Episode 21: Evolution Outside the Genome
- Links to this episode: Spotify / Apple Podcasts
- This transcript was generated with AI using PodcastTranscriptor.
- Unofficial AI-generated transcripts. These may contain mistakes. Please check against the actual podcast.
- Speakers are denoted as color names.
Transcript
[00:00:11] Blue: Welcome to the theory of anything podcast. How’s it going cameo? It is going great Bruce. How are you? I’m doing fairly well. We were just discussing that. I’m a little bit of pain, but I sometimes have to go through painful moments because of I’ve got a bit of arthritis and that’s actually relevant to today’s discussion. I’m kind of excited to talk about it the thing that kind of led up to this was I had come across somebody I’m kind of on Twitter put this up on their Twitter feed and I looked at it. It’s a TED Talk. TED Talk came out a few days ago it’s by Michael Levine and it’s called the Electrical Blueprints that orchestrate life and I got really excited when I watched it. I went back and I did some research afterwards and it looks like a lot of these ideas are things he’s been putting out there for a couple years. So it isn’t the TED Talk was brand new and I think it was going to a larger audience for the first time but it’s clear he’s actually been kind of trying to advertise his research for a couple years and so perhaps this isn’t like some sort of immediate breakthrough but it’s just starting to get out into the media and people are starting to find out about it and it’s kind of an exciting interesting breakthrough that he’s come up with. So I sent it over to Camille and then Camille what was your reaction?
[00:01:37] Red: Well, it’s very very fascinating. I watched it and then read the transcript and then talked about it with my husband and it’s very interesting because it does talk about the potential for being able to leverage these electrical blueprints that we’re going to talk about here to really change what happens for us at the cellular level but I also think it has some really interesting implications across maybe some intelligent design concepts like where do these blueprints come from? How are they part of our cellular makeup and what does it mean for kind of our place within the universe?
[00:02:18] Blue: Yes. Okay so let’s talk about that because just by coincidence I had actually been reading a paper and the paper is called Was the Watchmaker Blind or Was She One -Eyed? And it’s by Raymond Noble and Denise Noble. I assume they’re related in some way. It’s a really interesting paper. I actually highly recommend that people go read this particularly if they’re fans of neo -darwinism because the paper I want to be careful how I say this in a sense it refutes neo -darwinism. Really it only refutes a certain original formulation of neo -darwinism probably not its current formulation but I think a lot of people would be very interested in what it has to say about classical neo -darwinism. So I actually when I was reading this paper I got really excited because it tied into another paper I had been reading by Donald Campbell who was talking about the hierarchy of evolutionary processes and it was a direct relationship to that article which is a much older article back from the era of Karl Popper himself. Suddenly I see Michael Levine’s work and I’m realizing this is like a really solid example of what they’re talking about more solid than the ones that were in the papers themselves and so that I want to kind of tie all three of these ideas together of these papers together and talk about how they relate. So to do that let me first explain to you what the was the watchmaker blind or was she one -eyed what it’s about and then I’ll explain how it kind of ties in. They claim in the paper that neo -darwinian theory usually assumes all knowledge is held either in the genome or it’s in the mind or nervous system.
[00:04:08] Blue: So neo -darwinians would admit there is a source of knowledge outside of the genome that’s in human minds or for that matter in animal minds. You know you can classically condition a dog it can learn to beg for a treat that’s not something that anybody believes is knowledge in the genome. Classically they’ve tended to assume it’s either one of the two the knowledge either resides in the genome or it resides in the mind and that’s it. Modernly maybe not all of them believe that these theories kind of mutate over time they quote evolve over time. You could easily make the argument that modern neo -darwinian theory doesn’t make that claim however the authors of the article they give examples of where that is the assumption. So clearly at least in the past neo -darwinian theory has had this assumption that there’s really only two sources of information the genes of the mind and there’s been it’s been kind of at least tacitly assumed from the way they speak and the way they talk sometimes not tacitly assumed sometimes directly stated. So for example they quote Richard Dawkins he says in real life the criteria for selection is always short term either simple survival or more generally reproductive success. So Dawkins is making the claim there is no theology no purposefulness in evolution and this is this is something you will hear over and over again from neo -darwinians that that evolution has no purposefulness.
[00:05:40] Blue: Now again they know there’s at least one exception like if humans go out and breed dogs there’s clearly purposefulness in evolution at that point and they wouldn’t deny that but they do tend to assume that that’s the one exception and what this paper is saying is no that’s actually not the only exception that there’s actually many many many exceptions at many different levels of the evolutionary hierarchy which we’ll talk about what that is in just a second. They go on to say classical neo -darwinism was formulated by August Weisman and others in the late 19th century to expunge the inheritance of acquired characteristics from Darwin’s theory. Blind variation followed by natural selection was claimed to be entirely sufficient. Okay then they admit that it’s been redefined since then so that’s not necessarily true of everyone who would call themselves a neo -darwinian today but then they go refining a term does not however change the fact that the original theory using that term is no longer the complete story. Our position can therefore to some degree be seen to return to Darwin’s multi -mechanism viewpoint through though with vastly extended empirical evidence.
[00:06:47] Blue: So they’re setting themselves up at least as saying okay neo -darwinian theory at least classically has thought of things as genes are sort of a gene -centric view of the world and I think you’ll see just as a layman yourself that you certainly kind of had in your mind this idea that there’s all this knowledge in the genes and you really haven’t ever thought too much about where knowledge might else reside besides the genes or the mind precisely because neo -darwinian theory has kind of gotten out into the culture and it has sort of been imbibed in that way even though it’s not entirely accurate. Does that make sense so far are you following me?
[00:07:31] Red: Yeah and I think you’re right like one of the things the way they teach things like DNA in school is here’s all of the information that’s going to make up the person that you are it’s it’s this combination of these building blocks at the cellular level.
[00:07:47] Blue: Right and that’s not entirely untrue right it’s you have to kind of just understand that the nuance that’s being suggested here they go on to say in the paper genomes and phenotypes are far from being equivalent the mismatch works both ways the same genome can be used to generate many different phenotypes and the same phenotype can involve through many different genome variations to such an extent that the sequence variations may even be unpredictable. Okay so they’re trying to get the idea across that evolution actually works on the phenotype when I say phenotype that’s the actual body or organism that gets produced right
[00:08:25] Red: that’s what
[00:08:26] Blue: evolution actually works on it doesn’t directly impact the genes only indirectly insofar as the genes helped create the phenotype but once you realize that the phenotype actually is impacted by many different things not just the genes then you start to understand that evolution is going to be impacting all the inputs to the phenotype not just the genes. Right okay so now they go on and they they define something called natural purposeiveness they’re trying to make this not sound too much like intelligent design or something like that because it isn’t it’s it’s it’s still a very natural process that they’re talking about but they’re saying the gene -centric view of evolution are incorrect evolution is a high -level forming process not simply a matter of genome informatics it is rather the development of the conceptual interpretation of the process of evolution that differs from neo -darwinism in implementing the principle that there is no privileged level of causation we believe this is the novel concept conceptual advance that that they’re making it differs radically from views of evolution that privileged the role of DNA sequences in the intergenerational transmission of inheritance now when I say this you can probably think of exceptions because we’re starting to hear about exceptions everybody kind of knows about epigenetics now and epigenetics is a non -genetic form of knowledge that gets transmitted and they mention this in their article and they give another example and this this first example is a really good example but it’s it’s a well -known one though so the immune system you think about how the immune system works the immune system doesn’t come with knowledge of every single possible pathogen and how to stop it
[00:10:14] Red: what
[00:10:15] Blue: it actually does is it comes with a learning algorithm right absolutely what the learning algorithm says to do is it says okay so remember your DNA it’s in every single cell in your body and so the the the cells that are going to produce the antibodies they use DNA the algorithm that they have says oh look we’re invaded let’s hyper mutate our DNA but only in this one area that affects the antibodies nothing else because that would break us and so it starts going through hyper mutation of its own DNA and it then produces these antibodies that have random components to them that then go out and the ones that are successful are the ones that then start to get replicated and that’s then the ones that aren’t successful they just kind of die off based on that you wind up with an immune system which is able to not have to have knowledge in it from the beginning about how to fight every pathogen but instead can generate that knowledge for how to fight the pathogen in real time without having to you know give birth to another generation of puppies or something and so again this is something that’s well known right and so it’s interesting that this hasn’t really people haven’t really understood this is an example of how the genetic view of evolution isn’t really quite right even though we knew it wasn’t quite right the full implications of it haven’t been thought through all the way if they’re
[00:11:55] Red: right
[00:11:55] Blue: this is then an example of how in this case we’re still using DNA you don’t have to use DNA and that’s that’s what we’re doing in this case
[00:12:07] Blue: the DNA has a learning algorithm that tells itself how to modify itself the other example they give in in the paper is jumping genes apparently it was discovered before they had actually like sequenced the genome they had discovered that you know quote working with indian corn this researcher showed that in response to stress genetic material can move around between different chromosomes they had discovered that the genes in chromosomes could hop from chromosome to chromosome if the genetic material was under stress to try to protect itself at least at the time they didn’t have any idea how it was doing it how was it detecting that there was a stress that there was a problem how was it then knowing to try to take that gene and go relocate it somewhere else that’s not under stress and yet this is again a clear example of how the strict genomic info informatics view of evolution isn’t correct right that somehow the genes had some sort of learning algorithm that they had instantiated that allowed it to move their genes so they didn’t have to stay static to try to protect themselves okay and again we’re still dealing with genes here but in a way that’s at a different level of hierarchy so now what’s this idea of a hierarchy well this is actually an idea that dates back to probably before donald campbell but he’s the quite well so donald campbell was a huge fan of carl popper who obviously inspired a lot of this podcast and donald campbell came to this realization apparently at the same time as popper but he he published first and popper was still in the middle of writing his stuff according according to popper and he said oh hey um it seems to me so carl popper’s theory is this idea that evolution applies at the level of human ideas and at the level of science and so he’s taken this idea of evolution which at the time was understood as survival of the fittest that’s probably not the best way to describe i’ve taken some criticism over calling it that because that brings to mind kind of a false view of evolution that the strongest animal survives or something like that it’s really the fittest at doing replicating itself well and and error correcting yeah well actually error correcting is relative are we talking about the gene or we’re talking about the organism and those aren’t the same i know but we’re talking about the organism itself yeah campbell says you know what it’s it’s not just that evolution applies at the level of biology or human ideas but it’s it applies all over the place it’s there’s actually this it’s a generally applied principle that happens in a hierarchy and so first he had this meant this idea that it happens in a hierarchy okay so he goes human knowledge processes when examined in continuity with the evolutionary sequence turn out to involve numerous mechanisms at various levels hierarchically related and with some form of selective retention process at each level he gives examples of this for human knowledge he gives examples of how we might think about how our actions might impact others and then edit our actions before we actually have to go try our action out and then find out how they how they how people react badly to us okay and that’s that’s like a different level of evolution than you know the other levels we’ve talked about but it also might be it might also be that the very fact that you see something you don’t even have to think about it but you immediately decide to do something different that’s a that’s itself the seeing substitutes for you having to go move or act because people to see so he argues that’s a different levels from the human ideas level and yet it’s still a level of evolution that’s taking place okay interesting so then after pointing out that that popper’s theory applies or evolutionary theory I should say applies at all these different levels he points out that it’s also outside of human knowledge he says turning to higher levels the model can be applied to such dramatically teleological achievements this is an important word here as embryological growth and wound healing he goes on to explain that the way a leg grows back on a salamander is not something that’s determined by the genes directly but there’s there’s kind of a an algorithm that represents what environment it thinks the salamander is going to be in and then detects when to stop growing that leg okay now you can see how this directly relates to Michael Levine’s
[00:16:59] Blue: so he talks to Campbell talks about this and then he says the different levels of hierarchy in evolution they relate to each other so if I have if I let’s say that I produce some knowledge at one level in the hierarchy that knowledge can then be used as a heuristic at the next level down in the hierarchy so that it doesn’t have to search so far to be able to find variants anymore okay okay so that’s intriguing now what that means is is that evolution is teleological it means it’s purposeful not ultimately now Campbell points this out every single thing that in evolution has purpose itself at some point otherwise it would be an infinite regress has to have just been blind variation at some point right so but once you’ve evolved that learning algorithm and the new level of the hierarchy it can be purposeful from that point forward okay now this is actually the point Raymond Noble and Denise Noble are trying to make okay they’re trying to say there’s this natural purposeness in evolution because there is no privileged level of causation in evolution so once you’ve evolved a learning algorithm it then can evolve according to a purpose and what they’re saying is is that this is far more important to how evolution actually works than what the classical neo Darwinist Darwinian version of evolution seems to imply because evolution itself this is quoting them evolution itself evolves because you’re actually evolving purposes that then in turn evolve from there which think of it as like targeting in on what you want want to evolve and so you’ve now constrained or narrowed what you have to select between
[00:18:51] Red: sure it’s it’s it’s a pretty intriguing concept yeah okay would you ultimately make so much sense that how could it be any other way because I agree because how could you have a system designed to constantly adapt if could if the system itself couldn’t adapt itself right
[00:19:16] Blue: okay so now how does this relate to Michael Levine’s stuff so let’s let’s maybe let’s just describe what is in the TED talk I highly we’ll put a link in the show notes I highly encourage people to just go watch it and see for themselves and this is the typical warning we’re not experts we’re just laymen that are interested we’re doing our best to describe what we saw and we’re doing our best to understand it and we’re likely wrong on all sorts of things and you know what we don’t even apologize it’s just the way it is you don’t need to completely understand the subject to start talking about it and to start interacting with it you should if you had to do that no one could talk about anything right no right
[00:19:59] Red: life would be pretty boring then
[00:20:00] Blue: right I want to get away from the idea that I have to be an expert to talk about this I do I am not an expert and I’m going to talk about it and go go look into it for yourself if you disagree with our interpretation and quite frankly we’re probably mangling it for all I know right okay so actually cameo what why don’t you describe what what were the things that you found most interesting in the TED talk that he brings up the
[00:20:28] Red: well one of the things that’s very intriguing is that the way they were able to to isolate the electrical signal or watch the electrical messaging happening between the cells or almost to the cells that I don’t know if I could say I believe the cells were talking to each other it’s more like the he’s he’s describing a set of instructions that are being applied across the cellular level through the electrical signals so
[00:21:06] Blue: interestingly Dan Elton who on the front of mind on twitter who’s a phd that was the thing he found if I’m understanding Dan correctly the thing he found the most maybe misleading oh interesting he felt that Levine was making it sound too much like the cells were intelligent and talking to each other and he felt like that wasn’t really the truth and I don’t want to put words into Dan’s mouth either maybe I’m misunderstanding Dan but the way you just said that I think is accurate right there’s communication going on that’s probably been known for a while that there’s communication between cells I think the thing that I didn’t realize is that that communication is what determines what the phenotype is so the genes may give the knowledge to the operating system think of it as like a software operating system that there’s this electrical operating biological operating system that runs between the cells that itself contains knowledge the genes may tell it how to instantiate that learning algorithm so that the knowledge in that sense comes from the genes but it’s a but it is what actually forms the phenotype not the genes directly for example by giving a signal to you know frogs or tadpoles they could say grow extra legs and suddenly the you’ll have this tadpole with growing these extra legs going into a frog with six legs or something like that right all without ever editing the genes right
[00:22:39] Red: no no manipulation at the genetic level at all
[00:22:42] Blue: yeah and then the one that was really cool was the flatworm now flatworms don’t sexually reproduce they reproduce by splitting but they they split the the flatworm in half and then told it to grow back with two heads and so you have these flatworms that have a head on each side and when you and then after that every time you split it it always grows back with two heads until you reprogram the operating system again because that is now its phenotype is now the information on how to form its phenotype is now in that the the communication the biological signals in the cells and so even though the genes haven’t been changed you get this vastly different phenotype exactly like Raymond Noble and Denise Noble were explaining that that uh the the genes do not ultimately determine the phenotype by themselves right okay so that was a beautiful example of what the article was talking about and now I are you familiar with CRISPR you’ve probably heard about CRISPR right yeah sure so CRISPR is this very cool technology that has a lot of promise that they’re going to be able to put things into the body that change our DNA so if you have a genetic disease you know arthritis genetic disease they can someday inject me with something that will say okay stop you know that gene is let’s inject you with a different gene it’ll replace throughout my body and I’ll end up being healed uh -huh the disease right that’s very cool the fact that they can do that at all is amazing but what the what’s Levin is saying is that’s more complicated than it needs to be right is that actually we can figure out how to just simply tell the cells in your body here use a different electrical signal here’s the different software statements that you need using an analogy here but it’s not that far off because it is software we’re talking about and my cells will automatically without ever having to use CRISPR to change my genes will automatically know don’t do arthritis just stop
[00:24:56] Blue: just stop stop doing that that that’s silly yeah presumably it’s it’s caused by there’s different things that can cause arthritis that’s kind of a general term but what I have in mind here is like some sort of immune thing where your body’s reacting too strongly when it doesn’t need to right you know or like allergies or something along those lines where you have some sort of response you can just tell your body stop don’t don’t do that anymore there’s not even a need to change the genes the the individual cells will simply perpetuate that information at the cellular level without having to have a gene change which presumably is cheaper and easier and less scary and it’s just it seems like it would be a fairly substantial breakthrough if we could actually use this like that
[00:25:44] Red: right if we could figure out how to well how to speak the how to isolate and speak the language of that electrical signal and how to make sure that we’re applying the right essentially reprogramming you know I I think about it almost as a firmware update yes
[00:26:04] Blue: it’s like a firmware update yes yes a body firmware update I mean conceptually yes it seems a little bit better to do a firmware update than to you know have to completely replace the hardware at the genetic level it’s it’s a very fascinating you know and so much of when our bodies start to fall apart it’s it’s cellular failure failure cancer you know auto immune disease allergies those things aging you know it’s our cells stop doing the right things it’s interesting that he actually talks about that really briefly like you almost miss it in the TED talk but he basically in strongly implies actually using these biological signals we can we’re going to learn to be able to just tell your cells to stop aging right you know we’re going to be able to learn to just tell your cells to go heal when to stop when to start healing when to stop healing to avoid cancer you’re going to tell your cells hey stop that cancer that’s the wrong thing to do that’s very exciting right that there’s lots of potential here that’s huge that comes from understanding what this biological language is that they’re researching
[00:27:18] Red: so you say he’s been talking about these this this concept maybe for a while yeah like all right he’s he’s discovered this very cool thing is he is he struggling getting to pay get people to pay attention to it is there you know there’s always a huge gap between concept and like how did we actually turn this into a treatment I can go have you know like I could go have a you know an oxygen treatment that’s going to promise XYZ thing you know how can I go have a a cellular reboot treatment that will you know and and how can I as an entrepreneur build you know a spa where somebody can go and have a cellular treatment that will apply some electrical signals to their cellular makeup yeah
[00:28:10] Blue: good good question you know I don’t know the answer to that question right because there is a world of difference between some professor you know somewhere doing research with worms yeah with worms and then someone actually getting excited enough about the potential to make money with it that they put up money to go try to turn this into an actual treatment and as far as I can tell no one’s even attempting to do that at this point right what do I know maybe maybe there’s talks going on behind the scenes or something right I don’t know that he would announce that if he was had a deal in the works
[00:28:48] Red: no but I like there is there’s a really really big gap on you know he might not well he probably is not even the type of scientist who could figure that out right I mean he’s he does a thing and he’s got a thing like that it’s it’s a whole different ball of wax to figure out it is and and talk about a money well you know you could spend you could spend multiple people’s careers trying to solve that problem yeah
[00:29:21] Blue: so here’s something I found interesting about this so he do you remember the part about the Picasso frogs mm -hmm so in tadpoles they’ll take the tadpole and they’ll force it to develop where the eyes are in the wrong spot or something like that right right with the Picasso tadpole painting yeah then it develops into a frog and it still turns into a normal frog face and the reason why and he uses the word error correction this is one of the things that caught my attention is because the this operating system we’re talking about this biological operating system it does error correction it says oh how do I it doesn’t have direct program instructions take this eye and move it here when you when you turn a tadpole into a frog instead it understands what the goal is here’s another example of goal oriented evolution right and an error corrects towards that goal so this is a really strong indicator this operating system we probably could have predicted this but we’ll get a call it out that it is a learning algorithm right that it’s it has in it various types of means by which it can evolve solutions to problems purposefully it can right it says I want the frog to have a face that looks like a normal frogs and so I’m going to figure out how to error correct to get into the right spot so this is a really good example of both what Campbell and and the nobles are talking about where it seems like now I’m making some assumptions here that may not be true but it seems like we’re talking about some form of evolution that’s taking place outside the genome but not in the human not in a mind either
[00:31:04] Red: I that was the implication I took away also okay
[00:31:09] Blue: anytime you say the word error correction that seems like what you’re talking about although words are just words he might have something else in mind and I’m missing misinterpreting but yeah I thought that was very interesting so it’d be interesting if you could then give new program instructions I don’t know if this is possible or not as I don’t understand the technology and you could you could give it something more sophisticated how to not create cancer but also not age because one of one of the one of the theories that’s out there is that cancer is the natural outcome of aging is the way the body stops cancer is basically the theory the idea is is that cells are programmed to die after a certain number of generations so they don’t become cancerous it’s not too hard to change the cells so that they don’t age by having longer telomeres but if you do that then you’ll die of cancer instead evolution if this theory is true I don’t know if it’s true or not but if this theory is true that would seem to indicate that evolution could not find had to find a sweet spot between cancer and aging so what we would really want is neither we would want something that’s more sophisticated than that that aligns
[00:32:26] Red: reaction to that is well then why the hell do kids get cancer so much
[00:32:33] Blue: keep in mind that it’s at the cell level I know but yes it’s
[00:32:38] Red: I that it just seems like a cop out
[00:32:41] Blue: all right fair enough but it should still be a soluble problem either way
[00:32:47] Red: yes I agree
[00:32:48] Blue: and that might even be something where how do I explain what I’m thinking here and I’m grasping here and I admit but the gene it seems like genes are more rigid they’ve evolved they’re messy they have to work in certain ways this seemed almost more like it was it was easier to reprogram to give it new instructions that the genes never would have conceived of
[00:33:12] Red: well and you know in a way like if if you look at it it is easier to apply to have kind of a firmware infrastructure where you can have a piece of hardware that you can continually update with new information that will allow as you are learning things and adapting to things you can go back within the confines of the original hardware and apply a new set of instructions that is a more adaptable way to build things and a way to build things faster and kind of more componentized you know but building in more components makes things be able to to grow and change better maybe at the end of the day it’s the only way that something you know that you need at both a hardware component that is the genome and then a software component that is this electrical thing that has maybe always been there and we just didn’t understand that it was happening
[00:34:13] Blue: anyhow very interesting presentation and at least it surprised me you know maybe other people have more knowledge of this and this isn’t as big a breakthrough as it first appears to me but it seemed like this was kind of a big deal and I really hope that more people will discover about this work and you know even if it is not quite right error correction will take place right well the parts will will filter through and the parts that are maybe exaggerated won’t and will end up with something that is that is useful here
[00:34:46] Red: yes because I mean well very few things are so completely wrong like you know like co -fusion where as you dig into the science
[00:34:56] Blue: maybe there wasn’t anything there you
[00:34:59] Red: know and so like you say there’s probably elements of correctness and elements of error correction that will happen that that will start to and maybe none of it in our lifetimes sadly but maybe so I don’t know
[00:35:15] Blue: yeah you know that’s that’s the most frustrating thing to me is how long it takes to take these ideas I mean like do you remember a while back probably decades ago now they there was a news article that went around about these mice that they had engineered that could regrow limbs this sure do you do at the time I had the thought oh wow I wonder like I wonder if what if they turn that into something that’s medical right where you could like regrow a finger or something right amazing if they could do that right but that was decades ago and far as I know no one’s even working on that as a medical technology right to be able to regrow things right and yet there’s no particular reason why you shouldn’t be able to right I mean it’s we know that that’s a perfectly normal thing to for an organ for some organisms to do it’s it’s not I mean like you know the lizard you cut off its tail and it grows a new tail right and it’s regrowing limbs isn’t an impossibility that the it just just so happens that with the more complex and organisms like ourselves it’s not the most useful thing to do evolutionarily but it would be really useful to us right I mean like if if someone who lost a limb could regrow it that would be amazing that seems like that would be something we would we would want and then it seems like that might even have like they didn’t know at the time if the mouse would live a longer life or not but it seems like it
[00:36:45] Red: would
[00:36:45] Blue: right if you’ve got this super regenerating mouse why wouldn’t it live a longer life it seems like a lot of these ideas you hear about them they come out and then yes they’ll probably eventually turn into something you know they go they go into the knowledge in the background somewhere right but they’re not going to they don’t happen fast enough to actually do me any good
[00:37:08] Red: so part of that I think is because of the way that theoretical things and research things are funded where you have you know individual people who develop interest or specialty within a field and start to come up with concepts and want to pursue concepts but you know academia is funded the way it’s funded and it’s publisher perish and it’s there are probably ways that that money flows through through research in general that really keep in a way probably breakthroughs from happening and collaboration a little bit maybe it’s better than it used to be because you have people able to with with the rise of the internet across the world you have the ability for like people to find each other and start to kind of build off each other’s knowledge but then there’s also still kind of protective competitiveness within research where people don’t want to I don’t know that people are necessarily trying to solve the world’s problems you know that’s not really what we’re doing yet
[00:38:16] Blue: we’re yeah
[00:38:18] Red: you know and and and coming back to my statement about la vie not probably knowing how to turn this into something that’s a sellable he’s a research scientist who’s good at you know tracking and watching worms and you know seeing what what is a path from a kind of r &d standpoint from where he is at to something even conceptual that you could test on a mouse or test on a you know that’s that’s a big path with a lot of science between it you know yeah and if you could if you could leverage you know if you were the head the research scientist headed a big university that had a whole a whole you know maybe I don’t know you almost would need to develop a new branch of science with people I think it’s just hard for us to build big complicated things because the problem is big and complicated so
[00:39:20] Blue: there’s several things here that you just said that probably could be an episode in and of themselves one of them is that we split up knowledge into buckets uh -huh right we there’s the biology department and there’s the physics department and there’s the chemistry department and there’s no real there’s no they’re not set up they’re they’re set up to be to make it easy to teach and easy to administrate and not really they’re not really set up to make it easy to share knowledge between these different areas
[00:39:55] Red: yeah
[00:39:56] Blue: that knowledge doesn’t fit into buckets in real life right these are completely arbitrary categories and i’m not against this right i’ve seen some people get like upset over this and i’m not the need to administrate things is a real need right yeah real the need to make things so that we can make it easy to have certain types of classes is a real need there really is a lack of sharing and of knowledge between the different buckets between the different areas of knowledge and that’s where the breakthroughs come from right is is when you you’ve got people who are thinking outside the box because they come from a different area but i shouldn’t say it’s not like all breakthroughs come that way but that’s a really common way for breakthroughs to happen so clearly there’s something to this idea that what you really want is you want to respect the fact that knowledge knows no boundaries right and and then we do that and then we do that at several levels it’s not just that at a university we split things up into departments but we understand there to be a difference between a research scientist and business right you know and there’s all sorts of different levels where we have these kind of artificial barriers well
[00:41:09] Red: and we then and to your point we seem to think of of problems as having a very you know it’s it’s the right brothers inventing the airplane all sorts of people who specialized in this concept of flight we’re working really really hard at this problem you know a lot of people were do were really focused on how can we break through and actually get ourselves into the air and it took people who knew nothing about that and and kind of had had their own set of physics and their own understanding of the world to come in and and not just break through but figure out execution on on a concept so
[00:41:47] Blue: actually the right brothers is a really interesting example so we typically say the right brothers invented the airplane and from a certain point of view that is true but there were airplanes before the right brothers they there were people before the right brothers that had created flying machines uh -huh rightly be called airplanes that worked what the right brothers really invented if you really want to get technical is they invented a control from an airplane that could be used while you were on the airplane
[00:42:19] Red: oh interesting okay
[00:42:22] Blue: that was the big breakthrough that they came up with right just because they already knew how to make a flying machine interesting but they really didn’t know how to control a flying machine that’s right no one knew how to control a flying machine while you were in it well
[00:42:36] Red: that’s pretty big breakthrough it is and and that and of course an airplane is not really an airplane if you can’t be in it right so so the statement the right brothers invented the airplane is still a true statement but only if you understand the word airplane in a certain way right interesting there’s a lot of things like that in life where yeah where where the issue here and this is again probably a subject in of itself the problem is is that there are more concepts than there are words and so just the way late human you know natural language has to work words have to point at multiple concepts right one word has to be reused for multiple related concepts
[00:43:17] Blue: and because it wouldn’t be possible to actually create one word per concept in fact according to Karl Popper’s theory of knowledge that should actually be impossible because you every every individual human has to evolve their own understanding of that word separate from each other using each other for feedback right
[00:43:39] Red: okay wow they should have a whole episode just on that let’s
[00:43:42] Blue: we should actually there’s there’s a there’s a scientist who did considerable research on this uh Douglas Hofstadter who I love his work I know a lot of my agi friends don’t like his stuff and maybe his stuff’s just interesting on its own regardless whether it’s a good path for agi or not he documents a ton of this and it was all part of his research he was trying to research agi in and he ended up documenting a lot of stuff about language instead because he thought that that might be a hint to how the human brain actually did stuff and so he ended up documenting how the human mind abstracts things so you know how do we how do we get to the from the point that a desktop on a wooden desk is the same thing in some sense as a desktop on a computer desk right inside of an operating system
[00:44:35] Red: uh huh
[00:44:36] Blue: right and yet we somehow do it we somehow make some sort of connection that there’s enough similarities between the desktop of a wooden desk that when windows comes along or apple comes along or macintosh comes along that we can call there what’s on their screen a desktop and you suddenly have knowledge about how it works and it’s not it’s imperfect knowledge because it’s not the same and so he documents this he documents how we abstract things one of the reasons why this seems to be just necessary is just the economy of words right there’s just words absolutely will take on lots and lots of different meanings and what we actually do in the human mind is we determine by context what that word means in that context and we don’t even realize we’re doing it right so let me give you an example that he uses which is a really clever example let’s take the word grow what does the word grow mean
[00:45:33] Red: it means wow haha it’s it’s almost not an answerable question Bruce because it it if you look it up in the dictionary it has 72 entries for
[00:45:47] Blue: what the word means it’s very common for people to say it means to make something larger uh huh
[00:45:53] Red: okay and
[00:45:54] Blue: that’s actually a good answer so then he would tell people Hofstadter he would tell people he would say actually it sometimes just means a change of size whether larger or smaller people will challenge him they’ll actually say that is not true in the English language the word grow means to to change larger in size that is what the word grow means so he’ll say okay in Alice in Wonderland she takes the whatever and she grows smaller and smaller and smaller right the fact is is that English using people use that use of the word grow all the time to mean just a change in size
[00:46:30] Red: so we have a a favorite family game that is a word game that we play where where you’re supposed to think of a word and then and the ideal word has just vast amount of meetings I mean meaning it’s not meetings um because some words grow is is a pretty good example um has lots of different ways that we use it in the language that you know we we have an emotional meaning for grow it means to to
[00:47:04] Blue: advance or to yes yes
[00:47:08] Red: right and and you could if you had a group of people who were all trying competitively to think of yet another meaning of a way that we use grow to mean a variety of different things you would find just almost a constantly expanding set of explanation for that particular word
[00:47:28] Blue: yes okay and that’s his point is that actually the meaning of the word is in constant evolution based on how people actually use it the way I’ve tried to explain this to people is words don’t actually have definitions definitions are a made up abstraction that don’t exist in real life they’re useful but they’re just approximations words actually have uses and so when a person says uh you know the uh the stock market you know was growing smaller today everybody knows what that means nobody even stops and thinks about the fact that the word grow has a definition that means to get larger uh and then sees it as some sort of contradiction it’s because we just simply know the word can be used in that way period end of story and it communicates an idea
[00:48:19] Red: if
[00:48:20] Blue: it happens often enough you don’t even feel awkward about it you just use it and he points out that over time this means that words will start off with some sort of meaning and like he uses like the word handsome like what’s handsome got to do with hands and some you know at some point in our history they had some sort of relationship to those words right it had some sort of relationship to those words but it’s lost it right there’s all sorts of words like that where when you try to pick them apart they they’ve he points out that they either have lost their meaning entirely or they’ve partially lost their meaning like you can still make out what the sub word what happened right you can still figure out where the word came from because the words haven’t entirely lost their meaning yet and yet you never really think about it you you just simply know with the way we take words into our minds and use them with concepts we simply use the word and it becomes a signal for that concept but only within certain contexts and we’re always using the full context of the sentence the situation someone pointing things like that to be able to resolve what idea is actually being communicated by this word and you have to do that because otherwise it would be impossible to communicate because words simply don’t point to single they never point to single concepts okay
[00:49:44] Red: so I propose we stop talking about this right now because we could do another whole hour on this and let’s just let’s either do it for next time or the one after because I know you’re also got a subject ready to go for next time yep
[00:49:57] Blue: all right sounds good oh just before we go I want to bring up one other thing that was in the uh Michael Levine’s thing the Xenobot what did you think of that Xenobot
[00:50:07] Red: okay
[00:50:07] Blue: so you’re gonna have to help me remember the Xenobot was where they took um the skin cells of a frog they let it climb it I can’t remember if they they told it to clump together but they clumped together and it formed a little organism and then the organism the the remember the genes aren’t being changed the organism learned to steer itself around and explore its environment even using little hairs or cilia that were intended to move mucus so they had they had no purpose they weren’t the purpose if they were inside the frog would have been completely different than locomotion and yet it it learned on its own to create locomotion and move itself around and to explore its environment
[00:50:55] Red: I don’t really in a way it it seems like a difference like where is that instruction coming from and how his assertion is that still is that essentially electrical sub set of rules that that are actually stronger than the genetic set of rules perhaps
[00:51:17] Blue: that seems to be what he’s implying yeah
[00:51:19] Red: that has some huge implications for even what our current understanding of everything we we know about about life is really genetically driven like we know that electricity is is a thing we but but all of our understanding is that’s where we’ve been putting all of our focus
[00:51:39] Blue: yeah it means that we have no idea what’s going on honestly you know I I suppose I mean like I would love to see people who know more about this than me really assess the xenobots you know is it possible that it’s not actually exploring the environment it’s just by chance looks that way or something like that I would love to see criticisms about that but certainly the pictures that he showed of it it sort of looked like it was kind of swimming around exploring its environment and so that would be very suggestive that the operating system had a good enough intelligent error correction algorithm that it was able to take these skin cells intended for an entirely different purpose by the genes and repurpose them and basically turn itself into its own little organism an organism that doesn’t exist anywhere else you know in regular life in
[00:52:33] Red: nature yeah and that’s um yeah that’s kind of not not scary in but it just means that we really don’t understand and and you know that wouldn’t be that big of a surprise but I think we have a desire to especially you know as we’ve made enormous advances in understanding the genome to feeling like we’re cracking the code but if there’s this whole entire subsystem that actually has complete override capabilities yeah
[00:53:04] Blue: yeah I see where you’re going with this
[00:53:06] Red: yeah I mean it means that we’ve gotten really good at the we’re we’ve done a lot of discovery on the hardware but we had no idea that that there was a separate software operating system
[00:53:18] Blue: yeah you know I agree with everything you’re saying but if you really think about it that’s not that that probably is a big surprise but it probably shouldn’t be because of course mine because of course mines have been that way for forever right sure you know and clearly the genes somehow give rise to mines and mines are able to do purposeful you know evolution and changes that the genes never intended sure sure so it in many ways it’s it’s maybe a shock but maybe it shouldn’t be a shock
[00:53:53] Red: yeah you’re probably right fascinating though
[00:53:58] Blue: yeah I that was one of the things that I found the biggest the two things that really wowed me the most were the two -headed flatworm yeah could reproduce itself as a two -headed flatworm without using CRISPR and the other one was the xenobot again I kind of want to see what other scientists say about this I want people more knowledgeable to first criticize what he’s saying right it survives criticism or not but if it is actually taking skin cells and repurposing it into its own little organism that really is kind of a big deal right that that is a surprising level of intelligence that exists at the biological level outside of the genes
[00:54:40] Red: yes yeah and what we could talk about it for hours but great conversation Bruce I’m glad that you shared this as a as a as a topic
[00:54:49] Blue: yes and thank you for talking with me about it
[00:54:52] Red: yes always happy to yep talk to you later okay bye the
[00:55:00] Blue: theory of anything podcast could use your help we have a small but loyal audience and we’d like to get the word out about the podcast to others so others can enjoy it as well to the best of our knowledge we’re the only podcast that covers all four strands of David Deutch’s philosophy as well as other interesting subjects if you’re enjoying this podcast please give us a five -star rating on apple podcasts this can usually be done right inside your podcast player or you can google the theory of anything podcast apple or something like that some players have their own rating system and giving us a five -star rating on any rating system would be helpful if you enjoy a particular episode please consider tweeting about us or linking to us on facebook or other social media to help get the word out if you are interested in financially supporting the podcast we have two ways to do that the first is via our podcast host site anchor just go to anchor dot fm slash four dash strands f o u r dash s t r a n d s there’s a support button available that allows you to do reoccurring donations if you want to make a one -time donation go to our blog which is four strands dot org there is a donation button there that uses paypal thank you
Links to this episode: Spotify / Apple Podcasts
Generated with AI using PodcastTranscriptor. Unofficial AI-generated transcripts. These may contain mistakes; please verify against the actual podcast.