Kind: captions
Language: en
The following is a conversation with
Michael Leaven, his second time on the
podcast. He is one of the most
fascinating and brilliant biologists and
scientists I've ever had the pleasure of
speaking with. He and his labs at Tus
University study and build biological
systems that help us understand the
nature of intelligence, agency, memory,
consciousness, and life in all of its
forms here on Earth and beyond.
This is the Lex Freedman podcast. To
support it, please check out our
sponsors in the description where you
can also find links to contact me, ask
questions, give feedback, and so on. And
now, dear friends, here's Michael
Leaven.
You write that the central question at
the heart of your work from uh
biological systems to computational ones
is how do embodied minds arise in the
physical world and what determines the
capabilities and properties of those
minds? Can you unpack that question for
us and maybe uh begin to answer it?
>> Well, the fundamental tension is in both
the first person, the second person and
third person descriptions of mind. So,
so in third person, we want to
understand how do we recognize them and
how do we know looking out into the
world what degree of agency there is and
how best to relate to the different
systems that we find and uh are our
intuitions any good when we look at
something and it looks really stupid and
mechanical versus uh it really looks
like there's something cognitive going
on there. How do we get good at
recognizing them? Then there's the
second person which is the control and
that's both for engineering but also for
regenerative medicine. when you want to
tell the system to do something right,
what kind of tools are you going to use?
And this is a major part of my framework
is that all of these kinds of things are
operational claims. Are you going to use
the tools of hardware rewiring, of
control theory and cybernetics, of
behavior science, of psychoanalysis and
love and friendship? Like what are the
interaction protocols that you bring,
right? And then in first person, it's
this notion of having an inner
perspective and being a system that has
veilance and cares about the outcome of
things, makes decisions and has memories
and tells a story about itself and the
outside world. And how can all of that
exist and still be consistent with the
laws of physics and chemistry and
various other things that that we see
around us? So that that I find to be
maybe the most interesting and the most
important mystery for all of us to uh
both on the science and also on the
personal level. So that's that's what
I'm interested in. So your work is
focused on starting at the physics going
all the way to friendship and love and
psychoanalysis.
>> Yeah. Although although actually I would
turn that upside down. I I think that
pyramid is backwards and I think it's
behavior science at the bottom. I think
it's behavior science all the way. I
think in certain ways even math is the
behavior of a certain kind of being that
lives in a latent space. And physics is
what we call systems that at least look
to be amendable to a very uh simple low
agency kind of model. and so on. But uh
but that's what I'm interested in is
understanding that and developing
applications because it's very important
to me that uh what we do is transition
deep ideas and philosophy into actual
practical applications that not only
make it clear whether we're making any
progress or not but also allow us to
relieve suffering and make life better
for all sensient beings and and enable
to uh you know enable us and others to
reach their full potential. So these are
these are very practical things. I think
behavioral science I suppose is more
subjective and mathematics and physics
is more objective. Would that be the the
clear difference?
>> The idea basically is that where
something is on that spectrum and I've
called it the spectrum of
persuadability. You could call it the
spectrum of intelligence or agency or
something like that. I like the notion
of the spectrum of persuadability
because it's an engineering approach. It
means that these are not things you can
decide or have feelings about from a
from a philosophical armchair. You have
to make a hypothesis about which tools,
which interaction protocols you're going
to bring to a given system and then we
all get to find out how that worked out
for you, right? So, so you could be
wrong in many ways in both directions.
You can guess too high or too low or
wrong in various ways and then we can
all find out how that's working out. And
so I do think that the behavior of
certain objects is well described by
specific formal formal rules and we call
those things the the subject of
mathematics. And then there are some
other things whose behavior really
requires the kinds of uh tools that we
use in in behavioral cognitive
neuroscience. And those are other kinds
of minds that that we think we study in
biology or in psychology or other
sciences.
>> Why why are you using the term
persuadability? Who are you persuading
and of what?
>> Well,
>> in this context,
>> yeah, the beginning of my work is very
much in regenerative medicine, in uh in
bioengineering, things like that. So,
for those kinds of systems, the re the
question is always how do you get the
system to do what you want it to do? So,
there are cells, there are molecular
networks, there are materials, there are
organs and tissues and synthetic beings
and biobots and whatever. And so the
idea is if I want your cells to regrow a
limb, for example, if you're injured and
I want your cells to regrow a limb, I
have many options. Some of those options
are I'm going to micromanage all of the
molecular uh events that have to happen,
right? And there's an incredible number
of those. Or maybe I just have to
micromanage the cells and the stem cell
kinds of signaling factors. or maybe
actually I can give the cells a very
high level uh prompt that says you
really should build the limb and
convince them to do it right and so
where um what which of those is possible
I mean clearly people have a lot of
intuitions about that if you ask
standard people in regenerative medicine
and molecular biology they're going to
say well that convincing thing is crazy
what we really should be doing is
talking to the cells or better yet the
molecular networks and in fact all the
excitement of the biological sciences
today are at at you know single molecule
approaches and big data and and and
genomics and all of that. The assumption
is that uh going down is where the
action is going to be going down in
scale and and I think that's I think
that's wrong. But the but the thing that
we can say for sure is that you can't
guess that you you have to do
experiments and you have to see because
you don't know where any given system is
on that spectrum of persuadability. And
it turns out that every time we look and
we take tools from behavioral science,
so learning different kinds of training,
different kinds of models that are used
in uh active inference and surprise
minimization and uh perceptual
multi-stability and visual illusions and
all all these kinds of interesting
things, you know, stress perception and
and memory um active memory
reconstruction. and all these
interesting things when we apply them
outside the brain to other kinds of
living systems we find novel discoveries
and novel capabilities actually being
able to get the material to do new
things that nobody had ever found before
and and precisely because I think that
uh people didn't didn't look at it from
from those perspectives they they
assumed that it was a low-level kind of
thing so when I say persuadability I
mean different types of approaches right
and we all and we all know if you want
to if you want to persuade your windup
clock to do something you not going to
argue with it or make it feel guilty or
anything. You're going to have to get in
there with a wrench and you're going to
have to, you know, tune it up and do
whatever. If you want to do that same
thing to a cell or a thermostat or an
animal or a human, you're going to be
using other sets of tools that we've
given other names to. And so that's now
now of course that spectrum, the
important thing is that as you get to
the right of that spectrum, as the
agency of the system goes up, it is no
longer just about persuading it to do
things. It's a birectional relationship,
what Richard Watson would call a mutual
vulnerable knowing. So the idea is that
on the right side of that spectrum, when
systems reach the higher levels of
agency, the idea is that you're willing
to let that system persuade you of
things as well. You know, in molecular
biology, you do things hopefully the
system does what you want to do, but you
haven't changed. You're still you're
still exactly the way you you came in.
But on the right side of that spectrum,
if you're having interactions with even
cells, but certainly, you know, uh dogs,
other other animals, maybe maybe other
other creatures soon, you're not the
same at the end of that interaction as
you were going in. It's a mutual
birectional relationship. So it's not
just you persuading something else. It's
not you pushing things. It's a it's a
mutual birectional set of uh set of
persuasions whether those are purely
intellectual or of other kinds.
>> So in order to be effective at
persuading an intelligent being, you
yourself have to be persuadable. So the
closer in intelligence you are to the
thing you're trying to persuade, the
more persuadable you have to become.
Hence the mutual vulnerable knowing.
What a term.
>> Yeah. Yeah. Richard, yeah, you should
you should talk to Richard as well. He's
he's an amazing guy and he's got some
very interesting ideas about at the
intersection of cognition and um
evolution. But I, you know, I think I
think what you bring up is is very
important because um there has to be a
kind of impedance match between what
you're looking for and the tools that
you're using. I think the reason physics
always sees mechanism and not minds is
that physics uses low agency tools.
You've got voltmeters and and rulers and
things like this and and if you use
those tools as your interface, all
you're ever going to see is mechanisms
and and those kinds of things. If you
want to see minds, you have to use a
mind, right? You have to have there has
to be some degree of resonance between
your interface and the thing you're
hoping to find.
>> You said this about physics before. Can
you just linger on that? Like expand on
it. What you mean why physics is not
enough to understand life, to understand
mind, to understand intelligence? You
make a lot of controversial statements
with your work. That's one of them
because there's a lot of physicists that
believe they can understand life, the
emergence of life, the origin of life,
the origin of intelligence using the
tools of physics. In fact, all the other
tools are a distraction to those folks.
If you want to understand fundamentally
anything, you have to start a physics to
them. And you're saying, "No, physics is
not enough."
>> Here's here's the issue. Everything here
hangs on what it means to understand.
Okay? in for for me because understand
doesn't just mean uh have some sort of
uh pleasing model that seems to capture
some important aspect of what's going
on. It also means that you have to be
generative and creative in terms of
capabilities. And so for me that means
if I tell you this is what I think about
cognition in cells and tissues, it means
for example that uh I think we're going
to be able to take those ideas and use
them to produce new regenerative
medicine that actually helps people in
various ways. Right? is just an example.
So if you think as a physicist you're
going to have a complete understanding
of what's going on from that uh
perspective of of fields and particles
and then you know who knows what what
else is at the bottom there.
Does that mean then that when somebody
is missing a finger or has a
psychological problem or or or or you
know has these other highle issues that
you have something for them that you're
going to be able to do something because
my claim is that you're not going to and
even even if even if you you have some
theory of physics that is completely
compatible with everything that's going
on that is it's not enough that's not
specific enough to enable you to solve
the problems you need to solve. In the
end when you need to solve those
problems the the person you're going go
to is not a physicist. It's going to be
either a biologist or a psychiatrist or
who knows but but it's not going to be a
physicist. And and the simple example is
this, you know, let's say let's say
someone uh comes in here and tells you a
beautiful mathematical proof. Okay, it's
just really, you know, deep and
beautiful. And there's a physicist
nearby and he says, "Well, I know
exactly what happened. I there were some
air particles that moved from from from
that guy's mouth to your ear. I see what
goes on. It moved your uh the psyia um
in your ear and the and the electrical
signals went up to your brain. I mean we
have a complete accounting of what
happened done and done. But if you want
to understand what's the more important
aspect of that interaction, it's not
going to be found in the physics
department. It's going to be found in
the math department. So that's my only
claim is that is that physics is an
amazing lens with which to view the
world, but you're capturing certain
things and and if you want to stretch to
sort of encompass these other things, it
it's just we just don't call that
physics anymore, right? That's we we
call that something else.
>> Okay. But you're kind of speaking about
the uh super complex organisms. Can we
go to the simplest possible thing where
you first take a step over the line, the
cartisian cut as you've called it from
the non- mind to mind, from the
non-living to living is simplest
possible thing. Isn't that in the realm
of physics to understand? How do we
understand that first step where you're
like that thing is no mind probably
non-living and here's a living thing
that has a mind that line I think that's
a really interesting line maybe you can
speak to the line as well and can
physics help us understand it
>> yeah let's talk about well first of all
of of course it can mean it can help
meaning that I'm not saying physics is
not helpful of course it's helpful it's
it's a very important lens on one slice
of what's going on in any of these
systems but I think the most important
thing I can say about um that question
is I I don't believe in any such line. I
don't believe any of that exists. I
think uh I think there is a um I think
it's a continuum. I think we as humans
like to uh demarcate areas on that
continuum and give them names because it
makes life easier and then we have a lot
of battles over uh you know so-called
category errors when people transgress
those those categories. I think most of
those categories at this point they they
may have done some some good service at
the beginning of when the scientific
method was getting started and so on. I
think at this point uh they mostly hold
back science. Many many categories that
we can talk about are at this point very
harmful to progress because what those
categories do is they prevent you from
porting tools. If you think that uh
living things are fundamentally
different from non-living things or if
you think that cognitive things are
these like advanced brainy things that
are very different from other kinds of
systems, what you're not going to do is
take the tools that are appropriate to
these to to these kind of uh cognitive
systems, right? So the so the tools that
have been developed in in behavioral
science and so on, you're never going to
try them in other contexts because
because you've already decided that
there's a categorical difference that it
would be a categorical error to apply
them and and people say this to me all
the time is that you're making a
category error and as as if these
categories were given to us, you know,
from from from on high and we have to we
have to obey them forever more. The
category should change with the science.
So um yeah I don't believe in any such
line and I think I think a physics story
is very often a useful part of the story
but for most interesting things it's not
the entire story. Okay. So if there's no
line is it still useful to talk about
things like the origin of life. That's
the the one of the big open mysteries
before us as a human civilization, as uh
scientifically minded, curious homo
sapiens. How did this whole thing start?
Are you saying there is no start? Is
there a point where you could say that
invention right there was the start of
it all on Earth? My suggestion is that
much better than trying to in in in my
experience much better than trying to
define any kind of a line. Okay? Because
because inevitably I've never I've never
found and people try to you know we play
this game all the time when I make my
continuum claim then people try to come
up okay well what about this? You know
what about this? And I haven't found one
yet that really shoots that down that
that you can't zoom in and say yeah okay
but right before then this happened and
then if we really look close like here's
a bunch of steps in between right?
pretty much everything ends up being a
continuum. But here's what I think is
much more interesting than trying to
make that line. I think what's what's
really uh more useful is trying to
understand the transformation process.
What is it that happened to scale up?
And I'll give you a really dumb example
and we and we always get into this
because people people often really
really don't like this continuum view.
The word adult, right? Everybody is
going to say, "Look, I know what a baby
is. I know what an adult is. You're
crazy to say that there's no
difference." Not saying there's no
difference. What I'm saying is the word
adult is really helpful in court because
because because you just need to move
things along. And so we've decided that
uh if you're 18, you're an adult.
However, what it hides is is what what
it completely conceals is the fact that
first of all, [clears throat] nothing
happens on your 18th birthday, right?
That's that's special. Second, if you
actually look at the data, the car
rental companies actually have a much
better estimate because they actually
look at the accident statistics and
they'll say it's about 25 is is is
really what you're looking for, right?
So, theirs is a little better. It's less
arbitrary. But in either case, what it's
hiding is the fact that we do not have a
good story of what happened from the
time that you were an egg to the time
that you're this supposed adult. And
what is the scaling of re personal
responsibility, decisionm judgment, like
these are deep fundamental cont, you
know, questions. Nobody wants to get
into that every time somebody uh, you
know, has a traffic ticket. And so,
okay, so so we've just decided that
there's this adult idea. How and and and
of course it does come up in court
because then somebody has a brain tumor
or somebody's eaten too many Twinkies or
or something has happened. You say,
"Look, that wasn't me. Whoever did that?
I was on drugs." Well, why'd you take
the drugs? Well, that was, you know,
that was yesterday, me today. This is
some, right? So, so we get into these
very deep questions that are completely
glossed over by this idea of an adult.
So, so I think once you start scratching
the surface, most of these categories
are like that. They're convenient and
they're good. It it's, you know, I get
into this with neurons all the time. I
I'll ask people what's what's a neuron?
Like what's really a neuron? And yes, if
you're if you're in neurobiology 101, of
course, you just say, "Look, these are
what neurons look like. Let's just study
the neuro anatomy and we're done." But
if you really want to understand what's
going on, well, neurons develop from
other types of cells and that was a slow
and gradual process and most of the
cells in your body do the things that
neurons do. So, what really is a neuron,
right? So, so once you start scratching
this, this this happens and I have some
things that I think are coming out of
our lab and others that are I think very
interesting about the origin of life.
But I don't think it's about finding
that one boom like this is yeah there'll
be there there are innovations right
there are there are innovations that
that um allow you to uh scale in a in an
amazing way for for sure and and there
are lots of people that study those
right so so things that thermodynamic
kind of metabolic things and and and all
kinds of architectures and so on but I
don't think it's about finding a line I
think it's about finding a scaling
process
>> the scaling process but then there is
more rapid scaling and there's slower
scaling so innovation invention
I think is useful to understand so you
can predict how likely it is on other
planets for example or uh to be able to
describe
the likelihood of these kinds of
phenomena happening in certain kinds of
environments again specifically in
answering how many alien civilizations
there are you that's why it's useful but
it's also useful on a scientific level
to have categories not just cuz it makes
us feel good and fuzzy side but because
it makes conversation possible and
productive. I think if everything is a
spectrum is it it becomes um difficult
to make concrete statements. I think
like we even use the terms of biology
and physics those are categories
technically it's all the same thing
really fundamentally it's all the same
there's no difference between biology
and physics but it's a useful category
if you go to the physics department and
the biology department those people are
different in in some kind of categorical
way so somehow I don't know what the
chicken or the egg is but the categories
maybe the categories create themselves
because of the way we think about them
and use them in language But it does
seem useful.
>> Let me make the opposite argument.
They're absolutely useful. They're
useful specifically when you want to
gloss over certain things. Ex the
categories are exactly useful when
there's a whole bunch of stuff. And this
is this is what's important about
science is like the art of being able to
say something without first having to
say everything, right? Which would make
it impossible. So, so categories are
great when you when you want to say,
look, I I I know there's a bunch of
stuff hidden here. I'm going to ignore
all that and we're just going to like
let's get on with this particular thing.
And all of that is great as long as you
don't lose track of the stuff that you
glossed over. And that was what I'm
afraid is happening in a lot of
different ways. And in terms of look,
I'm I'm I'm very interested in in in
life, you know, beyond Earth and all all
of these kinds of things. Although we
should also talk about what I call suti
sui, the search for unconventional
terrestrial intelligences. I think I
think I think we got much bigger issues
than than actually recognizing aliens
off Earth. But I'll make this claim. I
think the categorical stuff is actually
hurting that search because because if
we try to define categories uh with the
kinds of criteria that we've gotten used
to, we are going to be very poorly set
up to recognize life in novel
embodiment. I think we have a kind of
mind blindness. I think this is really
key. It's much to to me to me um the
cognitive spectrum is much more
interesting than the spectrum of life. I
think really what we're talking about is
a spectrum of cognition. And uh it it's
I know it's weird as a biologist to say
I don't think life is all that
interesting a category. I think the
categories of of different types of
minds I think is extremely interesting.
And to the extent that we think our
categories are complete and are cutting
nature at its joints, we are going to be
very poorly placed to recognize novel
systems. So for example, a lot of people
will say, well, this is intelligent and
this isn't, right? and there's a binary
thing and and and that's useful in
occasionally that's useful for some
things. I would like to say instead of
that, let's make us let's let's let's
admit that we have a spectrum. But
instead of just saying, oh look,
everything's intelligent, right? Because
if you do that, you're right. You can't
you can't do anything after that. What
I'd like to say instead is no, no, you
have to be very specific as to what kind
and how much. In other words, what
problem space is it operating in? What
kind of mind does it have? What kind of
cognitive capacities does it have? You
have to actually be much more specific.
And and we can even name, right? That's
fine. We can name different types of I
mean this is doing predictive
processing. this can't do that but it
can't form memories. What kind? Well,
habituation and sensitization but not
associative conditioning. Like it's fine
to have categories for specific
capabilities. But it's it's uh it
actually I think it actually makes makes
for much more rigorous discussions
because it makes you say what is it that
you're claiming this thing does? And it
works in both directions. So So some
people will say well that's a that's a
cell that can't be intelligent. And I
say well let's be very specific. Here
are some claims about here's some
problem solving that it's doing. tell me
why that doesn't you know why doesn't
that match or in the opposite direction
somebody comes to me and says you're
right you're right you know the whole
the whole solar system and it's just
like this amazing like okay what is it
doing like tell me tell me what what
tools of cognitive and behavioral
science are you using to to to reach
that conclusion right and so I think I
think it's actually much more productive
to take this operationalist stance and
say tell tell me what protocols you
think you can deploy with this thing
that would lead you to to to use these
terms
>> to have a bit of a meta conversation
about the conversation I should say that
part of the persuadability argument that
we two intelligent creatures are doing
is uh me playing devil's advocate every
once in a while and you did the same
which is kind of interesting taking the
opposite view you see what comes out
>> cuz you don't know the result of the
argument until you have the argument and
it's seems productive to just take the
other side of the argument
>> for sure it's a very important uh
thinking aid to
first of all you know what they call
steel manning right to try to try to
make the strongest possible case for the
other side and to ask yourself, okay,
what are all the what are all the places
that I am sort of glossing over because
I don't know exactly what to say and
where all the where are all the holes in
the argument and what would what would a
you know a really good critique really
look like? Yeah.
>> Sorry to go back there just to linger on
the term because it's so interesting
persuadability.
>> Did I understand correctly that you mean
that it's kind of synonymous with
intelligence? So it's an engineering
centric view of an intelligence system
because if it's persuadable you're more
focused on how can I steer the goals of
the system the behaviors of the system
which meaning an intelligence system
maybe is a is a goal oriented goal-
driven system with agency and when you
call it persuadable you're thinking more
like okay here's an intelligent system
that I'm interacting with that I would
like to get it to accomplish certain
things, but fundamentally they're
synonymous or correlated persuadability
and intelligence.
>> They're definitely correlated. So, so
let me I want to I want to um preface
this with with one thing. When I say
it's an engineering perspective, I don't
mean that the standard uh tools that we
use in engineering and this idea of of
enforced control and steering is how we
should view all of the world. I'm not
saying that at all and and and I want to
be very clear on the because because
because because because people do email
me and say nah this engineering thing
you're going to drain the you know the
life and the majesty out of these
high-end like human conversation. My
whole my whole point is not that at all.
It's that uh of course at the right side
of the spectrum it doesn't look like
engineering anymore right it looks like
it looks like friendship and love and
psychoanalysis and all these other tools
that we have. But here's what I want to
do. I want to be very specific to my
colleagues in regenerative medicine and
just imagine if I you know if I if I
went to a bioengineering department or a
genetics department and I started
talking about highle you know cognition
and psychoanalysis right they don't want
to hear that so so I I bring my I focus
on the engineering approach because I I
want to say look
>> this is not a philosophical problem this
is not a linguistics problem we are not
trying to uh define terms in different
ways to make anybody feel fuzzy what I'm
telling you is if you want to reach
certain capab capabilities. If you want
to reprogram cancer, if you want to
regrow new organs, you want to defeat
aging, you want to do these specific
things, you are leaving too much on the
table by making an unwarranted
assumption that the low-level tools that
we have, so these are the rules of
chemistry and the kind of remlecular
rewiring that those are going to be
sufficient to get to where you want to
go. It's a it's a it's an assumption
only and it's an unwarranted assumption
and actually we've done experiments now.
So, so not philosophy but real
experiments that if you take these other
tools you can in fact persuade the
system in ways that has never been done
before and and and we can we can unpack
all of that but it is it is absolutely
um correlated with intelligence. So let
me um flesh that out a little bit. Um
what I think is scaling in all of these
things right because I keep talking
about the scaling. So what is it that's
scaling? What I think is scaling is
something I call the cognitive ly cone.
And the cognitive lyone is the size of
the biggest goal state that you can
pursue. This doesn't mean how far do
your senses reach. This doesn't mean how
far can you affect it. So the James Web
telescope has enormous sensory reach.
But that doesn't mean that's that's the
size of its cognitive ly. The size of
the cognitive ly is the scale of the
biggest goal you can actively pursue.
But I do think it's a useful concept to
enable us to think about very different
types of agents of different
composition, different provenence, you
know, engineered, evolved, hybrid,
whatever, all in the same framework. And
by the way, the reason I use Lyone is
that it has this idea from physics that
you're putting space and time kind of in
the same diagram, which is which which I
like here. So if you tell me that all
your goals revolve around maximizing the
amount of sugar con the amount of sugar
in this in this you know 10 20 micron
radius of spacetime and that you have
you know 20 minutes memory going back
and maybe 5 minutes predictive capacity
going forward that tiny little cognitive
light I'm going to say probably a
bacterium and if you say to me that well
I care I'm able to care about several
hundred yards sort of scale I could
never care about what happens 3 weeks
from now two towns over just impossible.
I'm say you might be a dog and if and if
you say to me okay I care about uh
really what happens you know the
financial markets on earth the you know
long after I'm dead and this and that
say you're probably a human and if you
say to me I care in the linear range I
actively not I'm not just saying it I
can actively care in the linear range
about all the living beings on this
planet I'm going to say well you're not
a standard human you must be something
else because humans I don't these
standard humans today I don't think can
do that you you must be some kind of a
body or some other thing that has these
massive cognitive icons. So I think
what's scaling from zero and I do think
it goes all the way down. I think we can
talk about um uh even even particles
doing something like this. I think what
scales is the size of the cognitive
icon. And so now this is an interesting
here. I'll I'll try for a definition of
life or whatever for whatever it's
worth. I spent no time trying to make
that stick, but if we wanted to, uh, I
think we call things alive to the extent
that
the cognitive light cone of that thing
is bigger than that of its parts. So, in
other words, rocks aren't very exciting
because the things it knows how to do
are the things that its parts already
know how to do, which is follow
gradients and and things like that. But
living things are amazing at aligning
their their competent parts so that the
collective has a larger cognitive lie
than the parts. I'll give you a very
simple example that comes up in in
biology and it comes up in our cancer um
program all the time. Individual cells
have little tiny cognitive lyones. They
what are their goals? Well, they're
trying to manage pH, metabolic state,
some other things. There are some goals
in transcriptional space, some goals in
uh metabolic space, some goals in uh
physiological state space, but but they
they're generally very tiny goals. One
thing evolution did was to provide a
kind of cognitive glue, which we can
also talk about that ties them together
into a multisellular system. And those
systems have grandiose goals. They're
making limbs. And and if you're a
salamander limb and you chop it off,
they will regrow that limb with the
right number of fingers. Then they'll
stop when it's done. the goal has been
achieved. No individual cell knows what
a finger is or how many fingers you're
supposed to have, but the collective
absolutely does. And that process of
growing that cognitive ly from a single
cell to something much bigger and of
course the failure mode of that process.
So cancer, right? When cells disconnect,
they physiologically disconnect from the
other cells, their cognitive ly shrinks.
The boundary between self and world,
which is what the cognitive ly defines,
uh shrinks. Now they're back to an
amoeba. As far as they're concerned, the
rest of the body is just external
environment. And they do what amibbas
do. They go where life is good. They
reproduce as much as they can. Right? So
that that cognitive lie that that that
is the thing that I'm talking about that
scales. And so when we're looking for
life, I I don't think we're looking for
specific materials. I don't think we're
looking for specific metabolic states. I
think we're looking for scales of
cognitive lone. We're looking for
alignment of parts towards bigger goals
in spaces that the parts could not
comprehend. And so cognitive ly cone
just to uh make clear is about goals
that you can actively pursue now. You
said linear like within reach
immediately.
>> No, I didn't. Sorry, I didn't mean that.
First of all, the goal necessarily is is
often removed in time. So in other
words, when you're pursuing a goal, it
means that you have a separation between
current state and target state at
minimum your your thermostat, right?
Let's just think about that. there there
is a separation in time because the
thing you're trying to make happen so
that the temperature goes to a certain
level is not true right now and all your
actions are going to be around reducing
that error right that basic homeostatic
loop is all about closing that that gap
when I meant when I said linear range
this is what I meant uh if I say to you
this this terrible thing happened to uh
you know 10 people and and you know you
have some some degree of activation
about it and then they say no no no
actually it was 100 you know 10,000
You're not a thousand times more
activated about it. You're somewhat more
activated, but but it's not a thousand.
And if I say, "Oh my god, it was
actually 10 million people." You're not
a million times more activated. You you
don't have that capacity in the linear
range, you sort of you sort of, right?
If you think about that curve, we sort
of we reach a saturation point. I have
some amazing colleagues in the Buddhist
community with whom we've written some
papers about this. The radius of
compassion is like, can you grow your
cognitive system to the point that yeah,
it really isn't just your family group.
It really isn't just the hundred people
you know in your in your you know
circle. Can you grow your cognitive um
lightco to the point where no no we care
about the whole whether it's all of
humanity or the whole ecosystem or the
whole whatever. Can you actually care
about that the exact same way that we
now care about a much smaller um set of
people. That's what I mean by linear
range.
>> But you say separated by time like a
thermostat. But a bacteria,
I mean, if you zoom out far enough, a
bacteria could be formulated to have a
goal state of creating human
civilization.
Because if you look at the, you know,
bacteria
>> has a role to play in the whole history
of Earth.
And so
if you anthropomorphize the goals of a
bacteria enough, I mean it has a
concrete role to play in the history of
the evolution of human civilization. So
you do need to when you define a
cognitive light cone, you're looking at
directly short-term behavior.
>> Well, no. How do you know what the
cognitive ly cone of something is?
Because as as you've said, it could be
it could be almost anything. The key is
you have to do experiments and the way
you do experiments is you put barrier
you have to do interventional
experiments. You have to put barriers
between it and its goal and you have to
ask what happens and intelligence is the
degree of ingenuity that it has in
overcoming barriers between it and its
goal. Now if it were to be that now now
this is the this this is I think a
totally doable but but impractical and
very expensive experiment but you could
imagine setting up a scenario where the
bacteria were blocked from becoming more
complex and you can ask if they would
try to find ways around it or whether
it's actually nah their goals are
actually metabolic and as long as those
goals are met they're not going to
actually get around your barrier. The
the the this this this business of
putting barriers between things and
their goals is actually extremely
powerful because we've deployed it in
all kinds of and I'm sure I'm sure we'll
get to this later, but we've we've
deployed it in all kinds of weird
systems that you wouldn't think are
goal- driven systems. And what it allows
us to do is to get beyond just the the
the what you call anthropomorphizing
claims of say you know saying oh yeah I
think you know I think this is thing is
trying to do this or that. The question
is well let's do the experiment. And one
other thing I want to say about
anthropomorphizing is people people say
this to me all the time. Um I I I don't
think that exists. I think that's kind
of like you know uh uh and I'll I'll
tell you why. I think it's like heresy
or like uh other other terms that aren't
really a thing because if you if you
unpack it, here's here's what
anthropomorphism means. Humans have a
certain magic and you're making a
category error by attributing that magic
somewhere else. My point is we have the
same magic that everything has. We have
a couple of interesting things besidg
and some other stuff. And it isn't that
you have to keep the humans separate
because there's some bright line. It's
just it's it's that same old uh all all
I'm all I'm arguing for is the
scientific method. Really, that's really
all this is. All I'm saying is you can't
just make pronouncements such as the
humans are this and let's not uh sort of
push that. You have to do experiments.
After you've done your experiments, you
can say either I've done it and I found
look at that. That thing actually can
predict the future for the next, you
know, 12 minutes. Amazing. Or you say,
you know what, I've tried all the things
in the behaviorist handbook. they just
don't help me with this. It's a very low
level of like that's it. It's it's a
very low level of intelligence. Fine.
Right. Done. So that's really all I'm
arguing for is an empirical approach and
then things like anthropomorphism go
away. It's just a matter of have you
done the experiment and what did you
find?
>> And that's actually one of the things
you're saying that uh if you remove the
categorization of things, you can use
the tools
>> of one discipline on everything.
>> You can try
>> to try and then see. That's the
underpaintings of the criticism
anthropomorphization
because uh what is that? That's like
psychoanalysis of another human could
technically be applied to to robots to
AI systems to more primitive biological
systems and so on. try. Yeah, we've used
everything from basic habituation
conditioning all the way through
anxolytics, hallucinogens, all kinds of
cognitive modification on the range of
things that you wouldn't believe. And by
the way, I'm not the first person to
come up with this. So, there was a guy
named Bose well over a hundred years
ago, who was studying how anesthesia
affected animals and animal cells and
drawing specific curves around
electrical excitability. And he then
went and did it with plants and saw some
very similar phenomena. And being the
genius that he was, he then said, "Well,
how do I don't know when to stop, but
there's no there's no, you know,
everybody thinks we should have stopped
long before plants cuz people made fun
of him for that." And he's like, "Yeah,
but but the science doesn't tell us
where to stop. The tool is working.
Let's keep going." And he showed
interesting phenomena on materials,
metals and and and other kinds of
materials, right? And so uh the
interesting thing is that yeah there is
no there is no uh you know generic rule
that tells you when uh when do you need
to stop. We make those up. Those are
completely made up. You have to just you
have to do the science and find out.
>> Yeah. You uh we'll probably get to it.
Uh you've been doing recent work on
looking at computational systems even
trivial ones like algorithms sorting
algorithms
>> and analyzing in the behavioral kind of
way. See if there's minds inside those
sorting algorithms. And it of course let
me make a pod statement question here
that
>> you can start to do things like uh
trying to do psychedelics with a
sorting.
>> Yeah.
>> And what does that even look like?
[snorts]
>> It looks like a ridiculous question.
It'll get you fired from most academic
departments, but it may be if you take
it seriously, you could try
>> and see if it applies.
>> Yeah. If it has if a thing could be
shown to have some kind of
cognitive complexity, some kind of mind,
why not apply to it the same kind of
analysis and the same kind of tools like
psychedelics that you would to a human
mind that's a complex human mind. It's
at least might be a productive question
to ask what cuz you've seen like spiders
on psychedelics like more primitive
biological organisms on psychedelics.
Why not try to see what what an
algorithm does on psychedelics?
>> Well, well, yeah, because you see the
the thing to remember is we don't have a
magic sense or a really good intuition
for what the mapping is between an the
embodiment of something and the degree
of intelligence it has. We we think we
do because we have an N of one example
on Earth and we kind of know what to
expect from cells, snakes, uh you know,
primates, what but we really don't. We
don't have and this is we we'll get into
more of the stuff on the platonic space
but I our intuitions around that stuff
is so bad that to really think that we
know enough not to try things at this
point is is I think really shortsighted
before we talk about the platonic space
let's uh let's lay out some foundations
I think one useful one comes from the
paper technological approach to mind
everywhere
>> an experimentally grounded framework for
understanding diverse bodies and minds
Could you tell me about this framework
and maybe can you tell me about figure
one from this paper that has a few
components? One is the tiers of
biological cognition. It goes from group
to whole organism to whole tissue organ
down to neural network down to
cytokeleton down to genetic network and
then there's layers of biological
systems from ecosystem down to swarm
down to organism tissue and finally
cell. So can you explain this figure and
can you explain the tame so-called
framework? So this is the version 1.0
and there's a there's a kind of update
of 2.0 that I'm writing at the moment
trying to uh formalize in a careful way
all the things that we've been talking
about here and in particular this notion
of having to do experiments to figure
out where any given system is on a
continuum. And we can let's let's just
start with figure two maybe for a second
and then we'll come back to figure one.
And first just to unpack the acronym, I
like the idea that it spells out tame
because the central focus of this is
interactions. And how do you um how do
you interact with a system to have a
productive interaction with it? And the
idea is that cognitive claims are really
protocol claims. When you tell me that
something has some degree of
intelligence, what you're really saying
is this is the set of tools I'm going to
deploy and we can all find out how that
worked out for you. And so um
technological because I wanted to be
clear uh with my colleagues that this
was not a pro a project in just
philosophy. This had very specific
empirical implications that are going to
play out in engineering and regenerative
medicine and so on. Technological
approach to mind everywhere. This idea
that we don't know yet where different
kinds of minds are to be found and we
have to uh empirically figure that out.
And so what you see here in figure two
is basically this this idea that there
is a spectrum. And I'm just showing four
way points along that spectrum. And as
you move to the right of that spectrum,
a couple things happen. Persuadability
goes up, meaning that the systems become
more reprogrammable, more plastic, more
able to do different things than
whatever they're standardly doing. So
you have more ability to get them to do
new and interesting things. The effort
needed to exert influence goes down.
That is autonomy goes up. And to the
extent that you are good at convincing
or motivating the system to do things,
you don't have to sweat the details as
much. Right? And this also has to do
with what I call engineering agential
materials. So when you engineer um wood,
metal, plastic, things like that, you
are responsible for absolutely
everything because the material is not
going to do anything other than
hopefully hold its shape. If you're
engineering
uh active matter or you're engineering
computational materials or better yet um
agential materials like like living
matter, you can do some very high level
uh prompting and let the system then do
very complicated things that you don't
need to micromanage. And we all we all
know that that increases when you're
starting to work with intelligent
systems like animals and and humans and
so on. And the other thing that goes
down as you get to the right is the
amount of mechanism or physics that you
need to exert the influence goes down.
So if you know how your thermostat is to
be set as far as its set point, you
really don't need to know much of
anything else, right? You you just need
to know that it is a homeostatic system
and that this is how I change the set
point. You don't need to know how the
cooling and heating plant works in order
to get it to do complex things.
>> By the way, a quick uh pause just for
people who are listening. Let me
describe what's in the figure. So
there's four different systems going up
the scale of persuadability.
So the first system is a mechanical
clock, then it's a thermostat, then it's
a a dog that gets rewards and
punishments. Pavlov's dog, and then
finally a bunch of very smartl
lookinging humans communicating with
each other and arguing, persuading each
other using hashtag reasons. And then uh
there's arrows below that showing
persuadability going up as you go up
these systems from the mechanical clock
to a bunch of Greeks arguing and then
going down as the effort needed to exert
influence and once again going down as
mechanism knowledge needed to exert that
influence.
>> Yeah, I'll give you an example about
that panel C here with the with the dog.
Isn't it amazing that humans have been
training dogs and horses for thousands
of years knowing zero neuroscience? Also
amazing is that when I'm talking to you
right now, I don't need to worry about
manipulating all of the synaptic
proteins in your brain to make you
understand what I'm saying and hopefully
remember it. You're going to do that all
on your own. I'm giving you very thin in
terms of information uh content, very
thin prompt and I'm counting on you as a
as a multiscale agential material to
take care of the chemistry underneath.
Right?
>> So you don't need a wrench to convince
me.
>> Correct. I don't need and I don't need
physics to convince you and I don't need
to know how you work. like I I don't
need to understand all of the steps.
What I do need to have is trust that you
are a multiscale cognitive system that
already does that for for yourself. And
you do like this is an amazing thing. I
don't people don't think about this
enough. I think uh when you wake up in
the morning and you have social goals,
research goals, financial goals,
whatever, whatever it is that you have,
in order for you to act on those goals,
sodium and calciu