hot.
01:31:46 I think we wanna be diluted
01:31:49 in the sense that we want to make a simple,
01:31:53 like Einstein’s simple theory of the thing around us.
01:31:56 We want that simplicity.
01:31:58 And so maybe the hunger for the simplicity
01:32:02 is the thing that could be used
01:32:03 to construct a pretty dumb simulation that tricks us.
01:32:07 So maybe tricking humans
01:32:09 doesn’t require building a universe.
01:32:11 No, I don’t.
01:32:12 I mean, this is not what I work on,
01:32:14 so I don’t know how close to it we are.
01:32:15 I don’t think anyone works on it.
01:32:16 But I agree with you that, yeah,
01:32:18 I’m not sure that it’s a morally justifiable thing to do,
01:32:21 but is it possible in principle?
01:32:26 I think it would be very difficult,
01:32:28 but I don’t see why in principle it wouldn’t be possible.
01:32:31 And I agree with you that we try to understand the world.
01:32:35 We try to integrate the sensory inputs that we have,
01:32:38 and we try to come up with a hypothesis
01:32:40 that explains what’s going on.
01:32:41 I think though that we have huge input
01:32:46 from the social context that we’re in.
01:32:49 We don’t do it by ourselves.
01:32:50 We don’t kind of blunder around in a universe by ourself
01:32:53 and understand the whole thing.
01:32:55 We’re told by the people around us
01:32:58 what things are and what they do,
01:32:59 and language is coming in here and so on.
01:33:01 So it would have to be an extremely impressive simulation
01:33:05 to simulate all of that.
01:33:08 Yeah, simulate all of that,
01:33:10 including the social construct,
01:33:12 the spread of ideas and the exchange of ideas.
01:33:15 I don’t know.
01:33:16 But those questions are really important to understand
01:33:18 as we become more and more digital creatures.
01:33:22 It seems like the next step of evolution
01:33:23 is us becoming all the same mechanisms we’ve talked about
01:33:28 are becoming more and more plugged into the machine.
01:33:31 We’re becoming cyborgs.
01:33:34 And there’s an interesting interplay
01:33:36 between wires and biology.
01:33:40 Zeros and ones and the biological systems.
01:33:43 And I don’t think we’ll have the luxury
01:33:48 to see humans as disjoint from the technology
01:33:51 we’ve created for much longer.
01:33:53 We are an organism that’s.
01:33:56 Yeah, I mean, I agree with you.
01:34:00 But we come really with this to consciousness.
01:34:06 Yes.
01:34:06 And is there a distinction there?
01:34:08 Because what you’re saying,
01:34:09 the natural end point says we are indistinguishable,
01:34:12 that if you are capable of building an AI,
01:34:17 which is sufficiently close and similar
01:34:19 that we merge with it,
01:34:20 then to all intents and purposes,
01:34:23 that AI is conscious as we know it.
01:34:26 And I don’t have a strong view, but I have a view.
01:34:35 And I wrote about it in the epilogue to my last book,
01:34:37 because 10 years ago,
01:34:39 I wrote a chapter in a book called Life Ascending
01:34:44 about consciousness.
01:34:45 And the subtitle of Life Ascending
01:34:47 was The 10 Great Inventions of Evolution.
01:34:49 And I couldn’t possibly write a book
01:34:51 with a subtitle like that that did not include consciousness.
01:34:54 And specifically consciousness
01:34:56 as one of the great inventions.
01:34:59 And it was in part because I was just curious to know more
01:35:02 and I read more for that chapter.
01:35:04 I never worked on it, but I’ve always,
01:35:06 how can anyone not be interested in the question?
01:35:09 And I was left with the feeling that A, nobody knows,
01:35:13 and B, there are two main schools of thought out there
01:35:18 with a big kind of skew in distribution.
01:35:21 One of them says, oh, it’s a property of matter.
01:35:23 It’s an unknown law of physics.
01:35:26 Panpsychism, everything is conscious.
01:35:28 The sun is conscious.
01:35:29 It’s just a matter of, or a rock is conscious.
01:35:31 It’s just a matter of how much.
01:35:33 And I find that very unpersuasive.
01:35:36 I can’t say that it’s wrong.
01:35:37 It’s just that I think we somehow can tell the difference
01:35:41 between something that’s living and something that’s not.
01:35:45 And then the other end is it’s an emergent property
01:35:48 of a very complex central nervous system.
01:35:51 And I never quite understand what people mean
01:35:56 by words like emergence.
01:35:57 I mean, there are genuine examples,
01:35:59 but I think we very often tend to use it
01:36:03 to plaster over ignorance.
01:36:08 As a biochemist, the question for me then was,
01:36:10 okay, it’s a concoction of a central nervous system.
01:36:16 A depolarizing neuron gives rise to a feeling,
01:36:20 to a feeling of pain, or to a feeling of love,
01:36:24 or anger, or whatever it may be.
01:36:27 So what is then a feeling in biophysical terms
01:36:30 in the central nervous system?
01:36:31 Which bit of the wiring gives rise to,
01:36:34 and I’ve never seen anyone answer that question
01:36:38 in a way that makes sense to me.
01:36:41 And that’s an important question to answer.
01:36:43 I think if we want to understand consciousness,
01:36:45 that’s the only question to answer.
01:36:47 Because certainly an AI is capable of out thinking,
01:36:51 and it’s only a matter of time.
01:36:53 Maybe it’s already happened.
01:36:54 In terms of just information processing
01:36:58 and computational skill,
01:37:00 I don’t think we have any problem in designing a mind
01:37:04 which is at least the equal of the human mind.
01:37:07 But in terms of what we value the most as humans,
01:37:11 which is to say our feelings, our emotions,
01:37:13 our sense of what the world is in a very personal way,
01:37:20 that I think means as much or more to people
01:37:23 than their information processing.
01:37:24 And that’s where I don’t think that AI necessarily
01:37:28 will become conscious, because I think
01:37:31 it’s the property of life.
01:37:33 Well, let’s talk about it more.
01:37:34 You’re an incredible writer, one of my favorite writers.
01:37:36 So let me read from your latest book, Transformers,
01:37:40 what you write about consciousness.
01:37:42 I think therefore I am, said Descartes,
01:37:46 is one of the most celebrated lines ever written.
01:37:49 But what am I exactly?
01:37:51 An artificial intelligence can think too, by definition,
01:37:54 and therefore is, yet few of us could agree
01:37:58 whether AI is capable in principle
01:38:00 of anything resembling human emotions,
01:38:03 of love or hate, fear and joy, of spiritual yearnings,
01:38:08 for oneness or oblivion,
01:38:10 or corporeal pangs of thirst and hunger.
01:38:14 The problem is we don’t know what emotions are,
01:38:18 as you were saying.
01:38:19 What is the feeling in physical terms?
01:38:21 How does a discharging neuron give rise
01:38:23 to a feeling of anything at all?
01:38:25 This is the hard problem of consciousness,
01:38:28 the seeming duality of mind and matter,
01:38:31 the physical makeup of our innermost self.
01:38:34 We can understand in principle
01:38:35 how an extremely sophisticated parallel processing system
01:38:38 could be capable of wondrous feats of intelligence,
01:38:41 but we can’t answer in principle
01:38:44 whether such a supreme intelligence
01:38:46 would experience joy or melancholy.
01:38:49 What is the quantum of solace?
01:38:52 I, speaking to the question of emergence,
01:38:57 you know, there’s just technical,
01:39:00 there’s an excellent paper on this recently
01:39:03 about this kind of phase transition,
01:39:08 emergence of performance in neural networks
01:39:10 on the problem of NLP, natural language processing.
01:39:14 So language models, there seems to be this question of size.
01:39:19 At some point, there is a phase transition
01:39:23 as you grow the size of the neural network.
01:39:25 So the question is,
01:39:27 that’s sort of somewhat of a technical question
01:39:29 that you can philosophize over.
01:39:32 The technical question is,
01:39:33 is there a size of a neural network
01:39:35 that starts to be able to form the kind of representations
01:39:39 that can capture a language,
01:39:40 and therefore be able to, not just language,
01:39:44 but linguistically capture knowledge
01:39:47 that’s sufficient to solve a lot of problems in language,
01:39:50 like be able to have a conversation.
01:39:52 And there seems to be not a gradual increase,
01:39:55 but a phase transition.
01:39:57 And they’re trying to construct the science of where that is,
01:40:01 like what is a good size of a neural network,
01:40:03 and why does such a phase transition happen?
01:40:05 Anyway, that sort of points to emergence,
01:40:08 that there could be stages where a thing goes
01:40:15 from being, oh, you’re very intelligent toaster,
01:40:20 to a toaster that’s feeling sad today and turns away
01:40:25 and looks out the window, sighing,
01:40:29 having an existential crisis.
01:40:30 Thinking of Marvin, the paranoid android.
01:40:33 Marvin is simplistic because Marvin is just cranky.
01:40:38 Yes.
01:40:40 So easily programmed.
01:40:41 Yeah, easily programmed, nonstop existential crisis.
01:40:45 You’re almost basically, what is it?
01:40:47 Notes from Underground by Dostoevsky,
01:40:48 like just constantly complaining about life.
01:40:53 No, they’re capturing the full rollercoaster
01:40:57 of human emotion, the excitement, the bliss,
01:41:00 the connection, the empathy and all that kind of stuff.
01:41:03 And then the selfishness, the anger, the depression,
01:41:09 all that kind of stuff.
01:41:09 They’re capturing all of that
01:41:11 and be able to experience it deeply.
01:41:14 Like it’s the most important thing
01:41:16 you could possibly experience today.
01:41:18 The highest highs, the lowest lows, this is it.
01:41:21 My life will be over.
01:41:24 I cannot possibly go on that feeling.
01:41:26 And then like after a nap, you’re feeling amazing.
01:41:30 That might be something that emerges.
01:41:33 So why would a nap make an AI being feel better?
01:41:42 First of all, we don’t know that for a human either, right?
01:41:45 But we do know that that’s actually true
01:41:47 for many people much of the time.
01:41:48 You may be utterly depressed and you have a nap
01:41:50 and you do in fact feel better, so.
01:41:53 Oh, you are actually asking the technical question there,
01:41:55 is there, so that’s a very,
01:41:57 there’s a biological answer to that.
01:41:59 And so the question is whether AI needs to have
01:42:01 the same kind of attachments to its body,
01:42:04 bodily function and preservation
01:42:08 of the brain’s successful function,
01:42:13 self preservation essentially in some deep biological sense.
01:42:17 I mean, to my mind, it comes back round
01:42:19 to the problem we were talking about before
01:42:21 about simulations and sensory input
01:42:24 and learning what all of this stuff means
01:42:28 and life and death,
01:42:31 that biology unlike society has a death penalty
01:42:35 over everything and natural selection works
01:42:37 on that death penalty.
01:42:38 That if you make this decision wrongly, you die.
01:42:47 And the next generation is represented by beings
01:42:50 that made a slightly different decision on balance.
01:42:56 And that is something that’s intrinsically
01:43:00 difficult to simulate in all this richness, I would say.
01:43:06 So what is?
01:43:09 Death in all its richness.
01:43:11 Yeah.
01:43:12 Our relationship with death or the whole of it.
01:43:16 So which when you say richness, of course,
01:43:20 there’s a lot in that.
01:43:21 Yeah.
01:43:22 Which is hard to simulate.
01:43:23 What’s part of the richness that’s hard to simulate?
01:43:27 I suppose the complexity of the environment
01:43:31 and your position in that or the position
01:43:33 of an organism in that environment,
01:43:35 in the full richness of that environment
01:43:37 over its entire life, over multiple generations
01:43:40 with changes in gene sequence over those generations.
01:43:44 So slight changes in the makeup of those individuals
01:43:46 over generations.
01:43:48 But if you take it back to the level of single cells,
01:43:52 which I do in the book and ask how does a single cell
01:43:59 in effect know it exists as a unit, as an entity?
01:44:02 I mean, no, in inverted commas,
01:44:03 obviously it doesn’t know anything,
01:44:07 but it acts as a unit and it acts
01:44:09 with astonishing precision as a unit.
01:44:14 And I had suggested that that’s linked
01:44:17 to the electrical fields on the membranes themselves
01:44:19 and that they give some indication
01:44:21 of how am I doing in relation to my environment
01:44:24 as a kind of real time feedback on the world.
01:44:28 And this is something physical,
01:44:32 which can be selected over generations
01:44:34 that if you get this wrong,
01:44:39 it’s linked with this set of circumstances
01:44:42 that I’ve just, as an individual,
01:44:45 I have a moment of blind panic and run
01:44:49 as a bacterium or something.
01:44:50 You have some electrical discharge that says blind panic
01:44:54 and it runs whatever it may be.
01:44:56 And you associate over generations, multiple generations
01:44:59 that this electrical phase that I’m in now
01:45:03 is associated with a response like that.
01:45:07 And it’s easy to see how feelings come in
01:45:09 through the back door almost with that kind of giving real time
01:45:17 feedback on your position in the world
01:45:19 in relation to how am I doing.
01:45:22 And then you complexify the system
01:45:23 and yes, I have no problem with phase transition.
01:45:27 And can all of this be done purely by the language,
01:45:36 by the issues with how the system understands itself?
01:45:42 Maybe it can, I honestly don’t know.
01:45:45 But the philosophers for a long time
01:45:47 have talked about the possibility
01:45:49 that you can have a zombie intelligence
01:45:54 and that there are no feelings there,
01:45:55 but everything else is the same.
01:45:59 I mean, I have to throw this back to you really.
01:46:01 How do you deal with the zombie intelligence?
01:46:03 So first of all, I can see that from a biologist perspective,
01:46:08 you think of all the complexities
01:46:10 that led up to the human being.
01:46:12 The entirety of the history of four billion years
01:46:15 that in some deep sense integrated the human being
01:46:18 into this environment.
01:46:20 And that dance of the organism and the environment,
01:46:25 you could see how emotions arise from that.
01:46:27 And then emotions are deeply connected
01:46:29 and creating a human experience.
01:46:32 And from that, you mix in consciousness
01:46:34 and the full mess of it, yeah.
01:46:37 But from a perspective of an intelligent organism
01:46:40 that’s already here, like a baby that learns,
01:46:45 it doesn’t need to learn how to be a collection of cells
01:46:49 or how to do all the things it needs to do.
01:46:52 The basic function of a baby as it learns
01:46:55 is to interact with its environment,
01:46:57 to learn from its environment,
01:46:58 to learn how to fit in to the social society,
01:47:01 to like…
01:47:03 And the basic response of the baby
01:47:05 is to cry a lot of the time.
01:47:07 To cry, well, to convince the humans to protect it
01:47:12 or to discipline it, to teach it.
01:47:14 I mean, we’ve developed a bunch of different tricks,
01:47:18 how to get our parents to take care of us,
01:47:22 to educate us, to teach us about the world.
01:47:24 Also, we’ve constructed the world in such a way
01:47:27 that it’s safe enough for us to survive in
01:47:30 and yet dangerous enough for learning the valuable lessons.
01:47:32 Like the tables are still hard with corners,
01:47:35 so it can still run into them.
01:47:36 It hurts like how…
01:47:38 So AI needs to solve that problem,
01:47:41 not the problem of constructing
01:47:43 this super complex organism that leads up…
01:47:47 To run the whole…
01:47:51 To make an apple pie, to build the whole universe,
01:47:53 you need to build a whole universe.
01:47:55 I think the zombie question is something
01:48:01 I would leave to the philosophers.
01:48:04 Because…
01:48:08 And I will also leave to them the definition of love
01:48:11 and what happens between two human beings
01:48:14 when there’s a magic that just grabs them.
01:48:18 Like nothing else matters in the world
01:48:20 and somehow you’ve been searching for this feeling,
01:48:22 this moment, this person your whole life.
01:48:25 That feeling, the philosophers can have a lot of fun
01:48:29 with that one and also say that that’s just…
01:48:32 You can have a biological explanation,
01:48:34 you can have all kinds of…
01:48:35 It’s all fake, it’s actually…
01:48:38 Ayn Rand will say it’s all selfish.
01:48:40 There’s a lot of different interpretations.
01:48:42 I’ll leave it to the philosophers.
01:48:43 The point is the feeling sure as hell feels very real.
01:48:48 And if my toaster makes me feel
01:48:51 like it’s the only toaster in the world.
01:48:55 And when I leave and I miss the toaster
01:48:58 and when I come back, I’m excited to see the toaster
01:49:01 and my life is meaningful and joyful
01:49:03 and the friends I have around me get a better version of me
01:49:08 because that toaster exists.
01:49:10 That sure as hell feels like a conscious toaster.
01:49:13 Is that psychologically different to having a dog?
01:49:16 No.
01:49:16 Because I mean most people would dispute
01:49:19 whether we can say a dog…
01:49:20 I would say a dog is undoubtedly conscious,
01:49:22 but some people say it doesn’t.
01:49:24 But there’s degrees of consciousness and so on,
01:49:26 but people are definitely much more uncomfortable
01:49:28 saying a toaster can be conscious than a dog.
01:49:32 And there’s still a deep connection.
01:49:35 You could say our relationship with the dog
01:49:37 has more to do with anthropomorphism.
01:49:40 Like we kind of project the human being onto it.
01:49:42 Maybe.
01:49:43 We can do the same damn thing with a toaster.
01:49:45 Yes, but you can look into the dog’s eyes
01:49:48 and you can see that it’s sad,
01:49:50 that it’s delighted to see you again.
01:49:52 I don’t have a dog, by the way.
01:49:53 It’s not that I’m a dog person or a cat person.
01:49:54 And dogs are actually incredibly good
01:49:56 at using their eyes to do just that.
01:49:59 They are.
01:50:00 Now, I don’t imagine that a dog is remotely
01:50:02 as close to being intelligent as an AI intelligence,
01:50:07 but it’s certainly capable
01:50:09 of communicating emotionally with us.
01:50:11 But here’s what I would venture to say.
01:50:13 We tend to think because AI plays chess well
01:50:17 and is able to fold proteins now well,
01:50:19 that it’s intelligent.
01:50:21 I would argue that in order to communicate with humans,
01:50:23 in order to have emotional intelligence,
01:50:25 it actually requires another order
01:50:27 of magnitude of intelligence.
01:50:28 It’s not easy to be flawed.
01:50:34 Solving a mathematical puzzle is not the same
01:50:38 as the full complexity of human to human interaction.
01:50:42 That’s actually, we humans just take for granted
01:50:46 the things we’re really good at.
01:50:49 Nonstop, people tell me how shitty people are driving.
01:50:52 No, humans are incredible at driving.
01:50:56 Bipedal walking, walking, object manipulation.
01:51:00 We’re incredible at this.
01:51:01 And so people tend to discount the things
01:51:05 we all just take for granted.
01:51:07 And one of those things that they discount
01:51:10 is our ability, the dance of conversation
01:51:13 and interaction with each other.
01:51:15 The ability to morph ideas together.
01:51:18 The ability to get angry at each other
01:51:20 and then to miss each other.
01:51:21 Like to create a tension that makes life fun
01:51:24 and difficult and challenging in a way that’s meaningful.
01:51:28 That is a skill that’s learned
01:51:31 and AI would need to solve that problem.
01:51:33 I mean, in some sense, what you’re saying is
01:51:37 AI cannot become meaningfully emotional, let’s say,
01:51:42 until it experiences some kind of internal conflict
01:51:45 that is unable to reconcile these various aspects
01:51:48 of reality or its reality with a decision to make.
01:51:54 And then it feels sad, necessarily,
01:51:56 because it doesn’t know what to do.
01:51:59 And I certainly can’t dispute that.
01:52:01 That may very well be how it works.
01:52:03 I think the only way to find out is to do it.
01:52:05 And to build it.
01:52:06 Yeah, and leave it to the philosophers
01:52:08 if it actually feels sad or not.
01:52:11 The point is the robot will be sitting there alone
01:52:13 having an internal conflict, an existential crisis,
01:52:16 and that’s required for it to have a deep,
01:52:19 meaningful connection with another human being.
01:52:21 Now, does it actually feel that?
01:52:23 I don’t know.
01:52:24 But I’d like to throw something else at you,
01:52:26 which troubles me on reading it.
01:52:31 Noah Harari’s book, 21 Lessons for the 21st Century.
01:52:35 And he’s written about this kind of thing
01:52:36 on various occasions.
01:52:38 And he sees biochemistry as an algorithm.
01:52:40 And then AI will necessarily be able to hack that algorithm
01:52:45 and do it better than humans.
01:52:46 So there will be AI better at writing music
01:52:48 that we appreciate than Mozart ever could,
01:52:50 or writing better than Shakespeare ever did, and so on.
01:52:53 Because biochemistry is algorithmic,
01:52:55 and all you need to do is figure out
01:52:56 which bits of the algorithm to play
01:52:58 to make us feel good or bad or appreciate things.
01:53:02 And as a biochemist, I find that argument
01:53:05 an argument close to irrefutable and not very enjoyable.
01:53:13 I don’t like the sound of it.
01:53:14 That’s just my reaction as a human being.
01:53:16 You might like the sound of it because that says
01:53:18 that AI is capable of the same kind of emotional feelings
01:53:23 about the world as we are,
01:53:25 because the whole thing is an algorithm
01:53:27 and you can program an algorithm, and there you are.
01:53:31 He then has a peculiar final chapter
01:53:33 where he talks about consciousness
01:53:36 in rather separate terms.
01:53:37 And he’s talking about meditating and so on
01:53:39 and getting in touch with his inner conscious.
01:53:41 I don’t meditate, I don’t know anything about that.
01:53:44 But he wrote in very different terms about it,
01:53:48 as if somehow it’s a way out of the algorithm.
01:53:52 Now, it seems to me that consciousness in that sense
01:53:56 is capable of scuppering the algorithm.
01:53:58 I think in terms of the biochemical feedback loops
01:54:01 and so on, it is undoubtedly algorithmic.
01:54:04 But in terms of what we decide to do,
01:54:07 it can be much more based on an emotion.
01:54:14 We can just think, I don’t care.
01:54:16 I can’t resolve this complex situation.
01:54:20 I’m gonna do that.
01:54:21 And that can be based on, in effect, a different currency,
01:54:24 which is the currency of feelings and something
01:54:27 where we don’t have very much personal control over.
01:54:29 And then it comes back around to you
01:54:32 and what are you trying to get at with AI?
01:54:35 Do we need to have some system
01:54:38 which is capable of overriding a rational decision
01:54:41 which cannot be made
01:54:42 because there’s too much conflicting information
01:54:45 by effectively an emotional judgmental decision
01:54:48 that just says, do this and see what happens.
01:54:50 That’s what consciousness is really doing in my view.
01:54:53 Yeah, and the question is whether it’s a different process
01:54:56 or just a higher level process.
01:54:59 I might, you know, the idea that biochemistry
01:55:02 is an algorithm is, to me, an oversimplistic view.
01:55:07 There’s a lot of things that the moment you say it,
01:55:13 it’s irrefutable, but it simplifies.
01:55:17 Of course.
01:55:17 And in the process loses something fundamental.
01:55:21 So for example, calling a universe
01:55:23 and an information processing system, sure, yes.
01:55:27 You could make that.
01:55:29 It’s a computer that’s performing computations,
01:55:32 but you’re missing the process of the entropy
01:55:40 somehow leading to pockets of complexity
01:55:42 that creates these beautiful artifacts
01:55:45 that are incredibly complex and they’re like machines.
01:55:48 And then those machines are through the process of evolution
01:55:52 are constructing even further complexity.
01:55:54 Like in calling universe information processing machine,
01:55:59 you’re missing those little local pockets
01:56:03 and how difficult it is to create them.
01:56:05 So the question to me is if biochemistry is an algorithm,
01:56:07 how difficult is it to create a software system
01:56:11 that runs the human body, which I think is incorrect.
01:56:16 I think that is going to take so long.
01:56:21 I mean, that’s going to be centuries from now
01:56:23 to be able to reconstruct the human.
01:56:25 Now, what I would venture to say
01:56:27 to get some of the magic of a human being
01:56:30 with what we’re saying with the emotions
01:56:32 and the interactions and like a dog makes a smile
01:56:36 and joyful and all those kinds of things
01:56:38 that will come much sooner,
01:56:39 but that doesn’t require us to reverse engineer
01:56:42 the algorithm of biochemistry.
01:56:44 Yes, but the toaster is making you happy.
01:56:47 Yes.
01:56:48 It’s not about whether you make the toaster happy.
01:56:51 No, it has to be.
01:56:52 It has to be.
01:56:55 It has to be.
01:56:56 The toaster has to be able to leave me happy.
01:56:58 Yeah, but it’s the toaster is the AI in this case
01:57:00 is very intelligent.
01:57:00 Yeah, the toaster has to be able to be unhappy and leave me.
01:57:03 That’s essential.
01:57:06 Yeah.
01:57:07 That’s essential for my being able to miss the toaster.
01:57:09 If the toaster is just my servant,
01:57:12 that’s not, or a provider of like services,
01:57:17 like tells me the weather makes toast,
01:57:20 that’s not going to deep connection.
01:57:22 It has to have internal conflict.
01:57:24 You write about life and death.
01:57:26 It has to be able to be conscious of its mortality
01:57:30 and the finiteness of its existence.
01:57:33 And that life is for temporary
01:57:35 and therefore it needs to be more selective.
01:57:38 One of the most moving moments in the movies
01:57:41 from when I was a boy was the unplugging of Hal in 2001,
01:57:45 where that was the death of a sentient being
01:57:48 and Hal knew it.
01:57:51 So I think we all kind of know
01:57:55 that a sufficiently intelligent being
01:58:00 is going to have some form of consciousness,
01:58:02 but whether it would be like biological consciousness,
01:58:06 I just don’t know.
01:58:07 And if you’re thinking about how do we bring together,
01:58:10 I mean, obviously we’re going to interact
01:58:13 more closely with AI,
01:58:16 but is a dog really like a toaster
01:58:21 or is there really some kind of difference there?
01:58:25 You were talking about biochemistry is algorithmic,
01:58:29 but it’s not single algorithm
01:58:31 and it’s very complex, of course it is.
01:58:33 So it may be that there are again conflicts
01:58:35 in the circuits of biochemistry,
01:58:37 but I have a feeling that the level of complexity
01:58:40 of the total biochemical system
01:58:43 at the level of a single cell is less complex
01:58:45 than the level of neural networking in the human brain
01:58:48 or in an AI.
01:58:52 Well, I guess I assumed that we were including the brain
01:58:55 in the biochemistry algorithm, because you have to…
01:58:59 I would see that as a higher level of organization
01:59:02 of neural networks.
01:59:02 They’re all using the same biochemical wiring
01:59:04 within themselves.
01:59:06 Yeah, but the human brain is not just neurons.
01:59:09 It’s the immune system.
01:59:11 It’s the whole package.
01:59:13 I mean, to have a biochemical algorithm
01:59:16 that runs an intelligent biological system,
01:59:20 you have to include the whole damn thing.
01:59:21 And it’s pretty fascinating that it comes from like,
01:59:24 from an embryo, like the whole, I mean, oh boy.
01:59:29 I mean, if you can, what is a human being?
01:59:33 Because it’s just some code and then you built,
01:59:36 and then that says DNA doesn’t just tell you what to build,
01:59:39 but how to build it.
01:59:40 I mean, the thing is impressive.
01:59:44 And the question is how difficult is it
01:59:49 to reverse engineer the whole shebang?
01:59:52 Very difficult.
01:59:54 I would say it’s,
01:59:59 don’t want to say impossible,
02:00:01 but it’s like, it’s much easier to build a human
02:00:05 than to reverse engineer, to build like a fake human,
02:00:09 human like thing than to reverse engineer
02:00:12 the entirety of the process of the evolution.
02:00:15 I’m not sure if we are capable
02:00:18 of reverse engineering the whole thing.
02:00:21 If the human mind is capable of doing that.
02:00:23 I mean, I wouldn’t be a biologist if I wasn’t trying,
02:00:27 but I know I can’t understand the whole problem.
02:00:31 I’m just trying to understand the rudimentary outlines
02:00:33 of the problem.
02:00:35 There’s another aspect though,
02:00:37 you’re talking about developing from a single cell
02:00:39 to the human mind and all the part system,
02:00:43 subsystems that are part of the immune system and so on.
02:00:48 This is something that you’ll talk about, I imagine,
02:00:53 with Michael Levin, but so little is known about,
02:01:00 you talk about reverse engineering,
02:01:02 so little is known about the developmental pathways
02:01:04 that go from a genome to going to a fully wired organism.
02:01:09 And a lot of it seems to depend on the same
02:01:11 in electrical interactions that I was talking about
02:01:16 happening at the level of single cells
02:01:17 and its interaction with the environment.
02:01:19 There’s a whole electrical field side to biology
02:01:23 that is not yet written into any of the textbooks,
02:01:27 which is about how does an embryo develop into
02:01:29 or a single cell develop into these complex systems?
02:01:32 What defines the head, what defines the immune system,
02:01:35 what defines the brain and so on?
02:01:37 That really is written in a language
02:01:38 that we’re only just beginning to understand
02:01:40 and frankly, biologists, most biologists
02:01:42 are still very reluctant to even get themselves tangled up
02:01:47 in questions like electrical fields influencing development.
02:01:51 It seems like mumbo jumbo to a lot of biologists
02:01:54 and it should not be because this is
02:01:55 the 21st century biology, this is where it’s going.
02:01:59 But we’re not gonna reverse engineer a human being
02:02:02 or the mind or any of these subsystems
02:02:04 until we understand how this developmental process
02:02:06 or how electricity in biology really works.
02:02:10 And if it is linked with feelings
02:02:13 and with consciousness and so on,
02:02:15 that’s the, I mean, in the meantime, we have to try,
02:02:18 but I think that’s where the answer lies.
02:02:22 So you think it’s possible that the key to things
02:02:27 like consciousness are some of the more tricky aspects
02:02:31 of cognition might lie in that early development,
02:02:34 the interaction of electricity and biology.
02:02:39 Electrical fields.
02:02:40 But we already know the EEG and so on
02:02:43 is telling us a lot about brain function,
02:02:44 but we don’t know which cells, which parts
02:02:46 of a neural network is giving rise to the EEG.
02:02:48 We don’t know the basics.
02:02:50 The assumption is, I mean, we know it’s neural networks,
02:02:53 we know it’s multiple cells, hundreds or thousands
02:02:55 of cells involved in it and we assume
02:02:57 that it has to do with depolarization during action
02:03:01 potentials and so on.
02:03:03 But the mitochondria which are in there
02:03:05 have much more membranes than the plasma membrane
02:03:08 of the neuron and there’s a much greater membrane potential
02:03:10 and it’s formed in parallel, very often parallel cristae,
02:03:14 which are capable of reinforcing a field
02:03:17 and generating fields over longer distances.
02:03:21 And nobody knows if that plays a role
02:03:23 in consciousness or not.
02:03:24 There’s reasons to argue that it could,
02:03:26 but frankly we simply do not know
02:03:28 and it’s not taken into consideration.
02:03:31 You look at the structure of the mitochondrial membranes
02:03:35 in the brains of simple things like Drosophila,
02:03:39 the fruit fly, and they have amazing structures.
02:03:42 You can see lots of little rectangular things
02:03:44 all lined up in amazing patterns.
02:03:48 What are they doing?
02:03:49 Why are they like that?
02:03:49 We haven’t the first clue.
02:03:52 What do you think about organoids and brain organoids
02:03:55 and so in a lab trying to study the development
02:03:59 of these in the Petri dish development of organs.
02:04:05 Do you think that’s promising?
02:04:06 Do you have to look at whole systems?
02:04:08 I’ve never done anything like that.
02:04:10 I don’t know much about it.
02:04:11 The people who I’ve talked to who do work on it
02:04:13 say amazing things can happen
02:04:15 and a bit of a brain grown in a dish
02:04:18 is capable of experiencing some kind of feelings
02:04:21 or even memories of its former brain.
02:04:23 Again, I have a feeling that until we understand
02:04:27 how to control the electrical fields
02:04:29 that control development, we’re not going to understand
02:04:32 how to turn an organoid into a real functional system.
02:04:36 But how do we get that understanding?
02:04:38 It’s so incredibly difficult.
02:04:41 I mean, you would have to, I mean, one promising direction,
02:04:44 I’d love to get your opinion on this.
02:04:46 I don’t know if you’re familiar with the work of DeepMind
02:04:49 and AlphaFold with protein folding and so on.
02:04:52 Do you think it’s possible
02:04:54 that that will give us some breakthroughs in biology
02:04:57 trying to basically simulate and model the behavior
02:05:03 of trivial biological systems
02:05:07 as they become complex biological systems?
02:05:11 I’m sure it will.
02:05:12 The interesting thing to me about protein folding
02:05:16 is that for a long time, my understanding,
02:05:19 this is not what I work on, so I may have got this wrong,
02:05:21 but my understanding is that you take the sequence
02:05:24 of a protein and you try to fold it.
02:05:28 And there are multiple ways in which it can fold.
02:05:31 And to come up with the correct conformation
02:05:33 is not a very easy thing because you’re doing it
02:05:35 from first principles from a string of letters,
02:05:37 which specify the string of amino acids.
02:05:39 But what actually happens is when a protein
02:05:43 is coming out of a ribosome,
02:05:45 it’s coming out of a charged tunnel
02:05:47 and it’s in a very specific environment,
02:05:49 which is going to force this to go there now
02:05:51 and then this one to go there and this one to come like that.
02:05:53 And so you’re forcing a specific conformational set
02:05:55 of changes onto it as it comes out of the ribosome.
02:05:58 So by the time it’s fully emerged,
02:06:00 it’s already got its shape.
02:06:01 And that shape depended on the immediate environment
02:06:06 that it was emerging into one letter,
02:06:09 one amino acid at a time.
02:06:11 And I don’t think that the field was looking at it that way.
02:06:16 And if that’s correct,
02:06:18 then that’s very characteristic of science,
02:06:20 which is to say it asks very often the wrong question
02:06:23 and then does really amazingly sophisticated analyses
02:06:25 on something having never thought to actually think,
02:06:27 well, what is biology doing?
02:06:29 And biology is giving you a charged electrical environment
02:06:31 that forces you to be this way.
02:06:33 Now, did DeepMind come up through patterns
02:06:37 with some answer that was like that?
02:06:39 I’ve got absolutely no idea.
02:06:41 It ought to be possible to deduce that
02:06:44 from the shapes of proteins.
02:06:46 It would require a much greater skill
02:06:50 than the human mind has.
02:06:52 But the human mind is capable of saying, well, hang on,
02:06:55 let’s look at this exit tunnel and try and work out
02:06:57 what shape is this protein going to take?
02:06:58 And we can figure that out.
02:07:00 That’s really interesting about the exit tunnel,
02:07:01 but like sometimes we get lucky
02:07:03 and just like in science, the simplified view
02:07:08 or the static view will actually solve the problem for us.
02:07:12 So in this case, it’s very possible
02:07:14 that the sequence of letters has a unique mapping
02:07:17 to our structure without considering how it unraveled.
02:07:21 So without considering the tunnel.
02:07:23 And so that seems to be the case in this situation
02:07:27 where the cool thing about proteins,
02:07:29 all the different shapes they can possibly take,
02:07:31 it actually seems to take very specific unique shapes
02:07:35 given the sequence.
02:07:36 That’s forced on you by an exit tunnel.
02:07:38 So the problem is actually much simpler than you thought.
02:07:40 And then there’s a whole army of proteins
02:07:44 which change the conformational state, chaperone proteins.
02:07:49 And they’re only used when there’s some presumably issue
02:07:54 with how it came out of the exit tunnel
02:07:56 and you wanna do it differently to that.
02:07:58 So very often the chaperone proteins will go there
02:08:00 and will influence the way in which it falls.
02:08:03 So there’s two ways of doing it.
02:08:06 Either you can look at the structures
02:08:09 and the sequences of all the proteins
02:08:11 and you can apply an immense mind to it
02:08:13 and figure out what the patterns are
02:08:14 and figure out what happened.
02:08:15 Or you can look at the actual situation where it is
02:08:17 and say, well, hang on, it was actually quite simple.
02:08:20 It’s got a charged environment
02:08:21 and then it’s forced to come out this way.
02:08:23 And then the question will be,
02:08:24 well, do different ribosomes
02:08:25 have different charged environments?
02:08:27 What happens if a chaperone?
02:08:28 You’re asking a different set of questions
02:08:30 to come to the same answer in a way
02:08:31 which is telling you a much simpler story
02:08:34 and explains why it is rather than saying it could be,
02:08:37 this is one in a billion different possible conformational
02:08:41 states that this protein could have.
02:08:42 You’re saying, well, it has this one
02:08:43 because that was the only one it could take
02:08:46 given its setting.
02:08:48 Well, yeah, I mean, currently humans are very good
02:08:51 at that kind of first principles thinking.
02:08:52 I was stepping back, but I think AI is really good
02:08:56 at collecting a huge amount of data
02:08:58 and a huge amount of data of observation of planets
02:09:01 and figure out that Earth is not at the center
02:09:04 of the universe, that there’s actually a sun,
02:09:06 we’re orbiting the sun.
02:09:08 But then you can, as a human being, ask,
02:09:10 well, how do solar systems come to be?
02:09:15 What are the different forces that are required
02:09:17 to make this kind of pattern emerge?
02:09:19 And then you start to invent things like gravity.
02:09:26 I mixed up the ordering of gravity,
02:09:29 wasn’t considered as a thing that connects planets,
02:09:32 but we are able to think about those big picture things
02:09:36 as human beings.
02:09:38 AI is just very good to infer simple models
02:09:42 from a huge amount of data.
02:09:45 And the question is with biology,
02:09:47 we kind of go back and forth at how we solve biology.
02:09:50 Listen, protein folding was thought to be impossible
02:09:54 to solve, and there’s a lot of brilliant PhD students
02:09:57 that worked one protein at a time
02:09:59 trying to figure out the structure.
02:10:00 And the fact that I was able to do that.
02:10:03 Oh, I’m not knocking it at all,
02:10:06 but I think that people have been asking
02:10:08 the wrong question.
02:10:09 But then, as the people start to ask
02:10:13 better and bigger questions,
02:10:17 the AI kind of enters the chat and says,
02:10:20 I’ll help you out with that.
02:10:22 Can I give you another example for my own work?
02:10:27 The risk of getting a disease as we get older,
02:10:32 there are genetic aspects to it.
02:10:35 If you spend your whole life overeating and smoking
02:10:38 and whatever, that’s a whole separate question.
02:10:41 But there’s a genetic side to the risk.
02:10:43 And we know a few genes that increase your risk
02:10:46 of certain things.
02:10:47 And for probably 20 years now,
02:10:49 people have been doing what’s called GWAS,
02:10:51 which is genome wide association studies.
02:10:55 So you’ve effectively scanned the entire genome
02:10:58 for any single nucleotide polymorphisms,
02:11:02 which is to say a single letter change in one place,
02:11:04 that has a higher association of being linked
02:11:07 with a particular disease or not.
02:11:09 And you can come up with thousands of these things
02:11:10 across the genome.
02:11:13 And if you add them all up and try and say,
02:11:17 well, so do they add up to explain
02:11:20 the known genetic risk of this disease?
02:11:23 And the known genetic risk often comes from twin studies.
02:11:26 And you can say that if this twin gets epilepsy,
02:11:30 there’s a 40 or 50% risk that the other twin,
02:11:33 identical twin will also get epilepsy.
02:11:35 Therefore, the genetic factor is about 50%.
02:11:39 And so the gene similarities that you see
02:11:43 should account for 50% of that known risk.
02:11:46 Very often it accounts for less than a 10th
02:11:49 of the known risk.
02:11:50 And there’s two possible explanations.
02:11:52 And there’s one which people tend to do,
02:11:54 which is to say,
02:11:55 ah, well, we don’t have enough statistical power.
02:11:58 If we, maybe there’s a million,
02:12:00 we’ve only found a thousand of them.
02:12:01 But if we find the other million,
02:12:02 they’re weakly related,
02:12:03 but there’s a huge number of them.
02:12:05 And so we’ll account for that whole risk.
02:12:07 Maybe there’s a billion of them.
02:12:11 So that’s one way.
02:12:12 The other way is to say,
02:12:15 well, hang on a minute, you’re missing a system here.
02:12:17 That system is the mitochondrial DNA,
02:12:19 which people tend to dismiss because it’s small
02:12:21 and it doesn’t change very much.
02:12:27 But a few single letter changes in that mitochondrial DNA,
02:12:30 it controls some really basic processes.
02:12:33 It controls not only all the energy
02:12:36 that we need to live and to move around
02:12:38 and do everything we do,
02:12:39 but also biosynthesis to make the new building blocks
02:12:44 to make new cells.
02:12:47 And cancer cells very often kind of take over
02:12:49 the mitochondria and rewire them
02:12:52 so that instead of using them for making energy,
02:12:54 they’re effectively using them as precursors
02:12:56 for the building blocks for biosynthesis.
02:12:58 You need to make new amino acids,
02:12:59 new nucleotides for DNA.
02:13:01 You wanna make new lipids to make your membranes and so on.
02:13:04 So they kind of rewire metabolism.
02:13:06 Now, the problem is that we’ve got all these interactions
02:13:10 between mitochondrial DNA and the genes in the nucleus
02:13:13 that are overlooked completely
02:13:15 because people throw away,
02:13:16 literally throw away the mitochondrial genes.
02:13:18 And we can see in fruit flies that they interact
02:13:21 and produce big differences in risk.
02:13:24 So you can set AI onto this question
02:13:29 of exactly how many of these base changes there are.
02:13:35 And this is one possible solution
02:13:36 that maybe there are a million of them
02:13:39 and it does account for the greatest part of the risk.
02:13:41 Or the other one is they aren’t, it’s just not there.
02:13:43 That actually the risk lies in something
02:13:45 you weren’t even looking at.
02:13:47 And this is where human intuition is very important.
02:13:50 And just this feeling that, well, I’m working on this
02:13:53 and I think it’s important and I’m bloody minded about it.
02:13:56 And in the end, some people are right.
02:13:57 It turns out that it was important.
02:14:00 Can you get AI to do that, to be bloody minded?
02:14:03 And that, hang on a minute,
02:14:06 you might be missing a whole other system here
02:14:09 that’s much bigger.
02:14:11 That’s the moment of discovery of scientific revolution.
02:14:17 I’m giving up on saying AI can’t do something.
02:14:22 I’ve said it enough times about enough things.
02:14:25 I think there’s been a lot of progress.
02:14:27 And instead I’m excited by the possibility
02:14:30 of AI helping humans.
02:14:31 But at the same time, just like I said,
02:14:34 we seem to dismiss the power of humans.
02:14:37 Yes, yes.
02:14:38 Like we’re so limited in so many ways
02:14:43 that we kind of, in what we feel like dumb ways,
02:14:48 like we’re not strong, we’re kind of our attention,
02:14:53 our attention, our memory is limited.
02:14:57 Our ability to focus on things is limited
02:15:00 in our own perception of what limited is.
02:15:02 But that actually, there’s an incredible computer
02:15:05 behind the whole thing that makes this whole system work.
02:15:08 Our ability to interact with the environment,
02:15:11 to reason about the environment.
02:15:13 There’s magic there.
02:15:14 And I’m hopeful that AI can capture
02:15:17 some of that same magic.
02:15:18 But that magic is not gonna look like
02:15:20 Deep Blue playing chess.
02:15:22 No, it’s going to be more interesting.
02:15:24 But I don’t think it’s gonna look
02:15:25 like pattern finding either.
02:15:27 I mean, that’s essentially what you’re telling me.
02:15:29 It does very well at the moment.
02:15:30 And my point is it works very well
02:15:33 where you’re looking for the right pattern.
02:15:36 But we are storytelling animals
02:15:38 and the hypothesis is a story.
02:15:40 It’s a testable story.
02:15:42 But a new hypothesis is a leap into the unknown
02:15:47 and it’s a new story basically.
02:15:48 And it says this leads to this leads to that.
02:15:51 It’s a causal set of storytelling.
02:15:54 It’s also possible that the leap into the unknown
02:15:57 has a pattern of its own.
02:15:58 Yes, it is.
02:15:59 And it’s possible that it’s learnable.
02:16:02 I’m sure it is.
02:16:04 There’s a nice book by Arthur Kessler
02:16:06 on the nature of creativity.
02:16:11 And he likens it to a joke where the punchline goes off
02:16:13 in a completely unexpected direction
02:16:15 and says that this is the basis of human creativity.
02:16:18 That some creative switch of direction
02:16:21 to an unexpected place is similar to a joke.
02:16:25 I’m not saying that’s how it works,
02:16:26 but it’s a nice idea and there must be some truth in it.
02:16:30 And it’s one of these,
02:16:32 most of the stories we tell are probably the wrong story
02:16:34 and probably going nowhere and probably not helpful.
02:16:37 And we definitely don’t do as well
02:16:39 at seeing patterns in things.
02:16:41 But some of the most enjoyable human aspects
02:16:44 is finding a new story that goes to an unexpected place.
02:16:47 And again, these are all aspects
02:16:48 of what being human means to me.
02:16:52 And maybe these are all things
02:16:53 that AI figures out for itself,
02:16:55 or maybe they’re just aspects.
02:16:58 But I just have the feeling sometimes
02:17:00 that the people who are trying to understand
02:17:04 what we are like,
02:17:08 if we wish to craft an AI system
02:17:10 which is somehow human like,
02:17:12 that we don’t have a firm enough grasp
02:17:16 of what humans really are like in terms of how we are built.
02:17:21 But we get a better, better understanding of that.
02:17:25 I agree with you completely.
02:17:26 We try to build a thing and then we go,
02:17:29 hang on a minute, there’s another system here.
02:17:33 And that’s actually the attempt to build AI
02:17:35 that’s human like,
02:17:36 is getting us to a deeper understanding of human beings.
02:17:39 The funny thing that I recently talked to Magnus Carlsen,
02:17:42 why they consider to be the greatest chess player
02:17:44 of all time.
02:17:46 And he talked about AlphaZero,
02:17:48 which is a system from DeepMind that plays chess.
02:17:51 And he had a funny comment.
02:17:55 He has a kind of dry sense of humor.
02:17:57 But he was extremely impressed
02:17:59 when he first saw AlphaZero play.
02:18:02 And he said that it did a lot of things
02:18:04 that could easily be mistaken for creativity.
02:18:07 So he like, as a typical human,
02:18:12 refused to give the system sort of its due.
02:18:16 Because he came up with a lot of things
02:18:18 that a lot of people are extremely impressed by.
02:18:22 Not just the sheer calculation,
02:18:24 but the brilliance of play.
02:18:26 So one of the things that it does
02:18:31 in really interesting ways is it sacrifices pieces.
02:18:35 So in chess, that means you basically take a few steps back
02:18:39 and then take a step forward.
02:18:41 You give away pieces for some future reward.
02:18:46 And that, for us humans, is where art is in chess.
02:18:50 You take big risks.
02:18:52 That for us humans, those risks are especially painful
02:18:58 because you have a fog of uncertainty before you.
02:19:02 So to take a risk now based on intuition
02:19:05 of I think this is the right risk to take,
02:19:07 but there’s so many possibilities,
02:19:09 that that’s where it takes guts.
02:19:11 That’s where art is, that’s that danger.
02:19:14 And then the alpha,
02:19:17 alpha zero takes those same kind of risks
02:19:20 and does them even greater degree.
02:19:22 But of course, it does it from a,
02:19:26 well, you could easily reduce down
02:19:30 to a cold calculation over patterns.
02:19:34 But boy, when you see the final result,
02:19:37 it sure looks like the same kind of magic
02:19:39 that we see in creativity.
02:19:41 When we see creative play on the chessboard,
02:19:45 but the chessboard is very limited.
02:19:46 And the question is, as we get better and better,
02:19:49 can we do that same kind of creativity in mathematics,
02:19:54 in programming, and then eventually in biology, psychology,
02:19:59 and expand into more and more complex systems?
02:20:04 I was, I used to go running when I was a boy,
02:20:07 and fell running, which is to say, running up and down mountains.
02:20:10 And I was never particularly great at it,
02:20:12 but there were some people who were amazingly fast,
02:20:16 especially at running down.
02:20:18 And I realized in trying to do this,
02:20:21 that there’s only really two ways,
02:20:25 there’s three possible ways of doing it,
02:20:26 and there’s only two that work.
02:20:27 Either you go extremely slowly and carefully,
02:20:30 and you figure out, okay, there’s a stone,
02:20:32 I’ll put my foot on this stone,
02:20:33 and then there’s another,
02:20:35 there’s a muddy puddle I’m going to avoid.
02:20:37 And you know, it’s slow, it’s laborious.
02:20:39 You figure it out step by step.
02:20:42 Or you can just go incredibly fast,
02:20:44 and you don’t think about it at all.
02:20:45 The entire conscious mind is shut out of it,
02:20:47 and it’s probably the same playing table tennis
02:20:49 or something, there’s something in the mind,
02:20:51 which is doing a whole lot of subconscious calculations
02:20:54 about exact, and it’s amazing.
02:20:55 You can run at astonishing speed down a hillside
02:20:58 with no idea how you did it at all.
02:21:00 And then you panic, and you think,
02:21:01 I’m going to break my leg if I keep doing this,
02:21:03 I’ve got to think about where I’m going to put my foot.
02:21:05 So you slow down a bit and try to bring
02:21:07 those conscious mind in, and then you do, you crash.
02:21:09 You cannot think consciously while running downhill.
02:21:14 So it’s amazing how many calculations
02:21:18 the mind is able to make.
02:21:21 And now the problem with playing chess or something,
02:21:23 if you’re able to make all of those subconscious
02:21:25 kind of forward calculations about
02:21:28 what is the likely outcome of this move now
02:21:32 in the way that we can by running down a hillside
02:21:34 or something, it’s partly about what we have adapted to do.
02:21:38 It’s partly about the reality of the world that we’re in.
02:21:40 Running fast downhill is something
02:21:42 that we better be bloody good at,
02:21:43 otherwise we’re going to be eaten.
02:21:46 Whereas trying to calculate multiple, multiple moves
02:21:51 into the future is not something
02:21:52 we’ve ever been called on to do.
02:21:54 Two or three, four moves into the future
02:21:55 is quite enough for most of us most of the time.
02:21:58 Yeah, yeah, so yeah, just solving chess may not,
02:22:05 we may not be as far towards solving the problem
02:22:10 of downhill running as we might think
02:22:14 just because we solve chess.
02:22:17 Still, it’s beautiful to see creativity.
02:22:20 Humans create machines.
02:22:23 They’re able to create art and art on a chessboard
02:22:27 and art otherwise.
02:22:29 Who knows how far that takes us.
02:22:31 So I mentioned Andrej Karpathy earlier.
02:22:35 Him and I are big fans of yours.
02:22:37 If you’re taking votes, his suggestion was
02:22:39 you should write your next book on the Fermi Paradox.
02:22:43 So let me ask you on the topic of alien life.
02:22:49 Since we’ve been talking about life
02:22:50 and we’re a kind of aliens,
02:22:51 how many alien civilizations are out there, do you think?
02:22:58 Well, the universe is very big, so some,
02:23:01 but not as many as most people would like to think
02:23:04 is my view because the idea that there is a trajectory
02:23:09 going from simple, simple cellular life like bacteria
02:23:14 all the way through to humans.
02:23:17 It seems to me there’s some big gaps along that way
02:23:19 that the eukaryotic cell, the complex cell that we have
02:23:23 is the biggest of them, but also photosynthesis is another.
02:23:27 The other, another interesting gap is a long gap
02:23:30 from the origin of the eukaryotic cell
02:23:33 to the first animals.
02:23:34 That was about a billion years, maybe more than that.
02:23:38 A long delay in when oxygen began
02:23:41 to accumulate in the atmosphere.
02:23:42 So from the first appearance of oxygen
02:23:44 in the Great Oxidation Event to enough for animals
02:23:47 to respire, it was close to two billion years.
02:23:52 Why so long?
02:23:53 It seems to be planetary factors.
02:23:54 It seems to be geology as much as in anything else.
02:23:57 And we don’t really know what was going on.
02:24:00 So the idea that there’s a kind of an inevitable march
02:24:04 towards complexity and sentient life,
02:24:10 I don’t think is right.
02:24:12 Doesn’t, not to say it’s not gonna happen,
02:24:14 but I think it’s not gonna happen often.
02:24:17 So if you think of Earth,
02:24:19 given the geological constraints and all that kind of stuff,
02:24:25 do you have a sense that life, complex life,
02:24:28 intelligent life happened really quickly on Earth
02:24:30 or really long?
02:24:31 So just to get a sense of,
02:24:35 are you more sort of saying that it’s very unlikely
02:24:38 to get the kind of conditions required to create humans?
02:24:42 Or is it, even if you have the condition,
02:24:44 it’s just statistically difficult?
02:24:46 I think the, I mean, the problem,
02:24:48 the single great problem at the center of all of that,
02:24:51 to my mind, is the origin of the eukaryotic cell,
02:24:53 which happened once and without eukaryotes,
02:24:55 nothing else would have happened.
02:24:56 And that is something that.
02:24:58 That’s because you’re saying it’s super important,
02:25:01 the eukaryotes, but.
02:25:02 I’m saying a tantamount to saying that it is impossible
02:25:05 to build something as complex as a human being
02:25:07 from bacterial cells.
02:25:09 Totally agree in some deep fundamental way.
02:25:11 But it’s just like a one cell going inside another.
02:25:14 Is that so difficult to get to work right?
02:25:17 That like.
02:25:18 Well, again, it happened once.
02:25:21 And if you think about, if you think,
02:25:25 I mean, I’m in a minority view in this position.
02:25:27 Most biologists probably wouldn’t agree with me anyway.
02:25:30 But if you think about the starting point,
02:25:32 we’ve got a simple cell, it’s an alkyl cell,
02:25:35 we can be fairly sure about that.
02:25:36 So it looks a lot like a bacterium,
02:25:39 but is in fact from this other domain of life.
02:25:42 So it looks a lot like a bacterial cell.
02:25:44 That means it doesn’t have anything.
02:25:46 It doesn’t have a nucleus.
02:25:47 It doesn’t really have complex endomembrane.
02:25:50 It has a little bit of stuff, but not that much.
02:25:53 And it takes up an endosymbiont.
02:25:56 So what happens next?
02:25:58 And the answer is basically everything
02:26:00 to do with complexity.
02:26:02 To me, there’s a beautiful paradox here.
02:26:04 Plants and animals and fungi
02:26:08 all have exactly the same type of cell.
02:26:11 But they all have really different ways of living.
02:26:14 So a plant cell, it’s photosynthetic.
02:26:19 They started out as algae in the oceans and so on.
02:26:22 So think of algal blooms, single cell things.
02:26:24 The basic cell structure that it’s built from
02:26:30 is exactly the same with a couple of small differences.
02:26:33 It’s got chloroplasts as well.
02:26:35 It’s got a vacuole.
02:26:35 It’s got a cell wall.
02:26:36 But that’s about it.
02:26:37 Pretty much everything else is exactly the same
02:26:39 in a plant cell and an animal cell.
02:26:42 And yet the ways of life are completely different.
02:26:44 So this cell structure did not evolve
02:26:47 in response to different ways of life,
02:26:49 different environments.
02:26:50 I’m in the ocean doing photosynthesis.
02:26:51 I’m on land running around as part of an animal.
02:26:54 I’m a fungus in a soil,
02:26:57 spreading out long shoots into whatever it may be, mycelium.
02:27:02 So they all have the same underlying cell structure.
02:27:05 Why?
02:27:06 Almost certainly it was driven by adaptation
02:27:10 to the internal environment,
02:27:11 to having these pesky endosymbionts
02:27:13 that forced all kinds of change on the host cell.
02:27:16 Now, in one way you could see that as a really good thing
02:27:18 because it may be that there’s some inevitability
02:27:21 to this process that as soon as you got endosymbionts,
02:27:23 you’re more or less bound to go in that direction.
02:27:25 Or it could be that there’s a huge fluke about it
02:27:27 and it’s almost certain to go wrong
02:27:29 in just about every case possible.
02:27:31 That the conflict will lead to effectively war
02:27:34 leading to death and extinction.
02:27:36 And it simply doesn’t work out.
02:27:37 So maybe it happened millions of times
02:27:39 and it went wrong every time.
02:27:40 Or maybe it only happened once and it worked out
02:27:43 because it was inevitable.
02:27:44 And actually we simply do not know enough now
02:27:47 to say which of those two possibilities is true.
02:27:49 But both of them are a bit grim.
02:27:50 But you’re leaning towards,
02:27:54 we just got really lucky in that one leap.
02:27:56 Like we got, so do you have a sense
02:27:59 that our galaxy, for example, has just maybe millions
02:28:04 of planets with bacteria living on it?
02:28:06 I would expect billions, tens of billions of planets
02:28:09 with bacteria living on it practically.
02:28:11 I mean, there’s probably what, five to 10 planets per star
02:28:16 of which I would hope that at least one
02:28:18 would have bacteria on.
02:28:20 So I expect bacteria to be very common.
02:28:23 I simply can’t put a number otherwise.
02:28:25 I mean, I expect it will happen elsewhere.
02:28:27 It’s not that I think we’re living
02:28:29 in a completely empty universe.
02:28:31 But I think that it’s not gonna happen inevitably.
02:28:35 And there’s something, it wasn’t,
02:28:37 that’s not the only problem with complex life on earth.
02:28:41 I mentioned oxygen and animals and so on as well.
02:28:44 And even humans, we came along very late.
02:28:46 You go back 5 million years and would we be that impressed
02:28:49 if we came across a planet full of giraffes?
02:28:52 I mean, you’d think, hey, there’s life here
02:28:53 and it’s a nice planet to colonize or something.
02:28:56 We wouldn’t think, oh, let’s try and have a conversation
02:28:58 with this giraffe.
02:29:00 Yeah, I’m not sure what exactly we would think.
02:29:04 I’m not exactly sure what makes humans so interesting
02:29:07 from an alien perspective or how they would notice.
02:29:11 I’ll talk to you about cities too
02:29:12 because that’s an interesting perspective
02:29:14 of how to look at human civilization.
02:29:18 But your sense, I mean, of course you don’t know,
02:29:20 but it’s an interesting world, it’s an interesting galaxy,
02:29:25 it’s an interesting universe to live in
02:29:27 that’s just like every sun,
02:29:31 like 90% of solar systems have bacteria in it.
02:29:39 Imagine that world and the galaxy maybe has
02:29:46 just a handful if not one intelligent civilization.
02:29:51 That’s a wild world.
02:29:53 I didn’t even think about that world.
02:29:55 There’s a kind of thought that,
02:29:58 like one of the reasons it would be so exciting
02:30:00 to find life on Mars or Titan or whatever
02:30:04 is like if its life is elsewhere,
02:30:05 then surely, statistically, that life,
02:30:10 no matter how unlikely you query as multicellular organisms,
02:30:14 sex, violence, what else is extremely difficult?
02:30:19 I mean, photosynthesis, figuring out some machinery
02:30:25 that involves the chemistry and the environment
02:30:27 to allow the building up of complex organisms,
02:30:30 surely that would arise.
02:30:32 But man, I don’t know how I would feel
02:30:35 about just bacteria everywhere.
02:30:38 Well, it would be depressing if it was true.
02:30:40 I suppose depressing, I don’t think, I don’t.
02:30:42 I don’t know what’s more depressing,
02:30:43 bacteria everywhere or nothing everywhere.
02:30:46 Yes, either of them are chilling.
02:30:48 Yeah.
02:30:49 But whether it’s chilling or not,
02:30:51 I don’t think should force us to change our view
02:30:55 about whether it’s real or not.
02:30:57 Yes.
02:30:58 And what I’m saying may or may not be true.
02:31:00 So how would you feel if we discovered life on Mars?
02:31:03 Absolutely.
02:31:04 It sounds like you would be less excited than some others
02:31:07 because you’re like, well.
02:31:08 What I would be most interested in
02:31:10 is how similar to life on Earth it would be.
02:31:12 It would actually turn into quite a subtle problem
02:31:13 because the likelihood of life having gone to and fro
02:31:20 between Mars and the Earth is quite,
02:31:23 I wouldn’t say high, but it’s not low, it’s quite feasible.
02:31:27 And so if we found life on Mars
02:31:29 and it had very similar genetic code,
02:31:32 but it was slightly different,
02:31:34 most people would interpret that immediately
02:31:36 as evidence that they’ve been transit one way or the other
02:31:38 and that it was a common origin of life on Mars
02:31:41 or on the Earth and it went one way or the other way.
02:31:43 The other way to see that question though would be to say,
02:31:45 well, actually the beginnings of life
02:31:47 lie in deterministic chemistry and thermodynamics,
02:31:50 starting with the most likely abundant materials,
02:31:53 CO2 and water and a wet rocky planet.
02:31:57 And Mars was wet and rocky at the beginning.
02:31:59 And will, I won’t say inevitably,
02:32:02 but potentially almost inevitably come up
02:32:04 with a genetic code which is not very far away
02:32:06 from the genetic code that we already have.
02:32:09 So we see subtle differences in the genetic code.
02:32:11 What does it mean?
02:32:12 Could be very difficult to interpret.
02:32:14 Is it possible, do you think, to tell the difference
02:32:17 of something that truly originated?
02:32:19 I think if the stereochemistry was different,
02:32:23 we have sugars, for example, that are the L form
02:32:25 or the D form and we have D sugars and L amino acids
02:32:31 right across all of life.
02:32:32 But lipids, the bacteria have one stereoisomer
02:32:38 and the bacteria have the other, the opposite stereoisomer.
02:32:42 So it’s perfectly possible to use one or the other one.
02:32:46 And the same would almost certainly go for,
02:32:48 and I think George Church has been trying to make life
02:32:53 based on the opposite stereoisomer.
02:32:56 So it’s perfectly possible to do and it will work.
02:33:00 And if we were to find life on Mars
02:33:02 that was using the opposite stereoisomer,
02:33:03 that would be unequivocal evidence
02:33:06 that life had started independently there.
02:33:08 So hopefully the life we find will be on Titan and Europa
02:33:13 or something like that where it’s less likely
02:33:15 that we shared and it’s harsher conditions
02:33:18 so there’s gonna be weirder kind of life.
02:33:20 I wouldn’t count on that because if life started
02:33:23 in deep sea hydrothermal vents here, that’s pretty harsh.
02:33:28 So Titan is different.
02:33:29 Europa is probably quite similar to Earth
02:33:32 in the sense that we’re dealing with an ocean,
02:33:34 some acidic ocean there, as the early Earth would have been.
02:33:38 And it almost certainly has hydrothermal systems.
02:33:41 Same with Enceladus.
02:33:43 We can tell that from these plumes
02:33:44 coming from the surface through the ice.
02:33:46 We know there’s a liquid ocean
02:33:48 and we can tell roughly what the chemistry is.
02:33:51 For Titan, we’re dealing with liquid methane
02:33:53 and things like that.
02:33:54 So that would really, if there really is life there,
02:33:56 it would really have to be very, very different
02:33:58 to anything that we know on Earth.
02:34:00 So the hard leap, the hardest leap,
02:34:02 the most important leap is from prokaryotes to eukaryotes.
02:34:07 It’s eukaryotic.
02:34:09 What’s the second, if we’re ranking?
02:34:12 What’s the, you gave a lot of emphasis on photosynthesis.
02:34:17 Yeah, and that would be my second one, I think.
02:34:20 But it’s not so much, I mean,
02:34:22 photosynthesis is part of the problem.
02:34:25 It’s a difficult thing to do.
02:34:26 Again, we know it happened once.
02:34:29 We don’t know why it happened once.
02:34:31 But the fact that it was kind of taken on board completely
02:34:39 by plants and algae and so on as chloroplasts
02:34:44 and did very well in completely different environments
02:34:47 and then on land and whatever else seems to suggest
02:34:50 that there’s no problem with exploring,
02:34:53 whether you could have a separate origin
02:34:55 that explored this whole domain over there
02:34:56 that the bacteria had never gone into.
02:34:58 So that kind of says that the reason
02:35:00 that it only happened once is probably
02:35:02 because it’s difficult, because the wiring is difficult.
02:35:05 But then it happened at least 2.2 billion years ago,
02:35:10 right before the GOE, maybe as long as 3 billion years ago,
02:35:14 when there are, some people say there are whiffs of oxygen,
02:35:16 there’s just kind of traces in the fossil
02:35:18 in the geochemical record that say,
02:35:20 maybe there was a bit of oxygen then.
02:35:22 That’s really disputed.
02:35:23 Some people say it goes all the way back
02:35:25 four billion years ago and then it’s gone.
02:35:28 And the common ancestor of life on Earth was photosynthetic.
02:35:32 So immediately you’ve got groups of people
02:35:34 who disagree over a two billion year period of time
02:35:37 about when it started.
02:35:41 But let’s take the latest date when it’s unequivocal,
02:35:45 that’s 2.2 billion years ago,
02:35:47 through to around about the time of the Cambrian explosion
02:35:49 when oxygen levels definitely got close to modern levels,
02:35:54 which was around about 550 million years ago.
02:35:56 So we’ve gone more than one and a half billion years
02:36:00 where the Earth was in stasis.
02:36:03 Nothing much changed.
02:36:04 It’s known as the boring billion, in fact.
02:36:08 Probably stuff was, that was when eukaryotes arose
02:36:10 somewhere in there, but it’s…
02:36:15 So this idea that the world is constantly changing,
02:36:17 that we’re constantly evolving,
02:36:19 that we’re moving up some ramp is a very human idea.
02:36:22 But in reality, there are kind of tipping points
02:36:30 to a new stable equilibrium where the cells
02:36:35 that are producing oxygen are precisely counterbalanced
02:36:37 by the cells that are consuming that oxygen,
02:36:39 which is why it’s 21% now and has been that way
02:36:42 for hundreds of millions of years.
02:36:44 We have a very precise balance.
02:36:46 You go through a tipping point and you don’t know
02:36:48 where the next stable state’s gonna be,
02:36:51 but it can be a long way from here.
02:36:54 And so if we change the world with global warming,
02:36:57 there will be a tipping point.
02:36:58 The question is where and when,
02:37:00 and what’s the next stable state?
02:37:01 It may be uninhabitable to us.
02:37:03 It’ll be habitable to life, for sure.
02:37:07 But there may be something like the Permian extinction
02:37:08 where 95% of species go extinct
02:37:11 and there’s a five to 10 million year gap
02:37:13 and then life recovers, but without humans.
02:37:16 And the question statistically, well, without humans,
02:37:18 but statistically does that ultimately lead
02:37:21 to greater complexity, more interesting life,
02:37:24 more intelligent life?
02:37:25 Well, after the first appearance of oxygen with the GOE,
02:37:29 there was a tipping point which led
02:37:31 to a longterm stable state that was equivalent
02:37:33 to the Black Sea today, which is to say oxygenated
02:37:36 at the very surface and stagnant, sterile,
02:37:38 not sterile, but sulfurous, lower down.
02:37:43 And that was stable certainly around the continental margins
02:37:47 for more than a billion years.
02:37:50 It was not a state that led to progression
02:37:52 in an obvious way.
02:37:55 Yeah, I mean, it’s interesting to think about evolution,
02:37:58 like what leads to stable states
02:38:01 and how often are
02:38:05 evolutionary pressures emerging from the environment.
02:38:11 So maybe other planets are able
02:38:13 to create evolutionary pressures, chemical pressures,
02:38:16 whatever, some kind of pressure that say,
02:38:18 you’re screwed unless you get your shit together
02:38:20 in the next like 10,000 years, like a lot of pressure.
02:38:26 It seems like Earth, like the boring building
02:38:29 might be explained in two ways.
02:38:31 One is super difficult to take any kind of next step.
02:38:34 And the second way it could be explained
02:38:37 is there’s no reason to take the next step.
02:38:39 No, I think there is no reason, but at the end of it,
02:38:41 there was a snowball Earth.
02:38:44 So there was a planetary catastrophe on a huge scale
02:38:46 where the ice was, the sea was frozen at the equator.
02:38:54 And that forced change in one way or another.
02:38:58 It’s not long after that, 100 million years,
02:39:00 perhaps after that, so not a short time,
02:39:02 but this is when we begin to see animals.
02:39:03 There was a shift again, another tipping point
02:39:06 that led to catastrophic change
02:39:08 that led to a takeoff then.
02:39:10 We don’t really know why, but one of the reasons
02:39:13 why that I discuss in the book is about sulfate
02:39:19 being washed into the oceans,
02:39:20 which sounds incredibly parochial.
02:39:22 But the issue is, I mean, what the data is showing,
02:39:27 we can track roughly how oxygen was going
02:39:30 into the atmosphere from carbon isotopes.
02:39:35 So there’s two main isotopes of carbon
02:39:37 that we need to think about here.
02:39:38 One is carbon 12, 99% of carbon is carbon 12.
02:39:41 And then 1% of carbon is carbon 13,
02:39:44 which is a stable isotope.
02:39:46 And then there’s carbon 14, which is a trivial radioactive,
02:39:48 it’s trivial in amount.
02:39:50 So carbon 13 is 1%.
02:39:53 And life and enzymes generally,
02:39:56 you can think of carbon atoms as little balls
02:40:00 bouncing around, ping pong balls bouncing around.
02:40:01 Carbon 12 moves a little bit faster than carbon 13
02:40:04 because it’s lighter and it’s more likely
02:40:06 to encounter an enzyme.
02:40:08 And so it’s more likely to be fixed into organic matter.
02:40:11 And so organic matter is enriched.
02:40:13 And this is just an observation.
02:40:14 It’s enriched in carbon 12 by a few percent
02:40:17 compared to carbon 13,
02:40:19 relative to what you would expect if it was just equal.
02:40:21 And if you then bury organic matter as coal
02:40:26 or oil or whatever it may be,
02:40:30 then it’s no longer oxidized.
02:40:31 So some oxygen remains leftover in the atmosphere.
02:40:35 And that’s how oxygen accumulates in the atmosphere.
02:40:37 And you can work out historically
02:40:39 how much oxygen there must’ve been in the atmosphere
02:40:40 by how much carbon was being buried.
02:40:43 And you think, well, how can we possibly know
02:40:45 how much carbon was being buried?
02:40:46 And the answer is, well, if you’re burying carbon 12,
02:40:49 what you’re leaving behind is more carbon 13 in the oceans
02:40:52 and that precipitates out into limestone.
02:40:54 So you can look at limestones over these ages
02:40:56 and work out what’s the carbon 13 signal.
02:40:59 And that gives you a kind of a feedback
02:41:00 on what the oxygen content.
02:41:03 Right before the Cambrian explosion,
02:41:05 there was what’s called a negative isotope anomaly excursion,
02:41:08 which is basically the carbon 13 goes down
02:41:10 by a massive amount and then back up again
02:41:12 10 million years later.
02:41:15 And what that seems to be saying is the amount
02:41:18 of carbon 12 in the oceans was disappearing,
02:41:26 which is to say it was being oxidized.
02:41:30 And if it’s being oxidized, it’s consuming oxygen.
02:41:33 And that should, so a big carbon 13 signal says
02:41:36 the ratio of carbon 12 to carbon 13 is really going down,
02:41:39 which means there’s much more carbon 12
02:41:42 being taken out and being oxidized.
02:41:44 Sorry, this is getting too complex, but.
02:41:46 Well, it’s a good way to estimate the amount of oxygen.
02:41:49 If you calculate the amount of oxygen
02:41:51 based on the assumption that all this carbon 12
02:41:53 that’s being taken out is being oxidized by oxygen,
02:41:56 the answer is all the oxygen in the atmosphere
02:41:58 gets stripped out, there is none left.
02:42:01 And yet the rest of the geological indicators say,
02:42:03 no, there’s oxygen in the atmosphere.
02:42:06 So it’s a kind of a paradox.
02:42:07 And the only way to explain this paradox
02:42:09 just on mass balance of how much stuff is in the air,
02:42:12 how much stuff is in the oceans and so on,
02:42:15 is to assume that oxygen was not the oxygen,
02:42:18 it was sulfate.
02:42:19 Sulfate was being washed into the oceans.
02:42:22 It’s used as an electron acceptor
02:42:24 by sulfate reducing bacteria,
02:42:26 just as we use oxygen as an electron acceptor.
02:42:28 So they pass their electrons to sulfate instead of oxygen.
02:42:31 And. Bacteria did.
02:42:32 Yeah, yeah.
02:42:34 So these are bacteria.
02:42:36 So they’re oxidizing carbon, organic carbon with sulfate,
02:42:41 passing the electrons onto sulfate,
02:42:43 that reacts with iron to form iron pyrite or fool’s gold,
02:42:47 sinks down to the bottom, gets buried out of the system.
02:42:51 And this can account for the mass balance.
02:42:53 So why does it matter?
02:42:55 It matters because what it says is
02:42:58 there was a chance event,
02:43:00 tectonically there was a lot of sulfate sitting on land
02:43:03 as some kind of mineral.
02:43:06 So calcium sulfate minerals, for example, are evaporitic.
02:43:11 And because there happened to be
02:43:13 some continental collisions, mountain building,
02:43:18 the sulfate was pushed up the side of a mountain
02:43:20 and happened to get washed into the ocean.
02:43:24 Yeah, so I wonder how many happy accidents
02:43:26 like that are possible.
02:43:27 Statistically, it’s really hard.
02:43:28 Maybe you can rule that in statistically,
02:43:30 but this is the course of life on earth.
02:43:34 Without all that sulfate being raised up,
02:43:36 this Cambrian explosion almost certainly
02:43:38 would not have happened.
02:43:39 And then we wouldn’t have had animals and so on and so on.
02:43:42 So it’s this kind of explanation of the Cambrian explosion.
02:43:48 So let me actually say in several ways.
02:43:51 So folks who challenge the validity
02:43:55 of the theory of evolution will give us an example.
02:44:00 Now I’m not well studied in this,
02:44:02 but will give us an example of the Cambrian explosion
02:44:04 as like, this thing is weird.
02:44:07 Oh, it is weird, yeah.
02:44:08 So the question I would have is
02:44:13 what’s the biggest mystery or gap in understanding
02:44:17 about evolution?
02:44:19 Is it the Cambrian explosion?
02:44:21 And if so, what’s our best understanding
02:44:23 of how to explain, first of all, what is it?
02:44:28 In my understanding, in the short amount of time,
02:44:30 maybe 10 million years, 100 million years,
02:44:32 something like that, a huge number of animals,
02:44:35 a variety, diversity of animals were created.
02:44:39 Anyway, there’s like five questions in there.
02:44:41 Is that the biggest mystery?
02:44:43 No, I don’t think it’s a particularly big mystery
02:44:45 really anymore.
02:44:48 There are still mysteries about why then.
02:44:51 And I’ve just said sulfate being washed
02:44:52 into the oceans is one.
02:44:54 It needs oxygen and oxygen levels rose around that time.
02:44:59 So probably before that, they weren’t high enough
02:45:01 for animals.
02:45:02 What we’re seeing with the Cambrian explosion
02:45:04 is the beginning of predators and prey relationships.
02:45:07 We’re seeing modern ecosystems and we’re seeing arms races
02:45:12 and we’re seeing the full creativity of evolution unleashed.
02:45:20 So I talked about the boring billion,
02:45:22 nothing happens for one and a half billion years,
02:45:26 one and a half billion years.
02:45:29 The assumption, and this is completely wrong,
02:45:31 this assumption, is then that evolution works really slowly
02:45:36 and that you need billions of years
02:45:37 to affect some small change
02:45:40 and then another billion years to do something else.
02:45:42 It’s completely wrong.
02:45:44 Evolution gets stuck in a stasis and it stays that way
02:45:47 for tens of millions, hundreds of millions of years.
02:45:50 And Steven Jay Gould used to argue this,
02:45:52 he called it punctuated equilibrium,
02:45:53 but he was doing it to do with animals
02:45:55 and to do with the last 500 million years or so,
02:45:58 where it’s much less obvious
02:46:00 than if you think about the entire planetary history.
02:46:02 And then you realize that the first two billion years
02:46:04 was bacteria only.
02:46:06 You have the origin of life,
02:46:07 two billion years of just bacteria,
02:46:09 oxygen photosynthesis arising here.
02:46:11 Then you have a global catastrophe,
02:46:14 snowball earths and great oxidation event
02:46:16 and then another billion years of nothing happening
02:46:18 and then some period of upheavals
02:46:20 and then another snowball earth
02:46:21 and then suddenly you see the Cambrian explosion.
02:46:23 This is long periods of stasis
02:46:25 where the world is in a stable state
02:46:27 and is not geared towards increasing complexity.
02:46:31 It’s just everything is in balance.
02:46:33 And only when you have a catastrophic level,
02:46:35 global level problem like a snowball earth,
02:46:38 it forces everything out of balance
02:46:40 and there’s a tipping point and you end up somewhere else.
02:46:42 Now, the idea that evolution is slow is wrong.
02:46:48 It can be incredibly fast.
02:46:50 And I mentioned earlier on that you can,
02:46:52 in theory, it would take half a million years
02:46:54 to invent an eye, for example, from a light sensitive spot.
02:46:57 It doesn’t take long to convert
02:47:01 one kind of tube into a tube with nobbles on it
02:47:05 into a tube with arms on it and then multiple arms
02:47:08 and then at one end is the head
02:47:10 where it starts out as a swelling.
02:47:11 It’s not difficult intellectually to understand
02:47:15 how these things can happen.
02:47:18 It boggles the mind that it can happen so quickly,
02:47:20 but we’re used to human timescales.
02:47:24 And what we need to talk about is generations of things
02:47:27 that live for a year in the ocean.
02:47:30 And then a million years is a million generations.
02:47:33 And the amount of change that you can do,
02:47:35 it can affect in that period of time is enormous.
02:47:38 And we’re dealing with large populations of things
02:47:41 where selection is sensitive to pretty small changes
02:47:44 and can, so again, as soon as you throw in
02:47:48 the competition of predators and prey
02:47:50 and you’re ramping up the scale of evolution,
02:47:53 it’s not very surprising that it happens very quickly
02:47:56 when the environment allows it to happen.
02:47:58 So I don’t think there’s a big mystery.
02:47:59 There’s lots of details that need to be filled in.
02:48:03 I mean, the big mystery in biology is consciousness.
02:48:11 The big mystery in biology is consciousness.
02:48:13 Well, intelligence is kind of a mystery too.
02:48:21 I mean, you said biology, not psychology.
02:48:28 Because from a biology perspective,
02:48:30 it seems like intelligence and consciousness
02:48:32 all are the same, like weird, like all the brain stuff.
02:48:37 I don’t see intelligence as necessarily that difficult,
02:48:41 I suppose.
02:48:42 I mean, I see it as a form of computing
02:48:44 and I don’t know much about computing, so I…
02:48:48 You don’t know much about consciousness either.
02:48:50 So I mean, I suppose, oh, I see.
02:48:54 I see, I see, I see, I see.
02:48:57 That consciousness you do know a lot about as a human being.
02:49:00 No, no, I mean, I think I can understand the wiring
02:49:04 of a brain as a series of, in pretty much the same way
02:49:08 as a computer in theory, in terms of the circuitry of it.
02:49:16 The mystery to me is how this system gives rise to feelings,
02:49:21 as we were talking about earlier on.
02:49:23 Yeah, I just, I think we oversimplify intelligence.
02:49:27 I think the dance, the magic of reasoning
02:49:31 is as interesting as the magic of feeling.
02:49:36 We tend to think of reasoning as like very,
02:49:42 running a very simplistic algorithm.
02:49:45 I think reasoning is the interplay between memory,
02:49:48 whatever the hell is going on, the unconscious mind,
02:49:51 all of that.
02:49:55 I’m not trying to diminish it in any way at all.
02:49:58 Obviously, it’s extraordinarily exquisitely complex,
02:50:01 but I don’t see a logical difficulty with how it works.
02:50:06 Yeah, no, I mean, I agree with you, but sometimes, yeah,
02:50:11 there’s a big cloak of mystery around consciousness.
02:50:16 Let me compare it with classical versus quantum physics.
02:50:20 Classical physics is logical, and you can understand the kind
02:50:26 of language we’re dealing with.
02:50:27 It’s almost at the human level, we’re
02:50:29 dealing with stars and things that we can see.
02:50:31 And when you get to quantum mechanics and things,
02:50:34 it’s practically impossible for the human mind
02:50:36 to compute what just happened there.
02:50:39 Yeah, I mean, that is the same.
02:50:41 It’s like, you understand mathematically
02:50:44 that the notes of a musical composition, that’s intelligence.
02:50:49 But why it makes you feel a certain way,
02:50:54 that is much harder to understand.
02:50:57 Yeah, that’s really, but it was interesting framing
02:51:02 that that’s a mystery at the core of biology.
02:51:05 I wonder who solves consciousness.
02:51:09 I tend to think consciousness will
02:51:11 be solved by the engineer, meaning the person who builds
02:51:15 it, who keeps trying to build the thing,
02:51:20 versus biology, such a complicated system.
02:51:24 I feel like the building blocks of consciousness
02:51:29 from a biological perspective are like,
02:51:34 that’s like the final creation of a human being.
02:51:36 So you have to understand the whole damn thing.
02:51:38 You said the electrical field, but like,
02:51:42 electrical field is plus plus.
02:51:43 Everything, the whole shebang.
02:51:47 I’m inclined to agree.
02:51:48 I mean, my feeling is from my meager knowledge
02:51:51 of the history of science is that the biggest breakthrough
02:51:53 has usually come through from a field that was not related.
02:51:57 So if anyone is not going to be a biologist who
02:52:00 solves consciousness, just because biologists
02:52:03 are too embedded in the nature of the problem.
02:52:06 And then nobody’s going to believe you when you’ve done it,
02:52:09 because nobody’s going to be able to prove that this AI is
02:52:12 in fact conscious and sad in any case,
02:52:16 and any more than you can prove that a dog is
02:52:18 conscious and sad.
02:52:20 So it tells you that it is in good language,
02:52:23 and you must believe it.
02:52:24 But I think most people will accept,
02:52:27 if faced with that, that that’s what it is.
02:52:30 All of this probability of complex life,
02:52:38 in one way, I think why it matters is that my expectation,
02:52:45 I suppose, is that we will be over the next 100 years
02:52:49 or so, if we survive at all, that AI will increasingly
02:52:53 dominate.
02:52:53 And pretty much anything that we put out
02:52:56 into space looking for other, well, for the universe,
02:53:00 for what’s out there, will be AI, won’t be us.
02:53:03 We won’t be doing that.
02:53:04 Or when we do, it’ll be on a much more limited scale.
02:53:07 I suppose the same would apply to any alien civilization.
02:53:12 So perhaps rather than looking for signs of life out there,
02:53:15 we should be looking for AI out there.
02:53:19 But then we face the problem that I
02:53:25 don’t see how a planet is going to give rise directly to AI.
02:53:29 I can see how a planet can give rise directly to organic life.
02:53:34 And if the principles that govern the evolution of life
02:53:36 on Earth apply to other planets as well,
02:53:40 and I think a lot of them would, then
02:53:43 the likelihood of ending up with a humanlike civilization
02:53:47 capable of giving rise to AI in the first place
02:53:50 is massively limited.
02:53:52 Once you’ve done it once, perhaps it takes over
02:53:54 the universe, and maybe there’s no issue.
02:53:57 But it seems to me that the two are necessarily linked,
02:54:01 that you’re not going to just turn a sterile planet
02:54:03 into an AI life form without the intermediary of the organics
02:54:07 first.
02:54:08 So you have to run the full evolutionary computation
02:54:13 with the organics to create AI.
02:54:15 How does AI bootstrap itself up without the aid, if you like,
02:54:18 of an intelligent designer?
02:54:20 The origin of AI is going to have
02:54:23 to be in the chemistry of a planet.
02:54:27 But that’s not a limiting factor, right?
02:54:29 So let me ask the Fermi paradox question.
02:54:35 Let’s say we live in this incredibly dark and beautiful
02:54:40 world of just billions of planets with bacteria on it
02:54:47 and very few intelligent civilizations,
02:54:49 and yet there’s a few out there.
02:54:52 Why haven’t we, at scale, seen them visit us?
02:54:58 What’s your sense?
02:54:59 Is it because they don’t exist?
02:55:02 Well, don’t exist in the right part of the universe
02:55:04 at the right time.
02:55:05 That’s the simplest answer for it.
02:55:08 Is that the one you find the most compelling,
02:55:10 or is there some other explanation?
02:55:13 I find that, no, it’s not that I find it more compelling.
02:55:16 It’s that I find more probable.
02:55:19 And I find all of them, I mean, there’s
02:55:21 a lot of handwaving in this.
02:55:22 We just don’t know.
02:55:24 So I’m trying to read out from what I know about life on Earth
02:55:27 to what might happen somewhere else.
02:55:30 And it gives, to my mind, a bit of a pessimistic view
02:55:33 of bacteria everywhere and only occasional intelligent life
02:55:37 and running forward humans only once on Earth and nothing else
02:55:41 that you would necessarily be any more excited about making
02:55:44 contact with than you would be making contact with them
02:55:47 on Earth.
02:55:49 So I think the chances are pretty limited.
02:55:52 And the chances of us surviving are pretty limited, too,
02:55:56 in the way we’re going on at the moment.
02:55:58 The likelihood of us not making ourselves extinct
02:56:01 within the next few hundred years,
02:56:03 possibly within the next 50 or 100 years, seems quite small.
02:56:08 I hope we can do better than that.
02:56:11 So maybe the only thing that will survive from humanity
02:56:13 will be AI.
02:56:14 And maybe AI, once it exists and once
02:56:15 it’s capable of effectively copying itself and cutting
02:56:19 humans out of the loop, then maybe that
02:56:22 will take over the universe.
02:56:24 I mean, there’s a kind of inherent sadness
02:56:26 to the way you described that.
02:56:28 But isn’t that also potentially beautiful,
02:56:31 that that’s the next step of life, I suppose,
02:56:37 from your perspective, as long as it carries the flame
02:56:39 of consciousness somehow?
02:56:41 No, I think, yes, there can be some beauty to it
02:56:43 being the next step of life.
02:56:44 And I don’t know if consciousness matters or not,
02:56:46 from that point of view, to be honest with you.
02:56:49 Yeah.
02:56:50 But there’s some sadness, yes, probably,
02:56:53 because I think it comes down to the selfishness
02:56:58 that we were talking about earlier on.
02:56:59 I am an individual with a desire not
02:57:03 to be displaced from life.
02:57:06 I want to stay alive.
02:57:07 I want to be here.
02:57:11 So I suppose the threat that a lot of people would feel
02:57:13 is that we will just be wiped out,
02:57:15 so that there will be potential conflict between AI and humans
02:57:20 and that AI will win because it’s a lot smarter.
02:57:25 Boy, would that be a sad state of affairs
02:57:27 if consciousness is just an intermediate stage
02:57:32 between bacteria and AI, right?
02:57:36 Well, I would see bacteria as being potentially
02:57:38 a kind of primitive form of consciousness anyway.
02:57:41 So the whole of life on Earth, to my mind,
02:57:43 is capable of some form of feelings
02:57:46 in response to the environment.
02:57:47 That’s not to say it’s intelligent,
02:57:49 it’s got its own algorithms for intelligence,
02:57:52 but nothing comparable with us.
02:57:55 I think it’s beautiful what a planet, what a sterile planet,
02:57:57 can come up with.
02:57:59 It’s astonishing that it’s come up with all of this stuff
02:58:01 that we see around us and that either we or whatever we
02:58:06 produce is capable of destroying all of that is a sad thought.
02:58:12 But it’s also hugely pessimistic.
02:58:17 I’d like to think that we’re capable of giving rise
02:58:19 to something which is at least as good,
02:58:21 if not better than us, as AI.
02:58:24 Yeah, I have that same optimism, especially a thing
02:58:29 that is able to propagate throughout the universe
02:58:31 more efficiently than humans can.
02:58:33 Or extensions of humans, some merger with AI and humans,
02:58:39 whether that comes from bioengineering of the human body
02:58:43 to extend its life somehow, to carry
02:58:47 that flame of consciousness and that personality
02:58:50 and the beautiful tension that’s within all of us,
02:58:54 carry that through to multiple planets,
02:58:56 to multiple solar systems, all out there in the universe.
02:58:59 I mean, that’s a beautiful vision.
02:59:02 Whether AI can do that or bioengineered humans can,
02:59:07 that’s an exciting possibility.
02:59:09 And especially meeting other alien civilizations
02:59:13 in that same kind of way.
02:59:14 Do you think aliens have consciousness?
02:59:16 If they’re organic.
02:59:18 So organic is connected to consciousness.
02:59:20 I mean, I think any system which is going to bootstrap itself
02:59:24 up from planetary origins, I mean, let me finish this
02:59:30 and then come on to something else.
02:59:31 But from planetary origins is going
02:59:34 to face similar constraints.
02:59:36 And those constraints are going to be addressed
02:59:37 in similar basic engineering ways.
02:59:40 And I think it will be cellular.
02:59:41 And I think it will have electrical charges.
02:59:43 And I think it will have to be selected
02:59:46 in populations over time.
02:59:47 And all of these things will tend
02:59:48 to give rise to the same processes
02:59:50 as the simplest fix to a difficult problem.
02:59:53 So I would expect it to be conscious, yes.
02:59:54 And I would expect it to resemble life
02:59:57 on Earth in many ways.
03:00:00 When I was about, I guess, 15 or 16,
03:00:03 I remember reading a book by Fred Hoyle
03:00:06 called The Black Cloud, which I was a budding biologist
03:00:10 at the time.
03:00:11 And this was the first time I’d come across someone really
03:00:13 challenging the heart of biology and saying,
03:00:16 you are far too parochial.
03:00:18 You’re thinking about life as carbon based.
03:00:20 Here’s a life form which is kind of dust, interstellar dust
03:00:26 on a solar system scale.
03:00:30 And it’s a novel.
03:00:32 But I felt enormously challenged by that novel
03:00:34 because it hadn’t occurred to me how limited my thinking was,
03:00:39 how narrow minded I was being.
03:00:43 And here was a great physicist with a completely different
03:00:46 conception of what life could be.
03:00:48 And since then, I’ve seen him attacked in various ways.
03:00:51 And I’m kind of reluctant to say the attacks make more sense
03:00:55 to me than the original story, which
03:00:58 is to say, even in terms of information processing,
03:01:02 if you’re on that scale and there’s
03:01:04 a limit to the speed of light, how quickly can something
03:01:06 think if you’re needing to broadcast
03:01:10 across the solar system, it’s going to be slow.
03:01:16 It’s not going to hold a conversation with you
03:01:19 on the kind of timelines that Fred Hoyle was imagining,
03:01:22 at least not by any easy way of doing it,
03:01:25 assuming that the speed of light is a limit.
03:01:28 And then again, you really can’t.
03:01:32 This is something Richard Dawkins argued long ago.
03:01:34 And I do think he’s right.
03:01:36 There is no other way to generate
03:01:39 this level of complexity than natural selection.
03:01:41 Nothing else can do it.
03:01:42 You need populations.
03:01:44 And you need selection in populations
03:01:46 and a kind of an isolated interstellar cloud.
03:01:53 Again, there’s unlimited time.
03:01:55 And maybe there’s no problems with distance.
03:01:57 But you need to have a certain frequency of generational time
03:02:03 to generate a serious level of complexity.
03:02:07 And I just have a feeling it’s never going to work.
03:02:11 Well, as far as we know, so natural selection and evolution
03:02:15 is really a powerful tool here on Earth.
03:02:17 But there could be other mechanisms.
03:02:19 So I don’t know if you’re familiar with cellular automata,
03:02:24 but complex systems that have really simple components
03:02:29 and seemingly move based on simple rules
03:02:31 when they’re taken as a whole, really interesting complexity
03:02:34 emerges.
03:02:36 I don’t know what the pressures on that are.
03:02:38 It’s not really selection, but interesting complexity
03:02:41 seems to emerge.
03:02:42 And that’s not well understood exactly why that complexity
03:02:46 emerges.
03:02:46 I think there’s a difference between complexity
03:02:48 and evolution.
03:02:51 So some of the work we’re doing on the origin of life
03:02:53 is thinking about how do genes arise?
03:02:59 How does information arise in biology?
03:03:01 And thinking about it from the point of view
03:03:03 of reacting CO2 with hydrogen, what do you get?
03:03:06 Well, what you’re going to get is carboxylic acids, then
03:03:08 amino acids.
03:03:09 It’s quite hard to make nucleotides.
03:03:13 And it’s possible to make them, and it’s been done,
03:03:15 and it’s been done following this pathway as well.
03:03:18 But you make trace amounts.
03:03:20 And so the next question, assuming
03:03:21 that this is the right way of seeing the question, which
03:03:24 maybe it’s just not, but let’s assume it is,
03:03:26 is, well, how do you reliably make more nucleotides?
03:03:29 And how do you become more complex and better at becoming
03:03:32 a nucleotide generating machine?
03:03:35 And the answer is, well, you need positive feedback loops,
03:03:38 some form of autocatalysis.
03:03:40 So that can work, and we know it happens in biology.
03:03:43 If this nucleotide, for example, catalyzes CO2 fixation,
03:03:48 then you’re going to increase the rate of flux
03:03:50 through the whole system, and you’re
03:03:51 going to effectively steepen the driving force
03:03:53 to make more nucleotides.
03:03:56 And this can be inherited because there
03:03:59 are forms of membrane heredity that you can have.
03:04:02 And effectively, if a cell divides in two
03:04:06 and it’s got a lot of stuff inside it,
03:04:08 and that stuff is basically bound
03:04:10 as a network which is capable of regenerating itself,
03:04:14 then it will inevitably regenerate itself.
03:04:17 And so you can develop greater complexity.
03:04:21 But everything that I’ve said depends on the underlying rules
03:04:24 of thermodynamics.
03:04:25 There is no evolvability about that.
03:04:27 It’s simply an inevitable outcome of your starting point,
03:04:33 assuming that you’re able to increase the driving
03:04:35 force through the system.
03:04:37 You will generate more of the same.
03:04:38 You’ll expand on what you can do,
03:04:40 but you’ll never get anything different than that.
03:04:42 And it’s only when you introduce information into that
03:04:45 as a gene, as a kind of small stretch of RNA, which
03:04:52 can be random stretch, then you get real evolvability.
03:04:55 Then you get biology as we know it.
03:04:57 But you also have selection as we know it.
03:05:00 Yeah, I mean, I don’t know how to think about information.
03:05:06 That’s a kind of memory of the system.
03:05:08 So it’s not, yeah, at the local level,
03:05:10 it’s propagation of copying yourself and changing
03:05:13 and improving your adaptability to the environment.
03:05:17 But if you look at Earth as a whole, it has a kind of memory.
03:05:23 That’s the key feature of it.
03:05:25 In what way?
03:05:27 It remembers the stuff it tries.
03:05:30 Like, if you were to describe Earth,
03:05:33 I think evolution is something that we experience
03:05:39 as individual organisms.
03:05:41 That’s how the individual organisms
03:05:44 interact with each other.
03:05:45 There’s a natural selection.
03:05:47 But when you look at Earth as an organism in its entirety,
03:05:54 how would you describe it?
03:05:55 I mean.
03:05:56 Well, not as an organism.
03:05:57 I mean, the idea of Gaia is lovely.
03:06:00 And James Lovelock originally put Gaia out
03:06:04 as an organism that had somehow evolved.
03:06:07 And he was immediately attacked by lots of people.
03:06:10 And he’s not wrong, but he backpedaled somewhat
03:06:14 because that was more of a poetic vision than the science.
03:06:20 The science is now called Earth systems science.
03:06:23 And it’s really about how does the world regulate itself
03:06:26 so it remains within the limits which are hospitable to life.
03:06:29 And it does it amazingly well.
03:06:30 And it is working at a planetary level of integration,
03:06:37 of regulation.
03:06:38 But it’s not evolving by natural selection.
03:06:41 And it can’t because there’s only one of it.
03:06:43 And so it can change over time.
03:06:45 But it’s not evolving.
03:06:46 All the evolution is happening in the parts of the system.
03:06:50 Yeah, but it’s a self sustaining organism.
03:06:53 No, it’s sustained by the sun.
03:06:56 Right, so you don’t think it’s possible to see Earth
03:07:00 as its own organism?
03:07:03 I think it’s poetic and beautiful.
03:07:04 And I often refer to the Earth as a living planet.
03:07:08 But it’s not, in biological terms, an organism, no.
03:07:14 If aliens were to visit Earth, what would they notice?
03:07:20 What would be the basic unit of light they would notice?
03:07:24 Trees, probably.
03:07:25 I mean, it’s green.
03:07:26 It’s green and blue.
03:07:27 I think that’s the first thing you’d notice.
03:07:29 It stands out from space as being different to any
03:07:32 of the other planets.
03:07:33 So it would notice the trees at first because the green.
03:07:36 Well, I would.
03:07:36 I notice the green, yes.
03:07:39 And then probably notice, figure out the photosynthesis.
03:07:42 Probably notice cities a second, I suspect, maybe first.
03:07:47 If they arrived at night, they’d notice cities first,
03:07:49 that’s for sure.
03:07:50 It depends.
03:07:50 Depends the time.
03:07:52 You write quite beautifully in Transformers.
03:07:55 Once again, I think you opened the book in this way.
03:07:57 I don’t remember.
03:07:59 From space, describing Earth, it’s such an interesting idea
03:08:04 of what Earth is, you also, I mean, Hitchhiker’s Guide,
03:08:10 summarizing it as harmless, or mostly harmless.
03:08:13 It’s a beautifully poetic thing.
03:08:15 You open Transformers with, from space,
03:08:19 it looks gray and crystalline, obliterating
03:08:22 the blue green colors of the living Earth.
03:08:24 It is crisscrossed by irregular patterns
03:08:27 and convergent striations.
03:08:30 There’s a central amorphous density
03:08:33 where these scratches seem lighter.
03:08:35 This, quote, growth does not look alive,
03:08:38 although it has extended out along some lines,
03:08:41 and there is something grasping and parasitic about it.
03:08:44 Across the globe, there are thousands of them,
03:08:47 varying in shape and detail, but all of them gray, angular,
03:08:51 and organic, spreading.
03:08:54 Yet at night, they light up, glowing up the dark sky,
03:08:59 suddenly beautiful.
03:09:00 Perhaps these cankers on the landscape
03:09:03 are in some sense living.
03:09:05 There’s a controlled flow of energy.
03:09:07 There must be information and some form of metabolism,
03:09:10 some turnover of materials.
03:09:12 Are they alive?
03:09:14 No, of course not.
03:09:16 They are cities.
03:09:18 So is there some sense that cities are living beings?
03:09:22 You think aliens would think of them as living beings?
03:09:24 Well, it’d be easy to see it that way, wouldn’t it?
03:09:27 It wakes up at night, they wake up at night.
03:09:30 Strictly nocturnal, yes.
03:09:33 I imagine that any aliens that are smart enough
03:09:36 to get here would understand
03:09:37 that they’re not living beings.
03:09:40 My reason for saying that is that we tend to think
03:09:47 of biology in terms of information and forget about cells.
03:09:52 I was trying to draw a comparison between the cell
03:09:54 as a city and the energy flow through the city
03:09:57 and the energy flow through cells
03:09:59 and the turnover of materials.
03:10:01 And an interesting thing about cities
03:10:04 is that they’re not really exactly governed by anybody.
03:10:09 There are regulations and systems and whatever else,
03:10:12 but it’s pretty loose.
03:10:16 They have their own life,
03:10:18 their own way of developing over time.
03:10:20 And in that sense, they’re quite biological.
03:10:23 There was a plan after the great fire of London.
03:10:27 Christopher Wren was making plans
03:10:29 not only for St. Paul’s Cathedral,
03:10:31 but also to rebuild in large Parisian type boulevards,
03:10:35 a large part of the area of central London that was burned.
03:10:40 And it never happened
03:10:42 because they didn’t have enough money, I think.
03:10:44 But it’s interesting what was in the plan.
03:10:45 There were all these boulevards
03:10:47 that were built in the middle of the city.
03:10:48 It’s interesting what was in the plan.
03:10:50 There were all these boulevards,
03:10:51 but there were no pubs and no coffee houses
03:10:55 or anything like that.
03:10:56 And the reality was London just kind of grew up
03:11:00 in a set of jumbled streets.
03:11:03 And it was the coffee houses and the pubs
03:11:04 where all the business of the city of London was being done.
03:11:07 And that was where the real life of the city was.
03:11:09 And no one had planned it.
03:11:10 The whole thing was unplanned and works much better that way.
03:11:13 And in that sense, the cell is completely unplanned,
03:11:15 is not controlled by the genes in the nucleus
03:11:17 in the way that we might like to think that it is,
03:11:19 but it’s kind of evolved entity
03:11:22 that has the same kind of flux,
03:11:24 the same animation, the same life.
03:11:25 So I think it’s a beautiful analogy,
03:11:28 but I wouldn’t get too stuck with it as a metaphor.
03:11:32 See, I disagree with you.
03:11:33 I disagree with you.
03:11:34 I think you are so steeped,
03:11:39 and actually the entirety of science,
03:11:43 the history of science is steeped
03:11:45 in a biological framework of thinking about what is life.
03:11:50 And not just biological, it’s very human centric too.
03:11:54 That human, the human organism is the epitome of life
03:11:59 on earth.
03:12:00 I don’t know.
03:12:01 I think there is some deep fundamental way
03:12:04 in which a city is a living being
03:12:07 in the same way that a human individual can.
03:12:09 But it doesn’t give rise to an offspring city.
03:12:13 So it doesn’t work by natural selection.
03:12:15 It works by, if anything, memes.
03:12:17 It works by copying itself conceptually
03:12:21 as a mode of being.
03:12:24 So maybe memes, maybe ideas are the organisms
03:12:29 that are really essential to life on earth.
03:12:32 Maybe it’s much more important
03:12:34 about the collective aspect of human nature,
03:12:37 the collective intelligence
03:12:38 than the individual intelligence.
03:12:40 Maybe the collective humanity is the organism.
03:12:43 And the thing that defines the collective intelligence
03:12:48 of humanity is the ideas.
03:12:50 And maybe the way that manifests itself is cities,
03:12:54 maybe, or societies or geographically concentrated societies
03:12:57 or nations and all that kind of stuff.
03:12:59 I mean, from an alien perspective,
03:13:02 it’s possible that that is the more deeply noticeable thing,
03:13:06 not from a place of ignorance.
03:13:08 What’s noticeable doesn’t tell you how it works.
03:13:12 I think, I mean, I don’t have any problem
03:13:14 with what you’re saying really,
03:13:15 except that it’s not possible without the humans.
03:13:20 You know, we went from a hunter gatherers type economy,
03:13:25 if you like, without cities to cities.
03:13:28 And as soon as we get into human evolution
03:13:30 and culture and society and so on,
03:13:32 then yes, there are other forms of evolution,
03:13:36 other forms of change.
03:13:38 But cities don’t directly propagate themselves,
03:13:41 they propagate themselves through human societies
03:13:43 and human societies only exist because humans
03:13:46 as individuals propagate themselves.
03:13:48 So there’s a kind of, there is a hierarchy there
03:13:51 and without the humans in the first place,
03:13:52 none of the rest of it exists.
03:13:54 So do you, life is primarily defined by the basic unit
03:13:59 on which evolution can operate?
03:14:01 I think it’s a really important thing, yes.
03:14:04 Yeah.
03:14:05 And we don’t know, we don’t have any other better ideas
03:14:08 than evolution for how to create life.
03:14:10 I never came across a better idea than evolution.
03:14:13 I mean, maybe I’m just ignorant and I don’t know.
03:14:15 And there’s, you know, you mentioned that’s no automator
03:14:19 and so on, and I don’t think specifically about that,
03:14:22 but I have thought about it in terms of selective units
03:14:24 of the origin of life and the difference
03:14:26 between evolvability and complexity
03:14:29 or just increasing complexity,
03:14:31 but within very narrow, narrowly defined limits.
03:14:35 The great thing about genes and about selection
03:14:39 is it just knocks down all those limits.
03:14:41 It gives you a world of information in the end
03:14:43 which is limited only by the biophysical reality
03:14:47 of what kind of an organism you are,
03:14:49 what kind of a planet you live on and so on.
03:14:52 And cities and all these other forms that look alive
03:14:55 and could be described as alive
03:14:58 because they can’t propagate themselves
03:14:59 can only exist as the product of something
03:15:02 that did propagate itself.
03:15:05 Yeah.
03:15:07 I mean, there’s a deeply compelling truth
03:15:09 to that kind of way of looking at things,
03:15:11 but I just hope that we don’t miss the giant cloud
03:15:17 among us.
03:15:18 I kind of hope that I’m wrong about a lot of this
03:15:21 because I can’t say that my worldview
03:15:24 is particularly uplifting, but in some sense,
03:15:28 it doesn’t matter if it’s uplifting or not.
03:15:29 Science is about what’s reality, what’s out there,
03:15:33 why is it this way?
03:15:35 And I think there’s beauty in that too.
03:15:39 There’s beauty in darkness.
03:15:41 You write about life and death
03:15:43 sort of at the biological level.
03:15:46 Does the question of suicide, why live,
03:15:49 does the question of why the human mind
03:15:52 is capable of depression, are you able to introspect
03:15:56 that from a place of biology?
03:16:00 Why our minds, why we humans can go to such dark places?
03:16:05 Why can we commit suicide?
03:16:08 Why can we go suffer, suffer period,
03:16:15 but also suffer from a feeling of meaninglessness
03:16:19 of going to a dark place that depression can take you?
03:16:23 Is this a feature of life or is it a bug?
03:16:30 I don’t know.
03:16:31 I mean, if it’s a feature of life,
03:16:32 then I suppose it would have to be true
03:16:33 of other organisms as well.
03:16:35 And I don’t know, we were talking about dogs earlier on
03:16:39 and they can certainly be very sad and upset
03:16:43 and may mooch for days after their owner died
03:16:46 or something like that.
03:16:47 So I suspect in some sense it’s a feature of biology.
03:16:50 It’s probably a feature of mortality.
03:16:54 It’s probably a, but beyond all of that,
03:16:59 I mean, I guess there’s two ways you could come at it.
03:17:01 There’s one of them would be to say,
03:17:03 well, you can effectively do the math
03:17:07 and come to the conclusion that it’s all pointless
03:17:10 and that there’s really no point
03:17:11 in me being here any longer.
03:17:14 And maybe that’s true in the greater scheme of things.
03:17:17 You can justify yourself in terms of society,
03:17:20 but society will be gone soon enough as well.
03:17:22 And you end up with a very bleak place just by logic.
03:17:26 In some sense, it’s surprising
03:17:27 that we can find any meaning at all.
03:17:30 Well, maybe this is where consciousness comes in
03:17:32 that we have transient joy, but with transient joy,
03:17:35 we have transient misery as well.
03:17:37 And sometimes with everything in biology,
03:17:41 getting the regulation right is practically impossible.
03:17:45 You will always have a bell shaped curve
03:17:47 where some people unfortunately are at the joy end
03:17:50 and some people are at the misery end.
03:17:52 And that’s the way brains are wired.
03:17:55 And I doubt there’s ever an escape from that.
03:17:58 It’s the same with sex and everything else as well.
03:18:00 We’re dealing with, you can’t regulate it.
03:18:04 So anything goes, it’s all part of biology.
03:18:12 Amen to that.
03:18:13 Let me, on writing in your book, Power, Sex and Suicide.
03:18:21 First of all, can I just read off the books you’ve written?
03:18:24 If there’s any better titles and topics to be covered,
03:18:27 I don’t know what they are.
03:18:28 It makes me look forward
03:18:29 to whatever you’re going to write next.
03:18:31 I hope there’s things you write next.
03:18:34 So first you wrote oxygen, the molecule that made the world
03:18:37 as we’ve talked about this idea
03:18:39 of the role of oxygen in life on earth.
03:18:41 Then wait for it, power, sex, suicide, mitochondria
03:18:46 and the meaning of life.
03:18:48 Then life ascending, the 10 great inventions of evolution.
03:18:52 The vital question, the first book I’ve read of yours,
03:18:54 the vital question, why is life the way it is?
03:18:58 And the new book, Transformer,
03:19:00 the deep chemistry of life and death.
03:19:03 In Power, Sex and Suicide, you write about writing
03:19:08 or about a lot of things,
03:19:09 but I have a question about writing.
03:19:13 You write, in The Hitchhiker’s Guide to the Galaxy,
03:19:16 Ford Perfect spends 15 years researching his revision
03:19:20 to the guide’s entry on the earth,
03:19:23 which originally read harmless.
03:19:26 By the way, I would also as a side quest,
03:19:29 as a side question would like to ask you
03:19:30 what would be your summary of what earth is.
03:19:34 You write, his long essay on the subject is edited down
03:19:37 by the guide to read mostly harmless.
03:19:41 I suspect that too many new editions suffer similar fate,
03:19:46 if not through absurd editing decisions,
03:19:48 at least through a lack of meaningful change in content.
03:19:51 As it happens, nearly 15 years have passed
03:19:54 since the first edition of Power, Sex, Suicide was published
03:19:57 and I am resisting the temptation to make any lame revisions.
03:20:02 Some say that even Darwin lessened the power
03:20:05 of his arguments in The Origin of Species
03:20:08 through his multiple revisions,
03:20:10 in which he dealt with criticisms
03:20:12 and sometimes shifted his views in the wrong direction.
03:20:16 I prefer my original to speak for itself,
03:20:19 even if it turns out to be wrong.
03:20:23 Let me ask the question about writing,
03:20:25 both your students in the academic setting,
03:20:28 but also writing some of the most brilliant writings
03:20:30 on science and humanity I’ve ever read.
03:20:33 What’s the process of writing?
03:20:36 How do you advise other humans?
03:20:43 If you were to talk to young Darwin or the young you
03:20:47 and just young anybody and give advice about how to write
03:20:51 and how to write well about these big topics,
03:20:54 what would you say?
03:20:56 I mean, I suppose there’s a couple of points.
03:20:59 One of them is what’s the story?
03:21:03 What do I want to know?
03:21:04 What do I want to convey?
03:21:06 Why does it matter to anybody?
03:21:08 And very often the biggest, most interesting questions,
03:21:15 the childlike questions are the one actually
03:21:19 that everybody wants to ask, but dents quite,
03:21:22 do it in case they look stupid.
03:21:24 And one of the nice things about being in science
03:21:26 is the longer you’re in,
03:21:28 the more you realize that everybody doesn’t know
03:21:30 the answer to these questions
03:21:31 and it’s not so stupid to ask them after all.
03:21:36 So trying to ask the questions
03:21:39 that I would have been asking myself at the age of 15, 16,
03:21:44 when I was really hungry to know about the world
03:21:47 and didn’t know very much about it
03:21:48 and wanted to go to the edge of what we know,
03:21:53 but be helped to get there.
03:21:58 I don’t want to be too much terminology.
03:22:01 And so I want someone to keep a clean eye
03:22:03 on what the question is.
03:22:07 Beyond that, I’ve wondered a lot about who am I writing for?
03:22:13 And that was in the end, the only answer I had
03:22:16 was myself at the age of 15 or 16,
03:22:19 because even if you just don’t know who’s reading,
03:22:25 but also where are they reading it?
03:22:27 Are they reading it in the bath or in bed
03:22:29 or on the Metro or listening to an audio book?
03:22:34 Do you want to have a recapitulation every few pages
03:22:39 because you read three pages at a time
03:22:41 or are you really irritated by that?
03:22:44 You’re going to get criticism from people
03:22:46 who are irritated by what you’re doing.
03:22:48 And you don’t know who they are or what you’re going to do
03:22:50 that’s going to irritate people.
03:22:51 And in the end, all you can do is just try
03:22:53 and please yourself.
03:22:57 And that means, well, what are these big fun,
03:23:00 fascinating and big questions?
03:23:03 And what do we know about it?
03:23:04 And can I convey that?
03:23:07 And I kind of learned in trying to write,
03:23:10 first of all, say what we know.
03:23:14 And I was shocked in the first couple of books
03:23:16 how often I came up quickly against
03:23:19 all the stuff we don’t know.
03:23:21 And if you’re trying to, I’ve realized later on
03:23:25 in supervising various physicists and mathematicians
03:23:29 who are PhD students, their maths is way beyond
03:23:32 what I can do.
03:23:34 But the process of trying to work out
03:23:36 what are we actually going to model here?
03:23:37 What’s going into this equation?
03:23:39 It’s a very similar one to writing.
03:23:40 What am I going to put on a page?
03:23:42 What’s the simplest possible way
03:23:43 I can encapsulate this idea?
03:23:45 So that I now have it as a unit
03:23:47 that I can kind of see how it interacts
03:23:48 with the other units.
03:23:50 And you realize that, well, if this is like that
03:23:53 and this is like this, then that can’t be true.
03:23:58 So you end up navigating your own path
03:24:00 through this landscape.
03:24:02 And that can be thrilling
03:24:02 because you don’t know where it’s going.
03:24:05 And I’d like to think that that’s one of the reasons
03:24:07 my books have worked for people
03:24:09 because this sense of the thrilling adventure ride
03:24:12 that I don’t know where it’s going either.
03:24:14 So finding the simplest possible way
03:24:16 to explain the things we know
03:24:18 and the simplest possible way to explain
03:24:20 the things we don’t know
03:24:20 and the tension between those two.
03:24:22 And that’s where the story emerges.
03:24:25 What about the edit?
03:24:27 Do you find yourself to the point of this,
03:24:32 you know, editing down to mostly harmless?
03:24:36 To arrive at simplicity, do you find the edit is productive
03:24:40 or does it destroy the magic that was originally there?
03:24:44 No, I usually find, I think I’m perhaps a better editor
03:24:47 than I am a writer.
03:24:48 I write and rewrite and rewrite and rewrite.
03:24:51 Put a bunch of crap on the page first
03:24:52 and then see the edit where it takes you.
03:24:55 Yeah, but then there’s the professional editors
03:24:58 who come along as well.
03:24:59 And I mean, in Transformer, the editor came back to me
03:25:05 after I’d sent him, two months after I sent
03:25:07 the first edition, he’d read the whole thing
03:25:08 and he said, the first two chapters prevent
03:25:11 a formidable hurdle to the general reader.
03:25:14 Go and do something about it.
03:25:16 And that was the last thing I really wanted to do.
03:25:18 Your editor sounds very eloquent in speech.
03:25:21 Yeah, well, this was an email,
03:25:23 but I thought about it, you know,
03:25:26 the bottom line is he was right.
03:25:28 And so I put the whole thing aside for about two months,
03:25:33 spent the summer, this would have been,
03:25:35 I guess last summer, and then turned to it
03:25:38 with full attention in about September or something
03:25:40 and rewrote those chapters almost from scratch.
03:25:42 I kept some of the material,
03:25:44 but it took me a long time to process it,
03:25:47 to work out what needs to change, where does it need to,
03:25:49 I wasn’t writing in this time.
03:25:51 How am I going to tell this story better
03:25:53 so it’s more accessible and interesting?
03:25:54 And in the end, I think it worked.
03:25:56 It’s still difficult.
03:25:58 It’s still biochemistry, but it has,
03:26:00 he ended up saying, now he’s got a barreling energy to it.
03:26:03 And I was, you know, because he’d been,
03:26:05 because he’d told me the truth the first time,
03:26:07 I decided to believe that he was telling me the truth
03:26:08 the second time as well and was delighted.
03:26:13 Could you give advice to young people in general,
03:26:18 folks in high school, folks in college,
03:26:20 how to take on some of the big questions you’ve taken on?
03:26:23 Now you’ve done that in the space of biology
03:26:24 and expanded out.
03:26:26 How can they have a career they can be proud of
03:26:32 or have a life they can be proud of?
03:26:35 Gosh, that’s a big question.
03:26:40 I’m sure you’ve gathered some wisdom
03:26:42 that you can impart.
03:26:44 Yeah, so the only advice that I actually ever give
03:26:48 to my students is follow what you’re interested in
03:26:55 because they’re often worried
03:26:58 that if they make this decision now
03:26:59 and do this course instead of that course,
03:27:01 then they’re going to restrict their career opportunities
03:27:04 and there isn’t a career path in science.
03:27:08 It’s not, I mean, there is, but there isn’t.
03:27:12 There’s a lot of competition,
03:27:14 there’s a lot of death symbolically.
03:27:17 So who survives?
03:27:19 The people who survive are the people
03:27:20 who care enough to still do it.
03:27:25 And they’re very often the people
03:27:26 who don’t worry too much about the future
03:27:31 and are able to live in the present.
03:27:33 Because if you do a PhD,
03:27:35 you’ve competed hard to get onto the PhD,
03:27:37 then you have to compete hard to get a postdoc job
03:27:39 and you have the next one maybe on another continent
03:27:44 and it’s only two years anyway.
03:27:46 And so, and there’s no guarantee
03:27:49 you’re going to get a faculty position at the end of it.
03:27:52 So.
03:27:53 And there’s always the next step to compete.
03:27:54 If you get a faculty position,
03:27:56 you get a tenure and with tenure go full professor
03:27:59 and full professor, then you go to some kind of,
03:28:01 whatever the discipline is,
03:28:03 there’s an award.
03:28:04 If you’re in physics,
03:28:05 you’re always competing for the Nobel Prize.
03:28:06 There’s different awards.
03:28:08 And then eventually you’re all competing to,
03:28:11 I mean, there’s always a competition.
03:28:12 So there is no happiness.
03:28:13 Happiness does not lie.
03:28:14 If you’re looking into the future, yes.
03:28:16 And if what you’re caring about is a career,
03:28:18 then it’s probably not the one for you.
03:28:22 If though you can put that aside,
03:28:25 and I’ve also worked in industry for a brief period
03:28:28 and I was made redundant twice.
03:28:30 So I know that.
03:28:32 You know, there’s no guarantee
03:28:35 that you’ve got a career that way either.
03:28:37 Yes.
03:28:38 So, so live in the moment
03:28:42 and try and enjoy what you’re doing.
03:28:44 And that means really go to the,
03:28:48 go to the themes that you’re most interested in
03:28:50 and try and follow them as well as you can.
03:28:52 And that tends to pay back in surprising ways.
03:28:57 I don’t know if you’ve found this as well,
03:28:58 but I found that people will help you often.
03:29:04 If they see some light shining in the eye,
03:29:08 you’re excited about their subject
03:29:11 and you know, just want to talk about it.
03:29:15 And they know that their friend in California
03:29:18 has got a job coming up.
03:29:19 They’ll say, go for this, this guy’s all right.
03:29:21 You know, they’ll use the network to help you out
03:29:26 if you really care.
03:29:27 And you’re not gonna have a job two years down the line,
03:29:29 but if what you really care about is what you’re doing now,
03:29:32 then it doesn’t matter if you have a job
03:29:34 in two years time or not.
03:29:35 It’ll work itself out if you’ve got the light in your eye.
03:29:39 And so that’s the only advice I can give.
03:29:42 And most people probably drop out through that system
03:29:46 because the fight is just not worth it for them.
03:29:49 Yeah, when you have the light in your eye,
03:29:51 when you have the excitement for the thing,
03:29:53 what happens is you start to surround yourself with others
03:29:56 that are interested in that same thing,
03:29:57 that also have the light.
03:29:59 If you really are rigorous about this
03:30:01 because I think it does take, it doesn’t,
03:30:05 it takes effort to make.
03:30:07 Oh, you’ve got to be obsessive.
03:30:08 But if you’re doing what you really love doing,
03:30:11 then it’s not work anymore, it’s what you do.
03:30:13 Yeah, but I also mean the surrounding yourself
03:30:15 with other people that are obsessed about the same thing
03:30:17 because depending on.
03:30:19 Oh, that takes some work as well, yes.
03:30:21 And luck.
03:30:21 Finding the right, yeah, finding the right mentors,
03:30:23 the collaborators, because I think one of the problem
03:30:27 with the PhD process is people are not careful enough
03:30:32 in picking their mentors.
03:30:34 Those are people, mentors and colleagues and so on,
03:30:38 those are people who are gonna define
03:30:40 the direction of your life, how much you love a thing,
03:30:43 how much, I mean the power of just like
03:30:46 the few little conversations you have in the hallway,
03:30:51 it’s incredible.
03:30:52 So you have to be a little bit careful in that.
03:30:55 Sometimes you just get randomly almost assigned,
03:30:59 really pursue, I suppose, the subject
03:31:04 as much as you pursue the people that do that subject.
03:31:07 So like both, the whole dance of it.
03:31:09 They kind of go together really.
03:31:10 Yeah, they really do.
03:31:11 But take that part seriously.
03:31:14 And probably in the way you’re describing it,
03:31:19 careful how you define success.
03:31:21 Because.
03:31:22 You’ll never find happiness in success.
03:31:24 There’s a lovely quote from Robert Louis Stevenson,
03:31:27 I think, who said, nothing in life
03:31:29 is so disenchanting as attainment.
03:31:33 Yeah, so I mean, in some sense,
03:31:35 the true definition of success is getting to do today
03:31:42 what you really enjoy doing.
03:31:43 Just what fills you with joy.
03:31:46 And that’s ultimately success.
03:31:48 So success isn’t the thing beyond the horizon,
03:31:51 the big trophy, the financials.
03:31:54 I think it’s as close as we can get to happiness.
03:31:57 That’s not to say you’re full of joy all the time,
03:31:59 but it’s as close as we can get
03:32:01 to a sustained human happiness
03:32:03 is by getting some fulfillment
03:32:05 from what you’re doing on a daily basis.
03:32:06 And if what you’re looking for is the world
03:32:11 giving you the stamp of approval with a Nobel Prize
03:32:14 or a fellowship or whatever it is,
03:32:15 then I’ve known people like this who,
03:32:18 they’re eaten away by the anger,
03:32:24 the kind of caustic resentment
03:32:27 that they’ve not been awarded this prize that they deserve.
03:32:31 And the other way, if you put too much value
03:32:32 into those kinds of prizes and you win them,
03:32:35 I’ve gotten a chance to see that it also,
03:32:42 the more quote unquote successful you are in that sense,
03:32:45 the more you run the danger of growing ego
03:32:50 so big that you don’t get to actually enjoy
03:32:54 the beauty of this life.
03:32:56 You start to believe that you figured it all out
03:32:58 as opposed to, I think what ultimately
03:33:01 the most fun thing is is being curious
03:33:03 about everything around you, being constantly surprised,
03:33:06 and these little moments of discovery
03:33:08 of enjoying beauty in small and big ways all around you.
03:33:12 And I think the bigger your ego grows,
03:33:14 the more you start to take yourself seriously,
03:33:15 the less you’re able to enjoy that.
03:33:17 Amen to that, I couldn’t agree more.
03:33:20 So the summary from harmless to mostly harmless
03:33:25 in Hitchhiker’s Guide to the Galaxy,
03:33:27 how would you try to summarize Earth?
03:33:31 And if you were given,
03:33:34 if you had to summarize the whole thing
03:33:36 in a couple of sentences,
03:33:38 and maybe throw in meaning of life in there,
03:33:40 like what, why, why, why, maybe,
03:33:45 is that a defining thing about humans
03:33:47 that we care about the meaning of the whole thing?
03:33:52 I wonder if that should be part of the,
03:33:55 these creatures seem to be very lost.
03:33:58 Yes, they’re always asking why.
03:34:00 I mean, that’s my defining question is why.
03:34:02 It was, as people used to make a joke,
03:34:06 I have a small scar on my forehead
03:34:08 from a climbing accident years ago.
03:34:11 And the guy I was climbing with had dislodged a rock
03:34:13 and he shouted something.
03:34:15 He shouted below, I think,
03:34:16 meaning that the rock was coming down.
03:34:18 And I hadn’t caught what he said,
03:34:20 so I looked up and then smashed the street on my forehead.
03:34:23 And everybody around me took the piss,
03:34:27 saying he looked up to ask why.
03:34:30 Yeah.
03:34:33 But that’s a human imperative.
03:34:34 That’s part of what it means to be human.
03:34:37 Look up to the sky and ask why, and ask why.
03:34:42 So your question, define the earth.
03:34:49 I’m not sure I can do that.
03:34:50 I mean, the first word that comes to mind is living.
03:34:54 I wouldn’t like to say mostly living, but perhaps.
03:34:57 Mostly living.
03:34:58 Well, it’s interesting because like,
03:35:00 if you were to write the Hitchhiker’s Guide to the Galaxy,
03:35:04 I suppose, say our idea that we talked about,
03:35:10 that bacteria is the most prominent form of life
03:35:13 throughout the galaxy and the universe.
03:35:17 I suppose that earth would be kind of unique
03:35:21 and would require.
03:35:22 There’s abundance in that case.
03:35:24 Yeah.
03:35:25 It’s profligate, it’s rich, it’s enormously,
03:35:28 enormously living.
03:35:29 So how would you describe that it’s not bacteria?
03:35:33 It’s.
03:35:36 Eukaryotic.
03:35:37 Yeah.
03:35:39 Well, I mean, that’s the technical term,
03:35:41 but it is basically it’s.
03:35:46 Yeah, and then.
03:35:47 How would I describe that?
03:35:49 I’ve actually really struggled with that term
03:35:52 because the word, I mean, there’s few words
03:35:55 quite as good as eukaryotic to put everybody off immediately.
03:35:58 You start using words like that
03:35:59 and they’ll leave the room.
03:36:01 A Krebs cycle is another one that gets people
03:36:03 to leave the room, but so I’ve tried to think,
03:36:08 is there another word for eukaryotic that I can use?
03:36:10 And really the only word that I’ve been able to use
03:36:13 is complex, complex cells, complex life and so on.
03:36:18 And that word, it serves one immediate purpose,
03:36:22 which is to convey an impression.
03:36:26 But then it means so many different things to everybody
03:36:31 that actually is lost immediately.
03:36:33 And so it’s kind of.
03:36:36 Well, that’s a noticeable from the perspective
03:36:38 of other planets, that is a noticeable phase transition
03:36:42 of complexity is the eukaryotic.
03:36:46 What about the harmless and the mostly harmless?
03:36:49 Is that kind of.
03:36:51 Probably accurate on a universal kind of scale.
03:36:55 I don’t think that humanity is in any danger
03:36:59 of disturbing the universe at the moment.
03:37:02 At the moment, which is why the mostly, we don’t know.
03:37:06 Depends what Elon is up to, depends how many rockets.
03:37:10 I think.
03:37:10 It’ll be still even then a while, I think,
03:37:13 before we disturb the fabric of time and space.
03:37:17 Was the aforementioned Andrej Karpathy,
03:37:20 I think he summarized Earth as a system
03:37:25 where you hammer it with a bunch of photons.
03:37:30 The input is like photons and the output is rockets.
03:37:35 If you just.
03:37:37 Well, that’s a hell of a lot of photons
03:37:38 before there was a rocket launch.
03:37:40 But like, you know, maybe in the span of the universe,
03:37:43 it’s not that much time.
03:37:46 And so, and I do wonder, you know, what the future is,
03:37:49 whether we’re just in the early beginnings of this Earth,
03:37:52 which is important when you try to summarize it,
03:37:55 or we’re at the end, where humans have finally
03:37:59 gained the ability to destroy the entirety
03:38:02 of this beautiful project we’ve got going on.
03:38:06 Not with nuclear weapons, with engineered viruses,
03:38:09 with all those kinds of things.
03:38:10 Or just inadvertently through global warming
03:38:12 and pollution and so on.
03:38:15 We’re quite capable of that.
03:38:15 I mean, we just need to pass the tipping point.
03:38:18 I mean, I think we’re more likely to do it inadvertently
03:38:20 than through a nuclear war, which could happen at any time.
03:38:24 But my fear is we just don’t know
03:38:30 where the tipping points are.
03:38:31 And we will, we kind of think we’re smart enough
03:38:35 to fix the problem quickly if we really need to.
03:38:37 I think that’s the overriding assumption
03:38:40 that we’re all right for now.
03:38:43 Maybe in 20 years time, it’s gonna be a calamitous problem.
03:38:45 And then we’ll really need to put some serious mental power
03:38:47 into fixing it without seriously worrying
03:38:51 that perhaps that is too late.
03:38:53 And that however brilliant we are, we miss the boat.
03:38:59 And just walk off the cliff.
03:39:01 I don’t know.
03:39:02 I have optimism in humans being clever descendants.
03:39:05 Oh, I have no doubt that we can fix the problem.
03:39:09 It’s an urgent problem.
03:39:11 We need to fix it pretty sharpish.
03:39:14 And I do have doubts about whether politically
03:39:16 we are capable of coming together enough
03:39:18 to not just in any one country, but around the planet.
03:39:23 To, I mean, I know we can do it, but do we have the will?
03:39:26 Do we have the vision to accomplish it?
03:39:31 That’s what makes this whole ride fun.
03:39:33 I don’t know.
03:39:35 Not only do we not know if we can handle
03:39:37 the crises before us, we don’t even know all the crises
03:39:40 that are gonna be before us in the next 20 years.
03:39:43 The ones I think that will most likely challenge us
03:39:48 in the 21st century are the ones we don’t even expect.
03:39:51 People didn’t expect World War II
03:39:53 at the end of World War I.
03:39:56 Some folks did, but yeah, not at the end of World War I.
03:39:58 But by the late 1920s, I think people
03:40:01 were beginning to worry about it.
03:40:03 Yeah, no, there’s always people worrying about everything.
03:40:05 So if you focus on the thing that.
03:40:08 People worry about, yes.
03:40:09 Because there’s a million things people worry about
03:40:11 and 99.999999% of them don’t come to be.
03:40:14 Of course, the people that turn out to be right,
03:40:16 they’ll say, I knew all along, but that’s not,
03:40:19 that’s not an accurate way of knowing
03:40:21 what you could have predicted.
03:40:22 I think rationally speaking, you can worry about it,
03:40:25 but nobody thought you could have another World War.
03:40:28 The war to end all wars, why would you have another war?
03:40:31 And the idea of nuclear weapons,
03:40:34 just technologically, is a very difficult thing
03:40:37 to anticipate, to create a weapon
03:40:39 that just jumps orders of magnitude
03:40:41 and destructive capability.
03:40:43 And of course, we can intuit all the things
03:40:46 like engineered viruses, nanobots,
03:40:49 artificial intelligence, yes, all the different
03:40:54 complicated global effects of global warming.
03:40:57 So how that changes the allocation of resources,
03:40:59 the flow of energy, the tension between countries,
03:41:02 the military conflict between countries,
03:41:04 the reallocation of power,
03:41:06 then looking at the role of China in this whole thing
03:41:09 with Russia and growing influence of Africa
03:41:13 and the weird dynamics of Europe,
03:41:16 and then America falling apart through the political
03:41:19 division fueled by recommender systems
03:41:22 through Twitter and Facebook.
03:41:24 The whole beautiful mess is just fun.
03:41:26 And I think there’s a lot of incredible engineers,
03:41:30 incredible scientists, incredible human beings
03:41:32 that while everyone is bickering and so on online
03:41:36 for the fun of it on the weekends,
03:41:37 they’re actually trying to build solutions.
03:41:39 And those are the people that will create
03:41:41 something beautiful.
03:41:42 At least I have, that’s the process of evolution.
03:41:45 It all started with a Chuck Norris single cell organism
03:41:53 that went out from the vents and was the parent
03:41:56 to all of us.
03:41:57 And for that guy or lady or both, I guess,
03:42:01 is a big thank you and I can’t wait to what happens next.
03:42:05 And I’m glad there’s incredible humans writing
03:42:08 and studying it like you are, Nick.
03:42:10 It’s a huge honor that you would talk to me.
03:42:12 This is fantastic.
03:42:13 This is really amazing.
03:42:14 I can’t wait to read what you write next.
03:42:17 Thank you for existing.
03:42:21 And thank you for talking today.
03:42:24 Thank you.
03:42:26 Thanks for listening to this conversation with Nick Lane.
03:42:28 To support this podcast, please check out our sponsors
03:42:31 in the description.
03:42:32 And now let me leave you with some words from Steve Jobs.
03:42:37 I think the biggest innovations of the 21st century
03:42:40 will be at the intersection of biology and technology.
03:42:45 A new era is beginning.
03:42:47 Thank you for listening and hope to see you next time.