- People tend to think of intelligence
as being of two kinds:
There's the quote, unquote "real" intelligence,
which is what we are supposed to have,
and then there's this idea of a 'collective intelligence,'
so swarms of bees, colonies of ants,
shoals of fish, and so on.
And people tend to think of those
as radically different things.
But the reality is
all intelligence is collective intelligence,
and this is because we are all made of parts.
So you and I are collections of cells,
and these cells,
including neurons and various other cells in our body,
have many competencies-
this is because they were once
separate individuals by themselves.
They were unicellular organisms
with all of the skills needed to survive in a complex world.
And that journey that we all took,
those progressive steps by which we construct ourselves-
we construct our bodies, we construct our minds-
that journey is maybe the most profound question
in all of science.
I'm Michael Levin, and I'm a developmental biologist
at Tufts University.
Developmental biology is maybe the most magical
of all the sciences
because you get to see with your own eyes
that journey that we all take from physics to mind.
We all start out life as an unfertilized oocyte,
and then slowly, gradually, step-by-step,
that oocyte turns into a bunch of cells
that self-construct an embryo,
and eventually that embryo matures
and becomes a large-scale adult.
In the case of a human, it will be an individual
with metacognitive capacities and the ability to reason.
But we all have our origin in that chemistry and physics
of that initial oocyte.
And the magic of developmental biology
is that there is a mechanism
by which all of these cells get together,
and they are able to cooperate towards large-scale goals.
This is the notion that biology uses
what I call a "Multi-scale competency architecture,"
which basically means
that we are not simply nested structurally
in terms of cells which comprise tissues,
comprising organs, and bodies,
and then ultimately societies and so on-
that's obviously true on a structural level.
But more interesting is the fact that each of these layers
has certain problem-solving competencies.
Each one solves problems in their own space,
so cells are simultaneously solving problems
in physiological spaces and metabolic spaces
and gene expression spaces,
and tissues and organs are solving those problems.
But, for example, during embryogenesis or regeneration,
they're also solving problems in anatomical space.
They're trying to navigate a path
from the shape of an early embryo or a fertilized zygote
all the way up to the complexity of a human body
with all of the different types of organs and structures.
So the competency architecture refers to the fact
that all of the parts inside of us
and inside of all other creatures
are themselves competent agents
with preferences, with goals,
with various abilities to pursue those goals,
and other types of problem-solving capacities.
What evolution has given us is this remarkable architecture
where every level shapes
the behavioral landscape of the levels below-
and the levels below do clever and interesting things
that allow the levels above not to have to micromanage,
and to be able to control
in an interesting top-down capacity.
One of the most important things
about this emerging field of diverse intelligence
is that we, as humans, have very limited capacity
and finely-honed ability to see intelligence
in medium-sized objects moving at medium speeds
through three-dimensional space.
So we see other primates
and we see crows and we see dolphins,
and we have some ability to recognize intelligence.
But we really are very bad at recognizing intelligence
in unconventional embodiments
where our basic expectations strain against this idea
that there could be intelligence
in something extremely small or extremely large.
People often criticize this approach by saying,
"Well, then anything goes.
If you can pick up a rock and say,
'I think this rock is cognitive and intelligent,
you know, there's a spirit with hopes
and dreams inside of every rock.'"
That's not what this is.
This is quite different.
As an engineer, what you have to do
is you have to come up with a way
to look at a particular system
that doesn't overestimate its intelligence
or underestimate its intelligence.
If you treat complex animals as if they were clockwork,
you're gonna miss everything that's important and exciting
about how they work.
If you treat a clock as if it had a complex intelligence,
you're going to waste a lot of time-
but getting it right is fundamentally important.
And so, you have this spectrum where the engineer
has to pick the right level for the right system,
and it's critical not to then say,
"Well, that doesn't sound like human intelligence," right?
We're looking for the basic minimal version.
So I think it should have two things:
The first thing it should have
is some degree of goal-directedness,
some ability to take different paths
to get to the same goals;
so this is William James's definition of intelligence.
And it has to have some ability to undertake actions
that are not completely determined by local circumstances.
So you start with all of that,
and systems that have scaled up,
those basic, very fundamental, non-zero levels of agency,
we call that life.
So it is a spectrum, and I think that in this Universe
it goes all the way to the bottom.
It's very hard for people
to think about these unconventional kinds of intelligences
that may be either too large or too small.
And of course, they often work in other spaces.
So we're good with three-dimensional space,
but imagine if we had a primary sense
of our own blood chemistry.
If you could feel your blood chemistry
the way that you currently see and smell and taste
things that are around you,
I think we would have absolutely no problem
having an intuitive understanding
of physiological-state space
the way we do for three-dimensional space.
I think that we would immediately be able to recognize
our various internal organs as intelligent agents
navigating that space and solving these kind of problems,
all the various things that happen during the day.
And here's one of my favorite examples of problem solving
in physiological and transcriptional spaces:
So we have these worms.
These are Planaria, these are flatworms.
And if you put these flatworms in a solution of barium-
barium is a non-specific potassium channel blocker;
it blocks the ability of these cells
to exchange potassium with the outside world-
the cells really don't like it,
especially cells in the head,
because the head is full of neurons;
neurons love to pass potassium.
And so what happens is that overnight their heads explode.
Literally, it's called head deprogression;
they literally lose their heads.
But if you leave them in the barium,
within a couple weeks they grow back a new head.
And the new head is completely barium-adapted,
has no problem with the barium whatsoever.
We said, "How could this be?"
We looked at the original heads, the original naive heads,
we looked at the barium-adapted heads,
and we simply did a subtraction and asked,
"What are the different genes that are expressed here?"
And we found out that the barium-adapted heads
have just a small number of genes
that were turned on and off
to allow them to adapt to this novel stressor.
Now, here's the amazing part.
Planaria never see barium in the wild.
There's no evolutionary history
of knowing what to do when you're hit with barium.
This is not an ecological stressor
that they normally have to deal with.
So just imagine you're a bunch of cells
and you're hit with this incredible physiological stressor
you've never seen before.
You've got tens of thousands of genes.
What do you do?
How do you know which genes to turn on and off?
You don't have time to try combinations.
You don't have time for an exhaustive search.
You don't have time for hill climbing.
You don't have time to try random things
because you'll probably kill the cell
long before you solve the problem.
And yet, you are able to navigate
from where you are to where you need to be
to escape this physiological stressor.
And so, what I think evolution has done
is pivoted some of the same tricks
from very simple systems that only solve metabolic problems
eventually to physiological
and then to transcriptional problems.
And when multicellularity comes on the scene,
large-scale anatomical problems.
And so it's never a question of:
Is something physics and chemistry, or is it cognitive?
The question is: What kind of cognition, and how much?