- 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?
