WEBVTT - Lab-Grown Brain Organoids Are Playing Video Games

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<v Speaker 1>Welcome to Tech Stuff. I'm Oz Veloshian. There's only one

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<v Speaker 1>way to put this. I read one of the craziest

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<v Speaker 1>articles in recent memory, recently in Wired. It's called AI

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<v Speaker 1>is Dead, Organoids are Alive. And it's a look inside scientists'

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<v Speaker 1>attempt to grow computers powered by human cells grown in

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<v Speaker 1>a lab. Written by Claire L. Evans, a journalist, a

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<v Speaker 1>speculative fiction writer, and a musician with the band Yacht.

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<v Speaker 1>who also had some remarkable experiences reporting this piece that

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<v Speaker 1>she's here to share with us today. Claire, thank you

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<v Speaker 1>for joining.

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<v Speaker 2>Oh, thank you so much for having me.

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<v Speaker 1>So talk about organoids and this quote that you have

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<v Speaker 1>early in the piece, I'm going to let you in

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<v Speaker 1>on a secret. Every cell in your body has the

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<v Speaker 1>potential to get smarter.

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<v Speaker 2>Yes, that's technically true. You can take any cell from

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<v Speaker 2>the human body, normally skin cells, but also hair, follicle cells, teeth, blood,

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<v Speaker 2>these all work. You can introduce those cells to a

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<v Speaker 2>special cocktail of proteins. Those cells will revert to their

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<v Speaker 2>embryonic state. They will become stem cells. They will become pluripotent,

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<v Speaker 2>which means capable of turning into many other different types

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<v Speaker 2>of cells. And you can turn those cells into neurons

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<v Speaker 2>and from there build all kinds of interesting things.

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<v Speaker 1>So what is an organoid?

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<v Speaker 2>Okay, well, big picture. An organoid is... essentially a small

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<v Speaker 2>spherical glob of human cells that reproduces on some different levels, structural, molecular,

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<v Speaker 2>developmental levels, some aspect of the body part from which

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<v Speaker 2>those cells were drawn. So you can think of it

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<v Speaker 2>as like a mini model of a human organ made

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<v Speaker 2>from the cells that constitute that organ. You can make

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<v Speaker 2>stomach organoids, for example. You can make cardiac organoids. You

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<v Speaker 2>can make tear gland organoids, and you can make brain organoids.

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<v Speaker 1>The brain ones are the most fascinating ones, right?

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<v Speaker 2>The brain ones are very interesting, but let us not

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<v Speaker 2>forget the others.

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<v Speaker 1>We need all the organs.

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<v Speaker 2>We need all the organs and it's fascinating. I mean,

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<v Speaker 2>heart organoids will beat, you know, tear gland organoids will

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<v Speaker 2>cry and brain organoids will, I mean, I wouldn't say

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<v Speaker 2>they think, but they definitely create synaptic connections. They crackle

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<v Speaker 2>with all kinds of electrical activity. They form these basic

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<v Speaker 2>structures that are similar to like a fetal brain. They

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<v Speaker 2>do brain things just on a much, much smaller scale.

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<v Speaker 1>But you can take a skin cell and turn it

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<v Speaker 1>into a brain organoid?

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<v Speaker 2>You can take a skin cell and turn it into

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<v Speaker 2>a neuron and then put enough of those neurons together

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<v Speaker 2>in a little dish, keep them warm and happy and well-fed,

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<v Speaker 2>and they will do what cells do, which is just divide, multiply, cohere, aggregate,

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<v Speaker 2>and form these little structures. There's an upper ceiling on

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<v Speaker 2>how big they can get because they don't have vascular system.

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<v Speaker 2>They don't have veins. to kind of cycle nutrients in

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<v Speaker 2>and clear out toxins. So they can only grow to

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<v Speaker 2>about five millimeters in size before they develop what's called

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<v Speaker 2>a necrotic core and suffocate from the inside out. But

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<v Speaker 2>within that tiny scale, you can have like five million neurons.

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<v Speaker 2>And that's about the size of a bee's brain. So

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<v Speaker 2>you can do lots of really interesting neuroscience research and

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<v Speaker 2>pharmaceutical testing with just that.

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<v Speaker 1>What got you onto this story?

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<v Speaker 2>Oh, there was a big splashy, I mean, I'm following,

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<v Speaker 2>you know, all the publications within this sort of space

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<v Speaker 2>of the overlap of computation and biology. It's my beat.

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<v Speaker 2>I'm very interested in those places where technology touches life

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<v Speaker 2>and vice versa. I think that's where technology is headed

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<v Speaker 2>because I believe that there is a limit to what

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<v Speaker 2>we can do with silicon. And I think there's also

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<v Speaker 2>a limit to how much silicon there is left in

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<v Speaker 2>the world to build things with. I mean, We're literally

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<v Speaker 2>running out of sand. We're running out of minerals. These

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<v Speaker 2>things are not renewable. So I'm really interested in where

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<v Speaker 2>biology can come in and provide alternative ways of not

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<v Speaker 2>just thinking about technology, but also alternative substrates and ways

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<v Speaker 2>of building technology that is more resilient, more efficient, more

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<v Speaker 2>in line with how the world already works rather than

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<v Speaker 2>the sort of artificial construction we call computing. Anyway, that's

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<v Speaker 2>neither here nor there. I have been following this intersection

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<v Speaker 2>for a long time, and there was a big splashy

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<v Speaker 2>press push out of Johns Hopkins University a year and

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<v Speaker 2>a half ago, pushing forward this idea of what they

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<v Speaker 2>were calling organoid intelligence. So organoids have been around since

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<v Speaker 2>like the early 2000, 2008, 2009. And they've been a

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<v Speaker 2>staple of basic research. But all of a sudden, there

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<v Speaker 2>was this outpouring of research around like, how can we

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<v Speaker 2>connect these organoids to computer systems and do computer things

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<v Speaker 2>with them? And they were calling it organoid intelligence. They

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<v Speaker 2>were trying to make a big swing to kind of

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<v Speaker 2>name this field and bring a lot of talent to it. Yeah, OI.

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<v Speaker 3>OI.

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<v Speaker 2>So I was like, this is something interesting. I don't

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<v Speaker 2>know how much of this is hype, how much of

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<v Speaker 2>this is just scientists trying to get press and funding

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<v Speaker 2>by sucking on to the hype around AI, or how

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<v Speaker 2>much of it is actually really going to transform how

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<v Speaker 2>we think about computing. And that's, yeah, it just nagged

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<v Speaker 2>at me for a long time until I finally got

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<v Speaker 2>approval from my editors to go figure it out.

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<v Speaker 1>How are they actually used today? I mean, how much

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<v Speaker 1>of this is about the future where groups of brain

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<v Speaker 1>organoids can replace silicon-based chips to do computing, and how

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<v Speaker 1>much of it is more like these have a purpose

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<v Speaker 1>for drug testing or for other types of laboratory experiments?

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<v Speaker 1>What is the actual use case today, and where's it going?

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<v Speaker 2>Well, obviously, we're a very long way away from living

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<v Speaker 2>AI systems. And, you know, there's like in all kind

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<v Speaker 2>of biology and basic research, not an enormous amount of

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<v Speaker 2>funding in this space compared to the kinds of resources

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<v Speaker 2>that are being put towards silicon-based intelligence. But we are

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<v Speaker 2>making quite significant strides. So, I mean, currently the state

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<v Speaker 2>of the art is we can grow brain organoids very

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<v Speaker 2>consistently at scale. We can grow them directly onto microelectrode arrays.

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<v Speaker 2>I say we, I mean like humanity. Obviously, I'm not

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<v Speaker 2>doing this. Onto these kind of electrode arrays, and then

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<v Speaker 2>we can stimulate them with electricity because very conveniently the

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<v Speaker 2>human brain responds to electricity as do conventional computing components.

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<v Speaker 2>So we can stimulate these neurons and then they will

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<v Speaker 2>sort of respond in kind and we can measure those

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<v Speaker 2>responses and in that process develop a kind of rudimentary

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<v Speaker 2>form of programming. So there are a number of researchers

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<v Speaker 2>who are training neural systems, both three-dimensional organoids but also

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<v Speaker 2>flat two-dimensional neural cultures, to do basic tasks that would

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<v Speaker 2>normally be done by AI, things like image classification, text recognition.

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<v Speaker 2>There's a very splashy.

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<v Speaker 1>But that's not happening today already, right? Yeah, yeah, that's

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<v Speaker 1>totally doable.

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<v Speaker 2>It's just, it's inconsistent and slow.

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<v Speaker 1>Right.

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<v Speaker 2>But it is absolutely possible.

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<v Speaker 3>Wow.

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<v Speaker 2>Yeah. I mean, obviously, it's not like neurons are using

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<v Speaker 2>their eyeballs to look at pictures of text and saying this, this,

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<v Speaker 2>or this, but the text is being translated into electrical

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<v Speaker 2>signals and then fed to those organoids. The organoids are

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<v Speaker 2>responding in kind and translated back. So there's a movement

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<v Speaker 2>between analog and digital that happens, you know, with all biological... interfaces.

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<v Speaker 2>You have to move from our world of bits and

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<v Speaker 2>bytes to their world of biochemistry and electricity and back again.

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<v Speaker 2>But we're figuring out how to do that. So it

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<v Speaker 2>is possible to do that. There is a startup in Australia.

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<v Speaker 1>I like that you described our world from the point

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<v Speaker 1>of view of being a computer and their world from

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<v Speaker 1>the point of view of being an organoid.

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<v Speaker 2>Yeah, I mean, the thing that I.

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<v Speaker 1>They inverted us and them, human-machine paradox.

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<v Speaker 2>I know. Honestly, it's so disorienting thinking about this stuff because...

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<v Speaker 2>Our cells make us, right? I mean, we're all made

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<v Speaker 2>of millions and billions of cells, but also they are

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<v Speaker 2>perfectly happy living without us. You can take these neural cultures,

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<v Speaker 2>put them in a dish. If you keep them fed

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<v Speaker 2>and warm, they will just live essentially forever without any

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<v Speaker 2>intervention from us. Like if you make an organoid out

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<v Speaker 2>of your own skin, is it you or is it

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<v Speaker 2>not you anymore? There's this sort of autonomy that cells have.

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<v Speaker 2>And when you sort of separate them from the human

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<v Speaker 2>system and let them do their own thing, they have

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<v Speaker 2>their own kind of onboard capacities that are unrelated to

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<v Speaker 2>the organism they form at scale. It's kind of disorienting

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<v Speaker 2>ontologically and bizarre.

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<v Speaker 1>You had this great quote, brain organoids are creepy. They

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<v Speaker 1>muddy the line between person and thing, which is like

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<v Speaker 1>the difference between humans and animals or the living and

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<v Speaker 1>the dead. It's a fundamental distinction. The trend turns culture.

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<v Speaker 1>I thought it was a really fascinating way of putting it.

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<v Speaker 3>Yeah, yeah.

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<v Speaker 2>That's something that came from some sociological research on kind

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<v Speaker 2>of the way people respond to organoids. An interesting, I think,

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<v Speaker 2>actually consequence of this piece is when I was writing it,

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<v Speaker 2>I was talking to a lot of sociologists of science

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<v Speaker 2>and bioethicists who were really invested in the question of

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<v Speaker 2>brain organoids. And they all kind of more or less

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<v Speaker 2>told me, yeah, people don't think brain organoids are weird.

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<v Speaker 2>people understand that it's for the greater good. It's for science.

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<v Speaker 2>They're not unsettling. They're not eerie. They're not that strange.

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<v Speaker 2>There's not going to be a lot of pushback against

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<v Speaker 2>this technology when it makes the leap to computing because

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<v Speaker 2>people kind of understand biomedical research. Everybody was very confident

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<v Speaker 2>in that. And then I published this piece and the

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<v Speaker 2>response has been across the board, people being like, ah,

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<v Speaker 2>you know, freaking out and being kind of horrified on

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<v Speaker 2>some fundamental level about the idea of a computer having

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<v Speaker 2>some living cells in it, I think people find it

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<v Speaker 2>much more morally objectionable than I think the bioethicists would

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<v Speaker 2>be comfortable to admit. So that's been an interesting consequence.

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<v Speaker 1>Are they just small human brains?

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<v Speaker 2>Well, if you talk to anyone in this space and

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<v Speaker 2>you call these things mini brains, they get really touchy.

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<v Speaker 2>They go, these aren't mini brains. These aren't mini brains.

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<v Speaker 2>These aren't even brains. I mean, a human brain has

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<v Speaker 2>171 billion cells, including both neurons and glial cells, which

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<v Speaker 2>are kind of the scaffolding. An organoid has maybe five million.

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<v Speaker 2>There's an enormous difference in scale. And what makes a

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<v Speaker 2>brain a brain is, I mean, a subject of ongoing debate, obviously. But,

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<v Speaker 2>you know, there is the general consensus that some emerging

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<v Speaker 2>capacity comes at this scale that is maybe not legible

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<v Speaker 2>at such a small scale. There's also long been this

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<v Speaker 2>sort of ambivalence, I guess, or even like outright distaste

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<v Speaker 2>on the part of the scientific community for talking about

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<v Speaker 2>questions of consciousness or sentience or even really intelligence.

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<v Speaker 1>Not from the AI community.

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<v Speaker 2>Well, the AI community is all for it. They think

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<v Speaker 2>they're so ready to ascribe sentience to absolutely anything. you know,

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<v Speaker 2>put a couple googly eyes on a laptop and all

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<v Speaker 2>of a sudden it's a person.

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<v Speaker 1>Let me ask you about the headline of the piece,

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<v Speaker 1>AI is dead, organoids are alive. I mean, I guess

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<v Speaker 1>your editor chose the headline, but is that, what are

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<v Speaker 1>your thoughts on it?

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<v Speaker 2>I mean, I think there is something really interesting about

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<v Speaker 2>the way that neurons process information that silicon systems will

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<v Speaker 2>never be able to achieve. I mean, neurons have the

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<v Speaker 2>capacity to grow and prune their synapses based on their

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<v Speaker 2>experience of the world. I mean, In the case of

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<v Speaker 2>an organoid, that experience is electrical signals or maybe some

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<v Speaker 2>chemical stimulus in a dish. It's not the same thing

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<v Speaker 2>that we think of as experience at the human scale.

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<v Speaker 2>But it is like an embodied experience, an embedded experience

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<v Speaker 2>of the world. And some philosophers call that nano-intentionality. It's

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<v Speaker 2>essentially the idea that living matter can respond to its

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<v Speaker 2>environment in real time. and yeah i mean ai systems

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<v Speaker 2>even the most sophisticated ai systems they're still built on

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<v Speaker 2>these sort of static elements which are not you know

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<v Speaker 2>self-assembling they're not responsive to the world they're not uh embodied.

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<v Speaker 1>The chips aren't but the models are.

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<v Speaker 2>No yeah i suppose so i mean i just think

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<v Speaker 2>there's like a i don't know there's just like a

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<v Speaker 2>sort of fundamental i guess sort of philosophical distinction between

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<v Speaker 2>these substrates whether you want to call that dead versus

0:11:40.059 --> 0:11:43.040
<v Speaker 2>alive i mean that's an editorial choice but I mean,

0:11:43.059 --> 0:11:46.770
<v Speaker 2>I do think the comparison between, you know, rocks and cells,

0:11:46.790 --> 0:11:50.130
<v Speaker 2>because I mean, computers are just rocks, right? And cells

0:11:50.570 --> 0:11:51.490
<v Speaker 2>is an instructive one.

0:11:52.690 --> 0:11:55.729
<v Speaker 1>Talk about the experience of actually reporting the piece. I

0:11:55.750 --> 0:11:57.770
<v Speaker 1>want to know about your trip to the UC San

0:11:57.790 --> 0:12:00.320
<v Speaker 1>Diego Stem Cell Institute.

0:12:01.900 --> 0:12:04.540
<v Speaker 2>Yes. So I had a great fun reporting this piece,

0:12:04.740 --> 0:12:06.620
<v Speaker 2>although I will tell you that like all cell culture

0:12:06.660 --> 0:12:09.290
<v Speaker 2>labs pretty much look the same. You know, they're not

0:12:09.330 --> 0:12:12.230
<v Speaker 2>like full of like bubbling beakers and brains and jars

0:12:12.270 --> 0:12:15.290
<v Speaker 2>like you would imagine. You know, it's incubators that basically

0:12:15.309 --> 0:12:18.440
<v Speaker 2>look like mini fridges with trays and trays and trays

0:12:18.559 --> 0:12:21.480
<v Speaker 2>of these like nutrient wells that basically look like contact

0:12:21.520 --> 0:12:24.020
<v Speaker 2>lens solution and little globs floating in them. Those are

0:12:24.040 --> 0:12:27.260
<v Speaker 2>the organoids. You know, it's not hugely glamorous. At UCSD,

0:12:27.300 --> 0:12:30.620
<v Speaker 2>they do have some robots. So there are people there

0:12:30.640 --> 0:12:34.630
<v Speaker 2>who are working on organoid controlled robots, which is quite interesting.

0:12:34.650 --> 0:12:34.730
<v Speaker 3>Wow.

0:12:35.520 --> 0:12:37.540
<v Speaker 2>They're doing a lot of really kind of strange and

0:12:37.559 --> 0:12:41.860
<v Speaker 2>interesting work. They're, for example, creating genetically modified Neanderthal brain

0:12:41.920 --> 0:12:45.610
<v Speaker 2>organoids to understand the difference between human and Neanderthal brains.

0:12:45.780 --> 0:12:46.300
<v Speaker 1>Whoa.

0:12:46.330 --> 0:12:48.689
<v Speaker 2>How do they do that? I'm not entirely sure, to

0:12:48.730 --> 0:12:49.370
<v Speaker 2>be honest with you.

0:12:49.410 --> 0:12:52.830
<v Speaker 1>Are they from fossils? Are they sequenced DNA?

0:12:52.870 --> 0:12:55.589
<v Speaker 2>Yeah, I think they are just... you know what i

0:12:55.610 --> 0:12:56.750
<v Speaker 2>don't know i don't know 100 no but there's an

0:12:56.790 --> 0:12:59.630
<v Speaker 2>entire neanderthal organoid department within.

0:12:59.370 --> 0:13:02.970
<v Speaker 1>The ucsd stem cell research crazy.

0:13:02.530 --> 0:13:05.810
<v Speaker 2>Yeah they're also sending organoids to space to understand how

0:13:05.950 --> 0:13:09.670
<v Speaker 2>like radiation affects human astronaut brains i mean the thing

0:13:09.720 --> 0:13:13.220
<v Speaker 2>is that you know organoids provide a basis for studying

0:13:13.260 --> 0:13:15.080
<v Speaker 2>the brain in so many different ways i mean the

0:13:15.160 --> 0:13:17.740
<v Speaker 2>obviously the ai stuff is splashy and exciting and we

0:13:17.760 --> 0:13:20.750
<v Speaker 2>love robots and we love computers but We know very

0:13:20.790 --> 0:13:24.920
<v Speaker 2>little about how the human brain is even formed in utero.

0:13:25.120 --> 0:13:28.080
<v Speaker 2>Because of ethical guidelines on research, we don't really know

0:13:28.100 --> 0:13:30.800
<v Speaker 2>what happens after about 14 days. Between 14 days and

0:13:30.820 --> 0:13:33.339
<v Speaker 2>nine months, we have no idea how the human brain

0:13:33.380 --> 0:13:35.610
<v Speaker 2>comes together. Everything we know about it, we've learned from

0:13:35.640 --> 0:13:38.750
<v Speaker 2>analogy through studies of rats and fruit flies and stuff.

0:13:38.790 --> 0:13:42.489
<v Speaker 2>So an organoid, which is essentially like a fetal mini, mini,

0:13:42.530 --> 0:13:47.290
<v Speaker 2>mini brain, allows researchers to understand basic things about human

0:13:47.309 --> 0:13:49.030
<v Speaker 2>brain development. And that's a lot of what's being done

0:13:49.929 --> 0:13:53.460
<v Speaker 2>in that particular lab. It's like the study of human

0:13:53.480 --> 0:13:57.420
<v Speaker 2>brain development. And the AI organoid piece is just one

0:13:57.540 --> 0:13:59.840
<v Speaker 2>other way of getting at those questions. Because if you

0:13:59.860 --> 0:14:04.040
<v Speaker 2>can train, quote unquote, you know, a wired up organoid

0:14:04.200 --> 0:14:08.140
<v Speaker 2>to respond to certain electrical stimulus, to perform certain tasks,

0:14:08.280 --> 0:14:11.880
<v Speaker 2>for example, playing a simple video game, then you can,

0:14:12.460 --> 0:14:15.660
<v Speaker 2>you know, expose that organoid to different environmental factors, to

0:14:15.679 --> 0:14:19.840
<v Speaker 2>different toxins, to different pharmaceuticals. and understand how those things

0:14:19.900 --> 0:14:24.120
<v Speaker 2>affect that little nascent brain's capacity to respond to those tasks.

0:14:24.160 --> 0:14:28.550
<v Speaker 2>So it's another piece of a toolkit for understanding how

0:14:28.570 --> 0:14:29.230
<v Speaker 2>the brain works.

0:14:30.090 --> 0:14:31.990
<v Speaker 1>So who is Alison Mowatry?

0:14:32.530 --> 0:14:37.110
<v Speaker 2>Alison Mowatry? Alison Mowatry, yeah. He's a developmental biologist at UCSD.

0:14:37.230 --> 0:14:40.980
<v Speaker 2>He's a leading organoid researcher. He's part of the sort

0:14:41.000 --> 0:14:45.580
<v Speaker 2>of larger organoid intelligence effort or cohort, but he's fundamentally

0:14:45.680 --> 0:14:49.480
<v Speaker 2>more interested in things like autism, human brain development.

0:14:49.600 --> 0:14:50.720
<v Speaker 1>His son is autistic, right?

0:14:51.020 --> 0:14:54.040
<v Speaker 2>Yeah, his son is autistic. And he actually has created

0:14:54.160 --> 0:14:59.330
<v Speaker 2>organoids from his son's cells in order to understand how

0:14:59.350 --> 0:15:02.790
<v Speaker 2>his son's brain works, which is really fascinating to me.

0:15:02.830 --> 0:15:05.930
<v Speaker 2>And I asked him, is it weird to you to

0:15:06.290 --> 0:15:09.990
<v Speaker 2>be looking down a microscope at a miniature brain made

0:15:10.050 --> 0:15:12.740
<v Speaker 2>out of your own son? And he told me that

0:15:12.770 --> 0:15:14.960
<v Speaker 2>he has to kind of just disassociate in order to

0:15:15.640 --> 0:15:18.450
<v Speaker 2>do the research and not get too emotionally invested in it.

0:15:19.120 --> 0:15:21.700
<v Speaker 1>How did actually going to labs change your understanding of

0:15:21.720 --> 0:15:22.200
<v Speaker 1>the story?

0:15:22.700 --> 0:15:25.400
<v Speaker 2>I think the most beneficial thing for me about going

0:15:25.450 --> 0:15:27.130
<v Speaker 2>to a lab is actually being able to sit down

0:15:27.150 --> 0:15:29.010
<v Speaker 2>and talk to scientists face to face and get a

0:15:29.030 --> 0:15:32.850
<v Speaker 2>sense of their vibe. Because, I mean, I don't have

0:15:32.890 --> 0:15:36.790
<v Speaker 2>a background in neuroscience or computer science for that matter.

0:15:36.850 --> 0:15:38.600
<v Speaker 2>So there's only so much I can really get out

0:15:38.620 --> 0:15:42.380
<v Speaker 2>of reading academic papers. I mean, I try my darndest,

0:15:42.440 --> 0:15:43.960
<v Speaker 2>but at the end of the day, going up to

0:15:43.980 --> 0:15:45.840
<v Speaker 2>the scientists and saying, how exactly did you do this

0:15:46.020 --> 0:15:47.869
<v Speaker 2>and what does it mean? I mean, of course, I

0:15:47.930 --> 0:15:49.930
<v Speaker 2>ask all the important questions like, what happens if you

0:15:50.010 --> 0:15:55.590
<v Speaker 2>eat an organoid? And I think it was Alison Mowtri

0:15:55.610 --> 0:15:58.100
<v Speaker 2>who told me that nothing happens if you eat an organoid.

0:15:58.120 --> 0:16:00.420
<v Speaker 2>You'll just digest it. But if you are working in

0:16:00.500 --> 0:16:02.780
<v Speaker 2>a lab with an organoid that was made from your

0:16:02.960 --> 0:16:06.880
<v Speaker 2>own cells... That's extremely dangerous because if you get any

0:16:06.920 --> 0:16:09.310
<v Speaker 2>part of that organoid back in your body by accident,

0:16:09.350 --> 0:16:12.090
<v Speaker 2>your bloodstream, for example, through a cut or a lesion

0:16:12.110 --> 0:16:17.330
<v Speaker 2>of some kind, it will reenter your body, having developed

0:16:17.430 --> 0:16:20.350
<v Speaker 2>outside of your body, and it will start dividing and

0:16:20.390 --> 0:16:22.490
<v Speaker 2>multiplying and it could cause cancer because that's essentially what

0:16:22.530 --> 0:16:25.600
<v Speaker 2>cancer is, is cells going rogue and dividing and multiplying

0:16:26.130 --> 0:16:28.460
<v Speaker 2>outside of the multicellular project of the body. So it

0:16:28.480 --> 0:16:32.610
<v Speaker 2>will have become independent, returned within... And gone rogue, which

0:16:32.630 --> 0:16:36.980
<v Speaker 2>I think is just absolutely fascinating and strange. But yeah,

0:16:37.820 --> 0:16:39.360
<v Speaker 2>I mean, my favorite thing about this kind of research

0:16:39.400 --> 0:16:41.520
<v Speaker 2>is just going into labs and asking the wackiest questions

0:16:41.580 --> 0:16:44.180
<v Speaker 2>I could possibly think of to sort of throw these

0:16:44.220 --> 0:16:47.720
<v Speaker 2>people off balance. And also, you get really fascinating answers. That,

0:16:47.760 --> 0:16:52.020
<v Speaker 2>to me, is such a strange reality of cellular research.

0:16:52.420 --> 0:16:54.080
<v Speaker 2>You can't work with your own cells because they might

0:16:54.360 --> 0:16:55.060
<v Speaker 2>infect you.

0:16:55.680 --> 0:16:59.320
<v Speaker 1>Is mortuary making progress on the autism question?

0:17:00.160 --> 0:17:02.090
<v Speaker 2>Yeah, I think so. I mean, I think he's studying

0:17:03.180 --> 0:17:06.570
<v Speaker 2>how the development of an autistic organoid differs from a

0:17:06.590 --> 0:17:10.210
<v Speaker 2>neurotypical organoid. Obviously, it's a really complicated thing to entangle.

0:17:10.230 --> 0:17:13.429
<v Speaker 2>But yeah, I think he's definitely making progress, looking at

0:17:13.470 --> 0:17:16.230
<v Speaker 2>different kinds of therapies that might emerge from this. And

0:17:16.310 --> 0:17:19.189
<v Speaker 2>he seems very optimistic that he can make a real difference.

0:17:19.710 --> 0:17:22.750
<v Speaker 1>Who told you that you don't need permission to torture

0:17:22.770 --> 0:17:24.930
<v Speaker 1>as many flies as you want? And what does that mean?

0:17:26.490 --> 0:17:29.730
<v Speaker 2>That was this amazing sociologist, John Evans, who's also at UCSD.

0:17:30.500 --> 0:17:32.300
<v Speaker 2>who has made a career of like kind of being

0:17:32.320 --> 0:17:35.580
<v Speaker 2>a sociologist of biology and bioethics. So he was a

0:17:35.600 --> 0:17:38.490
<v Speaker 2>great outside observer to talk to about this stuff. Yeah.

0:17:38.590 --> 0:17:41.470
<v Speaker 2>What he was saying was basically that the regulation around

0:17:41.510 --> 0:17:44.070
<v Speaker 2>experimenting with this stuff is a little bit, it's a

0:17:44.070 --> 0:17:47.609
<v Speaker 2>little bit unclear. Like there are very specific roles about

0:17:47.730 --> 0:17:50.010
<v Speaker 2>working with different kinds of animal models, right? Like if

0:17:50.030 --> 0:17:52.510
<v Speaker 2>you're going to do experiments on rats or apes, like

0:17:52.550 --> 0:17:54.290
<v Speaker 2>you have to go through all these different, you know,

0:17:54.609 --> 0:17:57.469
<v Speaker 2>reporting guidelines and ethical guidelines and You know, there are

0:17:57.530 --> 0:18:00.449
<v Speaker 2>ways that you appropriately euthanize an animal after you work

0:18:00.490 --> 0:18:02.850
<v Speaker 2>with them, things like that. There's no such regulations in

0:18:02.869 --> 0:18:07.670
<v Speaker 2>place for organoids. They're kind of equivalent to working with invertebrates,

0:18:07.690 --> 0:18:10.800
<v Speaker 2>which is also kind of unregulated. I mean, that's changing

0:18:10.820 --> 0:18:14.520
<v Speaker 2>a little bit now because there's new research about like

0:18:15.140 --> 0:18:19.040
<v Speaker 2>pain reception and sentience in insects. But from a legal standpoint,

0:18:19.080 --> 0:18:21.540
<v Speaker 2>you don't need to get permission to, you know, torture

0:18:21.560 --> 0:18:23.500
<v Speaker 2>as many fruit flies as you want. That's why fruit

0:18:23.520 --> 0:18:25.970
<v Speaker 2>flies are very common. in biology labs. And it's the

0:18:26.010 --> 0:18:29.690
<v Speaker 2>same thing for organides right now. You don't necessarily need

0:18:30.270 --> 0:18:33.530
<v Speaker 2>legal approval. It's not understood that they feel pain, for example.

0:18:33.810 --> 0:18:38.050
<v Speaker 2>So there's no real concerns around that for now. But

0:18:38.130 --> 0:18:41.389
<v Speaker 2>these organides are getting more and more complex. And now

0:18:41.430 --> 0:18:45.190
<v Speaker 2>that we're connecting them to these electrode arrays and stimulating them,

0:18:45.430 --> 0:18:48.710
<v Speaker 2>you could make an argument that they're having experiences, which

0:18:49.350 --> 0:18:52.300
<v Speaker 2>has an effect on how we think about sentience and consciousness.

0:18:52.359 --> 0:18:54.220
<v Speaker 2>I mean, there are philosophers of mind who think that

0:18:54.280 --> 0:18:58.129
<v Speaker 2>these things sentience and consciousness are a consequence of experience,

0:18:58.890 --> 0:19:01.510
<v Speaker 2>of an embodied experience of the world. It's also possible

0:19:01.550 --> 0:19:03.650
<v Speaker 2>now to create what are called assembloids, which is where

0:19:03.690 --> 0:19:07.449
<v Speaker 2>you take organoid structures from different parts of the body

0:19:07.609 --> 0:19:09.510
<v Speaker 2>and kind of glob them together. So you can make

0:19:09.550 --> 0:19:11.830
<v Speaker 2>an organoid that can see, for example, or at least,

0:19:11.890 --> 0:19:14.950
<v Speaker 2>you know, perceive light. So there's different sort of forms

0:19:14.970 --> 0:19:17.470
<v Speaker 2>of input now that we can create. And those, I

0:19:17.520 --> 0:19:20.460
<v Speaker 2>think it's getting more and more kind of morally, or

0:19:20.480 --> 0:19:23.629
<v Speaker 2>not morally, but ethically gray. in terms of what we

0:19:23.650 --> 0:19:28.870
<v Speaker 2>feel is permissible to do with these little human-not-human cellular structures.

0:19:28.890 --> 0:19:39.100
<v Speaker 3>Can they learn, and what does it mean when they learn?

0:19:47.210 --> 0:19:50.330
<v Speaker 1>Can they learn? And what does it mean when they learn?

0:19:50.930 --> 0:19:52.760
<v Speaker 2>Yeah, they can learn for sure. You can kind of

0:19:53.060 --> 0:19:56.280
<v Speaker 2>train them. So actually the best, I think, research in

0:19:56.300 --> 0:19:59.780
<v Speaker 2>this comes out of this biocomputing startup in Melbourne called

0:19:59.800 --> 0:20:04.000
<v Speaker 2>Cortical Labs, who basically did a series of experiments that

0:20:04.020 --> 0:20:06.110
<v Speaker 2>have served as a proof of concept for how one

0:20:06.140 --> 0:20:10.290
<v Speaker 2>can program these systems. There's a theory in neuroscience called

0:20:10.310 --> 0:20:13.010
<v Speaker 2>the free energy principle. It's way above my pay grade,

0:20:13.070 --> 0:20:16.080
<v Speaker 2>but I can try in the simplest of terms. It's

0:20:16.119 --> 0:20:21.790
<v Speaker 2>essentially just the idea that self-organizing biological systems like predictable stimulus,

0:20:21.830 --> 0:20:26.610
<v Speaker 2>they will rearrange themselves to avoid chaos because that way

0:20:26.690 --> 0:20:30.600
<v Speaker 2>it is easier to anticipate and predict change. It takes

0:20:30.630 --> 0:20:34.260
<v Speaker 2>more energy to respond to a radically changed environment than

0:20:34.300 --> 0:20:37.020
<v Speaker 2>it does to one that is regularly stimulating. And so

0:20:37.580 --> 0:20:43.620
<v Speaker 2>you can essentially subject, expose neural cultures to chaotic stimulus

0:20:43.770 --> 0:20:45.350
<v Speaker 2>and they will do everything they can to avoid that.

0:20:45.369 --> 0:20:50.610
<v Speaker 2>So If you pair regularly spaced signals with an input

0:20:50.710 --> 0:20:53.250
<v Speaker 2>that you want, like for example, in the case of

0:20:53.710 --> 0:20:56.590
<v Speaker 2>this research, it was to play the video game Pong.

0:20:57.170 --> 0:21:02.629
<v Speaker 2>So if the electrical signals representing the ball hitting the

0:21:02.670 --> 0:21:06.709
<v Speaker 2>paddle are associated with some like regularly pulsing input, the

0:21:07.050 --> 0:21:10.709
<v Speaker 2>neurons will rearrange themselves in order to create that outcome

0:21:10.790 --> 0:21:13.850
<v Speaker 2>as much as possible. So you essentially reward them with

0:21:14.130 --> 0:21:17.030
<v Speaker 2>regular electrical stimulation. It's hard to say, like, do they

0:21:17.130 --> 0:21:20.950
<v Speaker 2>like that? Is it something that they enjoy? You know,

0:21:20.990 --> 0:21:25.260
<v Speaker 2>these kinds of words are ambiguous at best, but they

0:21:25.340 --> 0:21:28.460
<v Speaker 2>will certainly rearrange themselves to create those conditions. So that's

0:21:28.540 --> 0:21:30.920
<v Speaker 2>a kind of a proof of concept for this neuroscience theory.

0:21:30.980 --> 0:21:34.119
<v Speaker 2>It's also has proven to be a useful way of programming.

0:21:34.700 --> 0:21:37.320
<v Speaker 2>I'm told there are other ways that are being developed,

0:21:37.440 --> 0:21:40.840
<v Speaker 2>but it's really like very early days. And there are

0:21:40.859 --> 0:21:42.940
<v Speaker 2>a number of different companies now who are creating these

0:21:42.960 --> 0:21:46.869
<v Speaker 2>kind of networked organoid systems. So they have cultures of

0:21:46.950 --> 0:21:49.750
<v Speaker 2>organoids kept alive in these, you know, little kind of

0:21:49.830 --> 0:21:53.550
<v Speaker 2>biological computers. Those biological computers are connected to the internet,

0:21:54.190 --> 0:21:56.910
<v Speaker 2>you know, a neural server, if you will, which sounds

0:21:56.970 --> 0:21:59.429
<v Speaker 2>very sci-fi, but essentially what it means is that it

0:21:59.470 --> 0:22:01.869
<v Speaker 2>allows people who are wanting to work with organoids in

0:22:01.890 --> 0:22:04.040
<v Speaker 2>this capacity to do it remotely. It's kind of like

0:22:04.100 --> 0:22:06.780
<v Speaker 2>actually quite analogous to like the early days of, you know,

0:22:06.840 --> 0:22:10.880
<v Speaker 2>the internet when researchers wanted to access resources at computers

0:22:10.920 --> 0:22:13.660
<v Speaker 2>and different sites on the ARPANET, they would do that

0:22:13.760 --> 0:22:15.859
<v Speaker 2>remotely rather than having to like travel there and do it.

0:22:15.920 --> 0:22:20.080
<v Speaker 2>So There are now ways of remotely programming these systems

0:22:20.160 --> 0:22:22.119
<v Speaker 2>and studying their responses in all kinds of different ways.

0:22:22.140 --> 0:22:23.580
<v Speaker 2>So there's lots of different research being done all over

0:22:23.600 --> 0:22:29.110
<v Speaker 2>the world on these networked neural servers to essentially articulate

0:22:29.130 --> 0:22:34.010
<v Speaker 2>what the programming language of biology will be. And it's

0:22:34.190 --> 0:22:37.109
<v Speaker 2>as yet unknown. I mean, electrical signaling is definitely the

0:22:37.130 --> 0:22:39.350
<v Speaker 2>most efficient way, but there's also an enormous amount of

0:22:39.830 --> 0:22:42.699
<v Speaker 2>neurotransmitter chemicals in the human brain that neurons use to

0:22:42.720 --> 0:22:45.320
<v Speaker 2>communicate with each other. It's possible that we might be

0:22:45.340 --> 0:22:48.520
<v Speaker 2>able to do so chemically. That's a little bit slower

0:22:48.580 --> 0:22:50.699
<v Speaker 2>and more diffuse, but there could be applications for that

0:22:50.740 --> 0:22:51.000
<v Speaker 2>as well.

0:22:51.560 --> 0:22:54.500
<v Speaker 1>And you did this, right? I mean, you interacted with

0:22:54.520 --> 0:22:55.780
<v Speaker 1>organoids over the internet.

0:22:56.359 --> 0:23:00.260
<v Speaker 2>Yeah, I played Pong with some neural cultures online. I know,

0:23:00.300 --> 0:23:02.120
<v Speaker 2>it's pretty wild. I mean, I needed to be walked

0:23:02.180 --> 0:23:04.639
<v Speaker 2>through it by, you know, an engineer at this company

0:23:04.680 --> 0:23:07.550
<v Speaker 2>because these neural cultures are addressable in Python. So there

0:23:07.590 --> 0:23:10.650
<v Speaker 2>is some programming. It's not like you're just playing online,

0:23:10.770 --> 0:23:12.730
<v Speaker 2>you know, as you would like any kind of online game.

0:23:13.300 --> 0:23:16.879
<v Speaker 2>But yeah, you run them through these trials repeatedly and

0:23:16.960 --> 0:23:18.899
<v Speaker 2>over time they get better and better at hitting the

0:23:18.920 --> 0:23:24.240
<v Speaker 2>paddle back and rallying. And over time, yeah, they improve.

0:23:24.840 --> 0:23:26.530
<v Speaker 2>They're not very good at it. They're still not very

0:23:26.570 --> 0:23:28.990
<v Speaker 2>good at it. And they can play Doom now. That

0:23:29.010 --> 0:23:31.570
<v Speaker 2>was like a big viral news story some months ago.

0:23:32.190 --> 0:23:36.850
<v Speaker 2>Similar technique, just more complex input. They're also not very

0:23:36.890 --> 0:23:39.310
<v Speaker 2>good at that either, but they can do it. And

0:23:39.350 --> 0:23:41.150
<v Speaker 2>that's really like a starting point.

0:23:41.890 --> 0:23:44.230
<v Speaker 1>Was it uncanny for you? Or was it like you're

0:23:44.260 --> 0:23:46.139
<v Speaker 1>in a Waymo and it's sort of uncanny for the

0:23:46.200 --> 0:23:48.740
<v Speaker 1>first 20 seconds and then you go back on your phone?

0:23:48.780 --> 0:23:51.619
<v Speaker 1>What was the personal experience for you of interacting with

0:23:51.640 --> 0:23:52.500
<v Speaker 1>these organoids?

0:23:53.160 --> 0:23:57.330
<v Speaker 2>It's very surreal because I just felt this weird burden

0:23:57.350 --> 0:24:00.690
<v Speaker 2>of responsibility. I mean, I had access to this beta

0:24:01.109 --> 0:24:05.090
<v Speaker 2>server system where you could control all the environmental factors.

0:24:05.130 --> 0:24:08.700
<v Speaker 2>You could control the CO2 balance and the temperature of

0:24:09.310 --> 0:24:11.310
<v Speaker 2>the server in which the neurons were being held. And

0:24:11.330 --> 0:24:12.869
<v Speaker 2>I was highly conscious of the fact that if I

0:24:12.910 --> 0:24:14.870
<v Speaker 2>just like clicked in the wrong place, I might kill them.

0:24:15.450 --> 0:24:18.090
<v Speaker 2>And that is something that, I mean, I say this

0:24:18.109 --> 0:24:20.409
<v Speaker 2>in the piece, but it's, that's a new paradigm in computing.

0:24:20.430 --> 0:24:22.630
<v Speaker 2>Like you don't normally expect when you do something wrong

0:24:22.670 --> 0:24:25.359
<v Speaker 2>on a computer that something dies as a consequence of

0:24:25.390 --> 0:24:30.959
<v Speaker 2>that error. And I don't know, I felt very, I was,

0:24:30.980 --> 0:24:33.280
<v Speaker 2>I was treading very carefully. I felt like a bull

0:24:33.320 --> 0:24:35.640
<v Speaker 2>in a China shop. You know, I was like, I just,

0:24:36.080 --> 0:24:38.990
<v Speaker 2>I want to make sure these organoids stay safe and

0:24:39.030 --> 0:24:41.629
<v Speaker 2>happy in their little in their little petri dish in

0:24:41.690 --> 0:24:45.210
<v Speaker 2>australia yeah strange it's a it's a strange feeling to

0:24:45.260 --> 0:24:48.659
<v Speaker 2>interact with something alive online i mean i suppose it's

0:24:48.680 --> 0:24:51.580
<v Speaker 2>not the first time i suppose like webcams of nature

0:24:51.600 --> 0:24:53.820
<v Speaker 2>you know you have like these portals into the living

0:24:53.859 --> 0:24:55.800
<v Speaker 2>world but so rarely do you have the capacity to

0:24:55.880 --> 0:24:59.950
<v Speaker 2>actually physically interact with something that is if not sentient

0:24:59.990 --> 0:25:01.350
<v Speaker 2>then alive.

0:25:01.990 --> 0:25:06.110
<v Speaker 1>Is the melbourne is that where cl1 is yes yes

0:25:06.750 --> 0:25:10.119
<v Speaker 1>and one of the creators of CL1 said CL1 is

0:25:10.140 --> 0:25:14.530
<v Speaker 1>the theoretical neuroscience as the Large Hadron Collider was the

0:25:14.590 --> 0:25:16.170
<v Speaker 1>theoretical physics. What does that mean?

0:25:16.670 --> 0:25:18.490
<v Speaker 2>Yeah, I mean, that's kind of that thing I was

0:25:18.530 --> 0:25:21.109
<v Speaker 2>talking about earlier about how they figured out a way

0:25:21.130 --> 0:25:23.929
<v Speaker 2>to program these neurons based on the theory of the

0:25:23.970 --> 0:25:28.560
<v Speaker 2>free energy principle, which is this neuroscience theory that they

0:25:28.580 --> 0:25:33.699
<v Speaker 2>essentially tested in silico, in utero in silico. I don't

0:25:33.720 --> 0:25:35.320
<v Speaker 2>even really know how you would describe what it is.

0:25:35.440 --> 0:25:37.180
<v Speaker 2>But I mean, yeah, they were able to kind of

0:25:37.720 --> 0:25:41.600
<v Speaker 2>take an idea from theoretical neuroscience, translate it into a

0:25:41.640 --> 0:25:45.399
<v Speaker 2>series of commands, interact directly with the living system, and

0:25:45.440 --> 0:25:47.379
<v Speaker 2>then see that that theory was in fact true. So

0:25:47.420 --> 0:25:50.609
<v Speaker 2>that was a way of using the CL1 to test

0:25:51.180 --> 0:25:54.429
<v Speaker 2>basic neuroscience theories, which is really, I think, exciting for

0:25:54.450 --> 0:25:56.909
<v Speaker 2>a lot of people. It's a little bit grand of

0:25:56.930 --> 0:26:00.450
<v Speaker 2>a claim, of course, but I don't think it's incorrect.

0:26:00.690 --> 0:26:06.649
<v Speaker 2>These are self-contained systems for testing theories of mind. It's

0:26:06.690 --> 0:26:08.840
<v Speaker 2>truly wild. And it's so interesting to talk to these

0:26:08.859 --> 0:26:12.100
<v Speaker 2>people because they have actually like a, you know, I

0:26:12.140 --> 0:26:14.880
<v Speaker 2>think some of the response to the Wired piece from

0:26:14.920 --> 0:26:17.859
<v Speaker 2>the general readership was kind of like, this is unholy.

0:26:17.900 --> 0:26:20.640
<v Speaker 2>These people have no respect for life. You know, there's

0:26:20.680 --> 0:26:23.140
<v Speaker 2>a sacred spark in the human mind and we are

0:26:23.800 --> 0:26:28.780
<v Speaker 2>befouling it by putting it in computers and instrumentalizing it

0:26:28.840 --> 0:26:31.459
<v Speaker 2>or objectifying it. And I think all of that is

0:26:32.270 --> 0:26:35.480
<v Speaker 2>absolutely valid and based on the track record of biomedical

0:26:35.500 --> 0:26:38.560
<v Speaker 2>industry and the tech industry a very fair assessment. But

0:26:38.619 --> 0:26:40.980
<v Speaker 2>I did find that talking to these people, they're all

0:26:41.000 --> 0:26:46.780
<v Speaker 2>incredibly sincere about wanting to understand how intelligence works, wanting

0:26:46.820 --> 0:26:50.879
<v Speaker 2>to understand the secrets of biology in a kind of

0:26:51.140 --> 0:26:54.700
<v Speaker 2>synthetic and constructive manner. I think the history of biology

0:26:54.740 --> 0:26:58.030
<v Speaker 2>has been, it's a very reductive science. Scientists have tried

0:26:58.070 --> 0:27:01.260
<v Speaker 2>to like understand all the little tiny pieces and how

0:27:01.300 --> 0:27:04.220
<v Speaker 2>they fit together. There's been this belief for a long

0:27:04.240 --> 0:27:06.400
<v Speaker 2>time that if we could just look in a microscope

0:27:06.440 --> 0:27:09.850
<v Speaker 2>small enough, we'll see how it all works. And at

0:27:09.890 --> 0:27:11.670
<v Speaker 2>the end of the day, there's certain things you can

0:27:11.730 --> 0:27:14.230
<v Speaker 2>only understand through building. You can only understand in a

0:27:14.250 --> 0:27:16.350
<v Speaker 2>kind of synthetic way. And in a way, I think

0:27:17.070 --> 0:27:20.330
<v Speaker 2>these people are putting together these systems and they're developing

0:27:20.369 --> 0:27:25.659
<v Speaker 2>a knowledge of fundamental underlying structure of intelligence that they

0:27:25.680 --> 0:27:27.679
<v Speaker 2>could only really get by doing what it is that

0:27:27.720 --> 0:27:30.970
<v Speaker 2>they're doing. Now, what comes next, you know, 10 years

0:27:31.010 --> 0:27:33.110
<v Speaker 2>from now, 20 years from now, how comfortable we may

0:27:33.590 --> 0:27:38.300
<v Speaker 2>be or not be with living systems? Those are other questions.

0:27:38.340 --> 0:27:40.280
<v Speaker 2>But right now, at least, I feel like a lot

0:27:40.300 --> 0:27:41.980
<v Speaker 2>of the stuff is just driven by a genuine desire

0:27:42.000 --> 0:27:45.300
<v Speaker 2>to understand intelligence and a genuine respect for the complexity

0:27:45.340 --> 0:27:48.600
<v Speaker 2>of biological intelligence. I mean, a lot of these people,

0:27:49.160 --> 0:27:53.060
<v Speaker 2>they're building these hybrid computational living systems, but they know

0:27:53.140 --> 0:27:58.679
<v Speaker 2>that AI, as it's currently instantiated, is fairly limited. It's

0:27:58.720 --> 0:28:02.080
<v Speaker 2>trying to emulate something that is so much more complex

0:28:02.160 --> 0:28:07.439
<v Speaker 2>than most engineers are willing to acknowledge. And only by

0:28:08.570 --> 0:28:11.350
<v Speaker 2>starting to kind of work with those living materials are

0:28:11.369 --> 0:28:15.669
<v Speaker 2>they really coming to understand just how much biology is

0:28:15.710 --> 0:28:18.810
<v Speaker 2>doing that we aren't even conscious of or capturing or

0:28:19.369 --> 0:28:21.649
<v Speaker 2>even close to modeling in synthetic systems.

0:28:23.170 --> 0:28:28.310
<v Speaker 1>But is the Holy Grail to replace silicon computing with

0:28:29.030 --> 0:28:32.390
<v Speaker 1>neural computing or organoid-based computing because it's so much more

0:28:33.030 --> 0:28:35.950
<v Speaker 1>energy efficient? Or is the holy grail to actually truly

0:28:35.970 --> 0:28:38.430
<v Speaker 1>understand how the human brain works?

0:28:39.170 --> 0:28:43.229
<v Speaker 2>Can't it be both? No, I don't know. I mean,

0:28:43.250 --> 0:28:45.370
<v Speaker 2>I think different people have different intentions. And that was

0:28:45.390 --> 0:28:47.690
<v Speaker 2>something that was really clarifying about reporting the piece is that,

0:28:48.380 --> 0:28:50.220
<v Speaker 2>you know, I talked to a lot of different scientists.

0:28:50.240 --> 0:28:52.320
<v Speaker 2>Some of them, you know, they're interested in this stuff

0:28:52.360 --> 0:28:54.140
<v Speaker 2>because they want to understand how the brain works, how

0:28:54.160 --> 0:28:57.120
<v Speaker 2>the brain is formed. Others want the stuff to work

0:28:57.160 --> 0:29:01.320
<v Speaker 2>so that they can do more accurate Alzheimer's research or

0:29:01.480 --> 0:29:05.530
<v Speaker 2>test pharmaceuticals. Some of them are interested in the computational questions.

0:29:05.590 --> 0:29:07.910
<v Speaker 2>I mean, there's a wide kind of gamut of approaches.

0:29:08.510 --> 0:29:11.170
<v Speaker 2>But I do think that's all kind of grounded in

0:29:11.190 --> 0:29:15.930
<v Speaker 2>a healthy respect for the complexity of life. For some,

0:29:15.990 --> 0:29:18.270
<v Speaker 2>I think, yes, the end goal is to create AI

0:29:18.310 --> 0:29:22.890
<v Speaker 2>systems with living materials that are competitive with AI systems

0:29:23.630 --> 0:29:27.110
<v Speaker 2>made from silicon. I think everyone is conscious that that's

0:29:27.120 --> 0:29:30.090
<v Speaker 2>a very, very long way away. And in a way,

0:29:30.130 --> 0:29:32.170
<v Speaker 2>sometimes the more we learn about biology, the more we

0:29:32.190 --> 0:29:35.350
<v Speaker 2>realize that we have yet to learn. So I think

0:29:35.370 --> 0:29:39.370
<v Speaker 2>they're all humbled by that. But the hope is perhaps that, yeah,

0:29:39.390 --> 0:29:40.920
<v Speaker 2>both those things can be true that we can build

0:29:41.020 --> 0:29:43.920
<v Speaker 2>computer systems and in the process learn a lot about

0:29:43.960 --> 0:29:45.010
<v Speaker 2>how intelligence works.

0:29:46.430 --> 0:29:49.470
<v Speaker 1>Can you kind of help me understand the difference between

0:29:49.650 --> 0:29:53.130
<v Speaker 1>what the researchers hope will eventually happen and what's actually

0:29:53.150 --> 0:29:55.500
<v Speaker 1>been demonstrated with organoids to date.

0:29:57.610 --> 0:30:00.530
<v Speaker 2>Yes. Well, I mean, to be fair, I think a

0:30:00.610 --> 0:30:03.380
<v Speaker 2>lot of the researchers are pretty measured in their estimations.

0:30:03.410 --> 0:30:05.640
<v Speaker 2>And in my experience of talking to biologists is that

0:30:05.680 --> 0:30:07.940
<v Speaker 2>they're really any scientists is that they're quite reticent to

0:30:07.960 --> 0:30:10.860
<v Speaker 2>be speculative about these things. I mean, they have ideas

0:30:10.920 --> 0:30:13.880
<v Speaker 2>about what questions would be cool to ask and what

0:30:13.920 --> 0:30:15.480
<v Speaker 2>things they think are going to get them funding. But

0:30:15.690 --> 0:30:17.830
<v Speaker 2>none of them is walking around saying, like, in the future,

0:30:17.890 --> 0:30:19.830
<v Speaker 2>computers are going to be made out of brains and

0:30:20.030 --> 0:30:21.630
<v Speaker 2>it's going to be impossible to tell the difference between

0:30:21.670 --> 0:30:25.200
<v Speaker 2>computers and people or whatever. Nobody's making those claims. they're

0:30:25.220 --> 0:30:28.150
<v Speaker 2>making much more prescribed and limited claims. So there's not

0:30:28.190 --> 0:30:32.610
<v Speaker 2>an enormous gap, frankly. I mean, they're interested in, yeah,

0:30:32.670 --> 0:30:37.430
<v Speaker 2>being able to use these computing organoid systems to ask

0:30:37.470 --> 0:30:42.100
<v Speaker 2>more pointed questions within their own realms of research, if

0:30:42.120 --> 0:30:44.820
<v Speaker 2>that makes sense. But I think all the grand claims

0:30:44.880 --> 0:30:48.780
<v Speaker 2>come from, you know, the university PR departments and the

0:30:48.820 --> 0:30:52.740
<v Speaker 2>journalists and the people like us who want to kind

0:30:52.820 --> 0:30:54.650
<v Speaker 2>of look at this stuff and go, oh, this is

0:30:54.670 --> 0:30:57.130
<v Speaker 2>where it's headed rather than kind of sit with the

0:30:57.150 --> 0:30:58.630
<v Speaker 2>complexity of where it is.

0:30:59.150 --> 0:31:00.930
<v Speaker 1>And one of the biggest obstacles is blood.

0:31:01.570 --> 0:31:01.810
<v Speaker 3>Yes.

0:31:02.270 --> 0:31:05.390
<v Speaker 2>Blood is really important. Vascularization is really important. There's an

0:31:06.090 --> 0:31:08.430
<v Speaker 2>upper ceiling for how big an organoid can get because

0:31:08.470 --> 0:31:11.780
<v Speaker 2>they don't have circulatory systems. They don't have veins. They

0:31:11.820 --> 0:31:15.460
<v Speaker 2>have no way of filtering out toxins and bringing in nutrients.

0:31:15.560 --> 0:31:20.180
<v Speaker 2>So there's some like Preliminary research being done now in

0:31:20.320 --> 0:31:23.400
<v Speaker 2>kind of artificial perfusion systems, you know, building these like

0:31:23.820 --> 0:31:28.250
<v Speaker 2>tiny microfluidic networks to kind of circulate nutrients throughout the

0:31:28.310 --> 0:31:31.050
<v Speaker 2>inside of the organoid. There are people who are building

0:31:31.550 --> 0:31:35.290
<v Speaker 2>vascular organoids, so like making organoids from like vein cells

0:31:35.430 --> 0:31:39.010
<v Speaker 2>to create these kind of rudimentary vascular structures. So we'll

0:31:39.050 --> 0:31:43.440
<v Speaker 2>probably break past that threshold in some way or another soon.

0:31:43.580 --> 0:31:46.880
<v Speaker 2>But for the time being... Yeah, they die after a

0:31:46.900 --> 0:31:49.440
<v Speaker 2>certain size because the cells on the inside of the

0:31:49.480 --> 0:31:53.200
<v Speaker 2>organoid suffocate without access to nutrients.

0:31:53.680 --> 0:31:54.770
<v Speaker 1>And what are the other big obstacles?

0:31:56.390 --> 0:31:59.090
<v Speaker 2>Funding, always, especially in the US.

0:32:00.230 --> 0:32:02.730
<v Speaker 1>So there hasn't been a rush of capital around the

0:32:02.770 --> 0:32:04.590
<v Speaker 1>AI stuff that's also funded a lot of this?

0:32:05.130 --> 0:32:07.110
<v Speaker 2>I didn't get the impression that there has been, no.

0:32:07.630 --> 0:32:11.410
<v Speaker 2>I mean, there are some startups in this space. there's

0:32:11.430 --> 0:32:13.630
<v Speaker 2>this company in Australia, there's a company in Switzerland that's

0:32:13.670 --> 0:32:18.300
<v Speaker 2>doing this. I think they are relatively well capitalized, but

0:32:18.320 --> 0:32:22.980
<v Speaker 2>not on the scale of like literally any AI company. Funding,

0:32:23.240 --> 0:32:26.740
<v Speaker 2>you know, within the kind of biomedical research context, basic

0:32:26.780 --> 0:32:31.360
<v Speaker 2>research is a real struggle right now in the US, obviously.

0:32:31.980 --> 0:32:36.910
<v Speaker 2>There is, however, like a turn towards organoid-based research in

0:32:36.950 --> 0:32:39.810
<v Speaker 2>the US because of a movement away from animal research models.

0:32:39.850 --> 0:32:42.530
<v Speaker 2>So the NIH just like basically said that it wouldn't

0:32:42.570 --> 0:32:47.850
<v Speaker 2>approve any grants that didn't include a like organoid type

0:32:47.930 --> 0:32:48.870
<v Speaker 2>system wow.

0:32:48.610 --> 0:32:51.390
<v Speaker 1>It's a big stimulus yeah because there's.

0:32:51.250 --> 0:32:55.810
<v Speaker 2>Just been this general kind of political and sociocultural move

0:32:55.850 --> 0:32:58.780
<v Speaker 2>away from animal testing which i mean organoids are great

0:32:58.800 --> 0:33:02.840
<v Speaker 2>in that regard because you know most especially like neurochemical

0:33:03.220 --> 0:33:07.000
<v Speaker 2>drugs uh psychiatric drugs fail in human trials because they're

0:33:07.020 --> 0:33:10.040
<v Speaker 2>tested on rats and you know rats don't get depressed

0:33:10.100 --> 0:33:12.300
<v Speaker 2>as far as we know so there is a limit

0:33:12.440 --> 0:33:15.260
<v Speaker 2>to what we can learn from animal models. And organoids

0:33:15.400 --> 0:33:19.459
<v Speaker 2>tend to be like a lot more representative chemically and

0:33:19.760 --> 0:33:22.500
<v Speaker 2>molecularly of what's happening in the human brain. So that's

0:33:22.540 --> 0:33:24.460
<v Speaker 2>a good thing. But yeah, I mean, funding is always

0:33:24.480 --> 0:33:29.860
<v Speaker 2>a constraint. I think, you know, the ethical questions are constraining.

0:33:29.900 --> 0:33:31.960
<v Speaker 2>I think for like basic organoid research, not so much,

0:33:32.020 --> 0:33:34.880
<v Speaker 2>but for this kind of computational stuff, I think there

0:33:34.940 --> 0:33:38.870
<v Speaker 2>is a lot of trepidation A lot of the, like

0:33:38.890 --> 0:33:41.830
<v Speaker 2>the Johns Hopkins team, for example, works with embedded ethicists

0:33:41.970 --> 0:33:43.510
<v Speaker 2>and is always touting the fact that they work with

0:33:43.550 --> 0:33:46.410
<v Speaker 2>embedded ethicists because I think they're sensitive to the fact

0:33:46.450 --> 0:33:49.080
<v Speaker 2>that people might get kind of squicked out by this

0:33:49.120 --> 0:33:53.620
<v Speaker 2>stuff and that could imperil their position. And so they

0:33:53.660 --> 0:33:56.940
<v Speaker 2>take everything really incrementally and, you know, they have regular

0:33:56.960 --> 0:33:59.280
<v Speaker 2>meetings between the people who are working in the wet

0:33:59.320 --> 0:34:01.800
<v Speaker 2>labs and the people who have, you know, who are

0:34:01.820 --> 0:34:05.660
<v Speaker 2>asking these kind of ethical sociological questions. They're very earnest

0:34:05.700 --> 0:34:08.160
<v Speaker 2>about that. It seems that they very much enjoy these

0:34:08.200 --> 0:34:12.770
<v Speaker 2>conversations and have this kind of constructive way of approaching it.

0:34:13.000 --> 0:34:15.540
<v Speaker 2>That being said, I mean, the bioethicists, you know, they're

0:34:15.560 --> 0:34:19.180
<v Speaker 2>embedded within these same biomedical institutions. So they might not

0:34:19.219 --> 0:34:22.000
<v Speaker 2>have the most clear outside perspective on how people in

0:34:22.020 --> 0:34:23.520
<v Speaker 2>the real world are going to respond to these things.

0:34:24.280 --> 0:34:25.470
<v Speaker 2>So that's a limitation for sure.

0:34:25.489 --> 0:34:25.569
<v Speaker 3>Yeah.

0:34:28.270 --> 0:34:29.450
<v Speaker 2>Those are the major ones, I would say.

0:34:30.489 --> 0:34:33.330
<v Speaker 1>Just before we wrap, can you quickly explain the nature

0:34:33.350 --> 0:34:39.489
<v Speaker 1>of consciousness and how... i have to ask you the

0:34:39.510 --> 0:34:41.870
<v Speaker 1>consciousness question yeah.

0:34:41.690 --> 0:34:43.630
<v Speaker 2>I mean the consciousness question is the question right and

0:34:43.670 --> 0:34:45.570
<v Speaker 2>it's one that absolutely none of the scientists want to

0:34:45.610 --> 0:34:48.330
<v Speaker 2>talk about i mean every single scientist i asked it's

0:34:48.350 --> 0:34:50.350
<v Speaker 2>like i was very careful to ask that question last

0:34:50.390 --> 0:34:52.549
<v Speaker 2>after i had proved my competency and all the kind

0:34:52.570 --> 0:34:55.739
<v Speaker 2>of bio biomedical aspects of this because they really don't

0:34:55.760 --> 0:34:58.420
<v Speaker 2>like talking about it not because they're not interested or

0:34:58.460 --> 0:35:00.540
<v Speaker 2>they don't like believe it's important because i think it's

0:35:00.719 --> 0:35:02.660
<v Speaker 2>all anyone ever asked them about you know and i

0:35:02.700 --> 0:35:07.000
<v Speaker 2>think they have a very different understanding of what consciousness is.

0:35:07.620 --> 0:35:11.680
<v Speaker 2>They're much more reluctant to label anything as being conscious

0:35:11.719 --> 0:35:15.310
<v Speaker 2>because they, I don't know, I think they work with

0:35:15.710 --> 0:35:17.270
<v Speaker 2>living matter all the time. They work with cells all

0:35:17.290 --> 0:35:20.730
<v Speaker 2>the time. They know what cells can do and can't do.

0:35:21.070 --> 0:35:24.390
<v Speaker 2>They're not precious about it. But yeah, I think the

0:35:24.410 --> 0:35:27.660
<v Speaker 2>question is they're, you know, somewhere between 5 million cells

0:35:27.719 --> 0:35:32.100
<v Speaker 2>and 170 billion cells, like something happens, right? Something called

0:35:32.140 --> 0:35:37.290
<v Speaker 2>consciousness dies. emerges. Whether that's possible in a dish alone

0:35:37.390 --> 0:35:40.830
<v Speaker 2>without external stimulus from the world, without an embodied experience

0:35:40.870 --> 0:35:43.990
<v Speaker 2>of the world, without parents or an upbringing or relation

0:35:44.070 --> 0:35:48.250
<v Speaker 2>with other animals and people and sensory experience, whether that's

0:35:48.830 --> 0:35:53.469
<v Speaker 2>possible in isolation is like an open question in philosophy

0:35:53.570 --> 0:35:57.440
<v Speaker 2>and in biology. Nobody really knows. I think a lot

0:35:57.460 --> 0:36:00.340
<v Speaker 2>of the reluctance that I encountered with talking to biologists

0:36:00.360 --> 0:36:04.469
<v Speaker 2>about this question is that there's no like quantifiable definition

0:36:04.570 --> 0:36:07.290
<v Speaker 2>of consciousness. You know, it's something we've been debating since

0:36:07.350 --> 0:36:11.830
<v Speaker 2>ancient times and nobody really knows how to name it.

0:36:12.090 --> 0:36:14.089
<v Speaker 2>And that makes it really difficult to say whether something

0:36:14.150 --> 0:36:17.310
<v Speaker 2>is conscious or not conscious. I mean, for example, an

0:36:17.350 --> 0:36:19.250
<v Speaker 2>organoid is about the size of a bee's brain. Do

0:36:19.270 --> 0:36:21.900
<v Speaker 2>you think of a bee as a sentient organism, a

0:36:21.940 --> 0:36:26.739
<v Speaker 2>conscious organism? Even within science, there's a huge gamma of

0:36:27.800 --> 0:36:30.759
<v Speaker 2>responses to that question. I personally would think a bee

0:36:30.820 --> 0:36:34.290
<v Speaker 2>is sentient. but others might not. So where we draw

0:36:34.310 --> 0:36:41.000
<v Speaker 2>those lines is ultimately quite personal and socially prescribed and philosophical,

0:36:41.260 --> 0:36:43.799
<v Speaker 2>and it's going to make it really difficult to guide

0:36:43.840 --> 0:36:47.940
<v Speaker 2>this research ethically. I mean, I think everybody's keen to

0:36:48.300 --> 0:36:50.739
<v Speaker 2>err on the side of caution with this stuff, but

0:36:51.940 --> 0:36:54.800
<v Speaker 2>it does feel inevitable that at some point along the road,

0:36:55.489 --> 0:36:59.219
<v Speaker 2>as these things get older, more mature, more complex, As

0:36:59.260 --> 0:37:04.290
<v Speaker 2>we start stimulating them and giving them sensory experience, some

0:37:04.370 --> 0:37:08.650
<v Speaker 2>thresholds will be crossed. And in the absence of any

0:37:08.670 --> 0:37:14.509
<v Speaker 2>way to infer conscious experience from the outside, we have

0:37:14.530 --> 0:37:17.920
<v Speaker 2>to be very careful. For the time being, I don't know.

0:37:18.200 --> 0:37:20.480
<v Speaker 2>I really don't know. It does seem to me, though,

0:37:20.540 --> 0:37:27.600
<v Speaker 2>that when you are giving these cells experience, you're putting

0:37:27.620 --> 0:37:31.080
<v Speaker 2>them well on the path towards something like consciousness even

0:37:31.120 --> 0:37:34.460
<v Speaker 2>if it's like a micro shade of that it's got

0:37:34.480 --> 0:37:37.399
<v Speaker 2>to be a piece of that puzzle and.

0:37:37.380 --> 0:37:39.580
<v Speaker 1>One of the most fascinating things in your piece i

0:37:39.620 --> 0:37:45.279
<v Speaker 1>think is that these organoids and cells their primary motivation

0:37:45.320 --> 0:37:47.040
<v Speaker 1>is to connect apparently.

0:37:47.600 --> 0:37:51.100
<v Speaker 2>Yeah yeah well neurons that's what they do right they

0:37:51.360 --> 0:37:54.120
<v Speaker 2>forge connections with each other every neuron has many many

0:37:54.140 --> 0:37:57.640
<v Speaker 2>connections with every other neuron it's it's their cellular imperative

0:37:57.760 --> 0:38:00.950
<v Speaker 2>so you put them together That's what they do. They

0:38:01.010 --> 0:38:06.330
<v Speaker 2>form these kinds of aggregations in the absence of a body,

0:38:06.370 --> 0:38:08.160
<v Speaker 2>in the absence of a brain, they'll still do what

0:38:08.180 --> 0:38:11.340
<v Speaker 2>they do. And I find that really beautiful. Like the

0:38:11.380 --> 0:38:14.819
<v Speaker 2>fact that all of our cells have these, I mean,

0:38:14.860 --> 0:38:17.040
<v Speaker 2>this is kind of like loaded language, but have these drives,

0:38:17.080 --> 0:38:20.540
<v Speaker 2>have these capacities, I guess, that kind of don't even

0:38:20.600 --> 0:38:24.390
<v Speaker 2>require us to be there in order to transpire. They

0:38:24.410 --> 0:38:27.500
<v Speaker 2>just do what they do. They're unfailingly resilient in that way.

0:38:27.520 --> 0:38:30.480
<v Speaker 2>And that's why life has been so successful. That's why

0:38:30.560 --> 0:38:32.600
<v Speaker 2>we're here talking about it is because all the cells

0:38:32.620 --> 0:38:33.899
<v Speaker 2>that make us and all the cells that have made

0:38:34.040 --> 0:38:38.740
<v Speaker 2>everything around us are plodding away relentlessly doing their thing.

0:38:39.420 --> 0:38:41.140
<v Speaker 2>And that's something that scientists can now kind of take

0:38:41.160 --> 0:38:45.090
<v Speaker 2>advantage of in order to observe ourselves from the outside

0:38:45.719 --> 0:38:50.149
<v Speaker 2>and to see what it is that makes them so special. Yeah,

0:38:50.630 --> 0:38:53.149
<v Speaker 2>I don't know. I'm very touched by that in a way.

0:38:53.330 --> 0:38:58.190
<v Speaker 2>I think there's something... comforting, I suppose, about it. That

0:38:58.230 --> 0:39:02.030
<v Speaker 2>life is, life literally finds a way, right? That life

0:39:02.090 --> 0:39:03.160
<v Speaker 2>is just unstoppable.

0:39:04.380 --> 0:39:05.160
<v Speaker 1>Claire Evans, thank you.

0:39:05.500 --> 0:39:06.560
<v Speaker 2>Thank you so much for having me.

0:39:24.000 --> 0:39:27.010
<v Speaker 1>For Tech Stuff, I'm Osvald Oschin. This episode was produced

0:39:27.090 --> 0:39:30.130
<v Speaker 1>by Eliza Dennis and Tyler Hill. It was executive produced

0:39:30.170 --> 0:39:34.130
<v Speaker 1>by me and Julian Nutter for Kaleidoscope and Katrina Norvell

0:39:34.150 --> 0:39:37.670
<v Speaker 1>for iHeart Podcasts. Jack Inslee mixed this episode and Kyle

0:39:37.690 --> 0:39:40.070
<v Speaker 1>Murdoch wrote our theme song. A special thank you to

0:39:40.180 --> 0:39:43.180
<v Speaker 1>all our listeners. Please rate, review and reach out to

0:39:43.260 --> 0:39:46.850
<v Speaker 1>us at techstuffpodcasts at gmail.com. We love hearing from you.