Marvin Minsky: Forward Thinker

it going to be Lee Marvin? It will not be Lee Marvin apart from this very moment where we are talking about Lee Marvin. No, Lee Barman wouldn't make a lot of sense on this party. No. I mean, you know, the lyric refers to Marvin the paranoid android from Hitchhiker's Guide to the Galaxy. But we're not talking about that Marvin either. Although we're talking about a Marvin who had a lot to do with artificial intelligence, which Marvin the paranoid Android possessed a great love that was kind of

a long way of going about that. We're talking about

Marvin Minsky. Marvin Minsky. So he passed away last month. Yes, Marvin Minsky was an artificial intelligence pioneer associated with the m I T. And he he passed away on Sunday, January four, sixteen, and a bunch of publications that I read and I'd seen online had been running some retrospectives of his life, looking at his influence on his main field, which I guess you would say is artificial intelligence, but also on the history of computational theory and on cognitive science.

You might say, yeah, it's interesting because uh, you know, we often will refer to artificial intelligence as being multidisciplinary. It's not. You know, you could argue artificial intelligence is its own discipline, but within that you have other disciplines. It's far more complex than just a label. And really, if you're talking about the the entire scope of artificial intelligence,

it almost necessarily encompasses all of human knowledge. Yeah, you're You're not wrong, I mean, and Minsky in many ways was kind of a human example of this, because he's certainly had a wide variety of interests and um and so we wanted to really kind of talk about him, and in a way we're thinking about doing occasionally an episode about a forward thinker of some sorts. So we may in the future do episodes about other Forward thinkers.

This is sort of a pilot program for that, and uh, I know, there are a lot of people we would love to talk about in the future, So we're gonna kind of start with this one. And if you guys out there have people, you know, Forward thinkers you would love us to to profile, you should definitely let us know. And we'll talk more about that at the end. But

let's talk more about Minsky. Yeah, and so we we thought it'd be good to talk about Minsky because we so often talk about artificial intelligence on the program and it's one of the great future frontiers that we keep coming back to, and that his his influence on the development of artificial intelligence in the SA and half of the twentieth century has been so profound, and also his views on where artificial intelligence had been going over the

last decade are really interesting. Yeah, we'll conclude with our discussion on that, but to start off at the beginning, Minsky himself was born in New York City on August nine, nineteen seven. Yeah. I so there was a piece that we read that was a profile of Minsky from The New Yorker in nineteen eighty one that was written by the physicist Jeremy Bernstein. It was just shy of a

full autobiography. I mean it was Yeah, it was really comprehensive and and one of the things that makes me realize is that we totally do not have space on this podcast to cover all of the interesting aspects of his life. So we're just going to do a kind of highlight reel of some of the things that stuck out to us. But if you're interested in the stuff we have here, I would highly recommend checking that out

to learn more about him. But anyway, that piece is going to be the source of several quotes that I've pulled about Minsky's childhood and and edgy cation that I thought would help give you a better picture of sort of the color of his personality in life. Right, Yeah, because this guy was a lot of people described him as being imaginative and humorous and maybe some people would

say eccentric. Certainly they would say, you know, he was very enthusiastic, so a vibrant personality, not like some person who would cloister himself away from everybody else in order to work on ideas. He strikes me as uh a quintessential outside the box thinker, you know what I mean, somebody who would always approach a problem in a in a strange and usually fruitful way. And he loved to

incorporate students in his in his thinking. You love to collaborate with students because I think, although I don't think he ever necessarily articulated it this way, to me, it sounds like he loved to talk with people who had not yet learned what was impossible, because that meant that they didn't put those constraints on their ideas from the getting. And that's where you see a lot of innovation. Yeah, I know exactly what you mean, and I think it's

kind of inspiring in that right. I agree, But but I want to start with with a little a picture of little Marvin. So he's talking about the different interests he had in in subjects in school when when he was a kid, and he he talks about his interesting chemistry and this is his sort of hands on approach to doing experiments and learning things firsthand. So he says, I've been reading some chemistry books and I thought it

would be nice to make some chemicals. In particular, I had read about ethel merkup Tan, which interested me because it was said to be the worst smelling thing around. I went to and this is his teacher, Zim mr Zim. I went to Zim and told him that I wanted to make some. He said, sure, how do you plan to do it? We talked about it for a while, and he convinced me that if we were going to be thorough, we should first make ethanol, from which we were to make ethel chloride. I did make the ethanol

and then the ethyl chloride, which instantly disappeared. It's about the most volatile thing there is. I think Zim had fooled me into doing this synthesis, knowing that the product would evaporate before I had actually got to make that awful merkuptan. I remember being sort of mad and deciding that chemistry was harder than it looked on paper, because when you synthesize something, it can just disappear. I thought this was an interesting metaphor also for the way you

would end up chasing the basis of physical intelligence. Sure, yeah, I mean it's it's you know, there's one thing that he would refer to, uh, you know. He would say that intelligence was sometimes why you would call a suitcase word because he would cram so many different concepts into the the suitcase of intelligence. And uh, we've also mentioned this when he would say the same thing about consciousness.

But I know that we've on this episode or not this episode, but on the show I've talked about how consciousness is kind of one of those ideas where you almost define it by striking things out from under the umbrella of consciousness, right, and then you're like, okay, so

whatever's left, that's what consciousness is. It's it's just some people, some people have made the criticism of of consciousness theory that you know, it's almost like when you're saying what consciousness is, you're just making a list of all the things the brain does and then striking out everything that we fully understand or not fully understand, but everything that we understand the physical basis, we've got a good grip on the actual mechanisms that are going on behind the scenes.

And so actually, I'm okay with using consciousness as a placeholder until we figured everything else out. That will kind of come into play with his ideas on what thought was all about. But before we get to that, we also need to talk that about how when he was uh when in the four he was joined the U. S. Navy,

served in the Navy until nineteen. Yeah. I think he explains that he he joined the Navy because he was saying that he knew they would send him to electric electricians electrical school whatever they called it back then, They would send him to school if he if he joined. So I think he was going to he was on track to be a radar technician or something like that. But of course that you know, he was in the military,

so they had him do basic training, he says. And he talks about this group that he was in the in the Navy with, and he says, our little group was a strange kind of mini Harvard in the middle of the Navy. Everything seemed unrealistic. I practiced shooting down planes on an anti aircraft simulator. I held the base record. I shot down a hundred and twenty planes in a row. I realized I had memorized the training tape and knew in advanced exactly where each plane would appear. But I

must have some odd skill in marksmanship. Many years later, my wife and I were in Mexico on a trip. We came across some kids shooting at things with a rifle. I asked them if I could try it, and I hit everything. It seems that I have a highly developed skill at shooting things for which there is no explanation. I also, I also love that he he talks about how there were maybe four people in my company who

are really remarkable, including a mathematician and an astronomer. And he started hearing this, you think there's like a nerdy version of inglorious bastards that could be made from Minsky's experience in the Navy. So instead of being these these tough like special forces guys, it's like the brilliant mathematicians and scientists who were part of the Navy and then went on to go and do other things. Um Minsky,

after he left the Navy, joined well. He attended Harvard University, and this is where we really get a first look at how he was interested in so many different fields that collectively lent themselves to this idea of artificial intelligence. He studied psychology, and he studied neurophysiology and physics. When he graduated, his degree was in mathematics. But he was interested in all this stuff while he was in school. Yes, he moved around a lot like he He says quote.

I was nominally a physics major, but I also took courses in sociology and psychology. I got interested in neurology around the end of high school. I started thinking about thinking. One of the things that got me started was wondering why it was so hard to learn mathematics. You take an hour a page to read this thing, and still it doesn't make sense. Then suddenly it becomes so easy, it's trivial. I had never thought about that before, but

he's exactly right about understanding math concepts. It's always been that way for me. That you can go over how to use a certain operator. You know, you're learning a new type of mathematical function or operation, and it's just banging your head against a wall until you get it. And then as soon as you get it, it's it seems so simple, it's stupid. Yeah, this was how I

experienced math when I was in high school. I remember by the time I got to trigonometry, uh it was it didn't take very long for that switch to click in my head where I would see what I was supposed to do and understand why I was doing it that way. It wasn't until I hit Calculus, and I'm not certain what the roadblock was, but for some reason, when I hit Calculus, that switch would take longer and

longer to click. And I would often attribute that to the fact that I think the way it was being taught was here's how you do this, not here's why you do this. So I think it also depends on your approach to learning that concept. But I totally get

what he's saying. Where you look at something and it just feels like I could read this for the twentieth time, but it's still not going to become any more clear to me, and then two hours later, when you're doing something totally different, you just think, oh wait, now I get it. Yeah, yeah, yeah, it's it says something very

interesting about human cognition. And I think this insight that he mentions here could very well come into play when we're talking about how you construct intelligence from base parts, uh, because there's something happening here. There's something about intuition and about maybe the formation of pathways like you would have in your old at work, where you know, once the pathway is set, now you can find your way back

there quite quite easily. Yeah, you could even think of that as being, you know, make it an analogy of a physical pathway through a forest. Like the first time you go and make a path, you're cutting your way through. It's a lot of work. Uh. It might even be hard for you to retrace it the first time, But after you've done it a couple of times, there's a pretty worn path there that's much easier to follow. It's

it's a fitting analogy in many ways. But Minsky also had, as we've said, very eclectic interests when he was in school. For example, there is all throughout his life he was interested in music, and I love what he says about music here. This is another interesting thing about cognition that I'll get to in this. He says, quote, I had also taken a number of music courses with Irving Fine. He usually gave me ces or d's, but he kept encouraging me to come back. He was a tremendously honest man.

Is that referring to the season d's. I'm not sure. Uh. He says he was a tremendously honest man. I think the problem was that I was basically an improviser, one of those people who can occasionally improvise an entire fugue in satisfactory form without much conscious thought or plan. The trouble is, the more I work on a piece deliberately, the worse it gets. I can totally get behind this too, because you know, we're both writers, and I'm sure that

I know what he's talking about. There's been experiences where you'll sit down and you just you get a nugget of inspiration and you just start writing. And why you end up whether you may have to go back and revise a little bit, but in large part, it's just

it feels really satisfying. And there are other times when you think I have an idea, I'm gonna go ahead and start the whole process of outlining all of this and then blocking it all out, and then I'll actually get around to writeing it, and then, like you know, two hours later, you're just like, I don't know, whatever made me think this was worth putting down on paper. Yeah, I know exactly what you mean. I mean usually, I would say for most people and for myself, more work

leads to improvement, but not all the time. Sometimes you can just write a thing to death. The more you keep tinkering with it, the less interesting it becomes. Uh So, by nineteen fifty one, he had graduated Harvard the year before, and then he goes and joins Princeton University for postgraduate studies, and uh that same year he built the world's first neural network simulator. And this is this is a thing

that is worth noting. It's a neural network simulator in nineteen fifty one, So try to imagine that this is not based on microchips. No. Um. Also, it was called SNARK, which is great. It's s n A r C. And that stands for stochastic Neural analog Reinforcement Calculator, which really clears it all up. Uh. Stochastic is one of those words that's going to pop up a couple of times as we talk about this. In case you aren't familiar with the term, it essentially means random. That's that's kind

of a easy way of translating it. Uh So. He graduated Princeton in nineteen fifty four with a doctorate in mathematics. The following year, in fifty five, he invented the confocal scanning microscope, which actually uses a little spatial penhole inside the lens, and the purpose of that is to filter out all the light that would not be in focus, so it therefore creates a higher resolution image of whatever it is you're looking at through the microscope. So it's

kind of just really improving resolution now. In nineteen fifties seven, Marvin Minsky began to work for m I T. Massachusetts Institute of Technology, and he was specifically interested in researching computers in order to understand human thought, which uh might seem counterintuitive to some people, like why would you look at computers in order to get a better understanding of how humans think? There it was a really good analogy,

I thought. In um one of the pieces we looked at it was on edge dot org that was talking about it was interviewing different people with recollections about Mints his life. But there was one part of this piece that talked about how, even though the analogy was not perfect, if you were a person today who wanted to understand how birds fly, probably one of the easiest ways to

start would be to look at how airplanes work. Even though airplanes and birds work in a different way, you can start getting the principles about what you know how things stay aloft in the air by looking at what an airplane needs to do in order to not fall. And I think the same thing could be true about computers and brains. Both do computation, both to information processing.

So if you look at a thing that's kind of graceful and mysterious, like a human mind, and you want to try to understand it, it it might be a good place to start to say, Okay, how does information processing work in a machine? Yeah, I mean, I I'm always hesitant about that. I there are a lot of things that Minsky talks about that I like a lot, but it's because it lates to the mind, not the brain.

And uh it's because I know that computer's process information in a very different way than the way we think in general. I mean, if you're talking about classical computers and the neural networks that we have in our in the wet ware we have in our heads. Uh, So

I'm always hesitant to make that comparison. However, when you go to an abstract level of the human mind as opposed to the human brain, then suddenly these conversations make a lot more sense to me, and I'm a lot more um inclined to agree and engage on that level as opposed to just crossing my arms and going yeah, well, I mean I think it plays on the same principle as the idea of the universal computer, right that if you have a touring machine, you know you have a

basic universal computer. It doesn't matter what the hardware is. If you can do the basic computing functions, you can do the same job as a different kind of computer that uses different hardware, right right, Well, moving on with our little biography on Marvin Minsky before we get into some more details about his specific ideas in fifty eight

or fifty nine. And the reason why I put that down is because depending on what source you read, some site that uh, this happened in nineteen fifty eight, others in nineteen fifty nine. My suspicion as this particular thing took a long time to happen and probably started in fifty eight and became official in fifty nine. Uh. Minsky partnered with a man named John McCarthy who was a professor of electrical engineering at m I t and together

they formed the m I t Ai Laboratory. And as a side note, John McCarthy is generally attributed as the person who actually coined the phrase artificial intelligence in the mid nineteen fifties, I didn't know. Yeah, so he was another, uh, founding father of the science of artificial intelligence. Like you know, if you were to make a list, you'd have people like Ada Lovelace and Alan Turing and Marvin Minsky and John McCarthy all on that list easily. I mean, you

would not want to leave them off. He would. Minsky, that is, would stay with m i T for the rest of his career. He became the Donner Professor of Science in nineteen seventy four and the Toshiba Professor of Media, Arts and Sciences at the m i T Media Lab in nineteen Yeah. Well, I think we should now just transition to a more general discussion of what were some of Minsky's influential ideas, concepts, and books, because, as we've

said earlier, he was massively influential. We we don't have time to talk about everything, but we want to highlight a few interesting things that he brought forward and and uh, A lot of his work kind of relates to this running theme of the whole and its parts. Yeah, like so whole as in w h O L E uh, the entirety and its parts, specifically with reference to intelligence. Right that that's a running theme throughout a lot of his work. One of his early ideas something that he

called frames. It was this concept that he proposed in nineteen and defined frames as the general information a computer system would have to possess before it can make specific decisions. So what do you mean by that? All Right? So let's say that you've you've built yourself a robot and you want the robot to do things. In order for the robot to to do the things you wanted to do, you have to teach the robot certain concepts. First, I

love that sentence. You want the robot to do things? Yeah, well, let's you know, you could just build a robot, right, I mean maybe maybe you're rawsom and you're just like, I just want some universal robots run around this place. But you know, I don't care if they do anything. No, you must send it upon the world with a mission. But if you here's a simple example, you've got a roomba.

You've built a roomba. Well, before you can just set a rumba down and have it vacuum of a room, you've got to teach it general concepts, things like uh, walls, you know, Uh, the what happens if you come up to allege all this kind of stuff. You have to teach it all of this before it can complete eat

the task it was built for. So one example that is commonly sited is imagine you've got a computer system and you've got a series of rooms, and these rooms are connected to each other through doorways that actually have doors on them. In order to have a this computer system be able to navigate through those rooms, you know, presumably through some sort of robotic form, it would have

to understand how doors work. What a door is, that a door could swing either inward or outward, the various mechanisms that might be employed in order to work a door, whether it's a door knob or um a handle that's got a latch that you have to press down with your thumb, or maybe even a bar that you have to push or pull. And you have to teach the computer system all these things. Now, these are things that

humans once you teach them. Once humans are really good, Like they can recognize get the basic concept of a door. You've got pretty much all doors ready to go. Yeah, you might get thrown by something like a revolving door that you see for the first time. But most most of the time, you're gonna see a door and you're gonna think, all right, this is either going to open

inward or outward. It's not going to do anything else unless it's Star Trek and then goes But yeah, like you said, you're a robot and you come to a door with different types of door knobs, or with door knobs at different height, or you or you only taught the robot how to open a door if it opens outward. What if it's a push door and it doesn't have a knob. Yeah, And these are all sort of things that that we take for granted as humans because we've

had some experience and we're able to extrapolate. Computer systems in general are not good at this. Computer systems are very good at performing tasks that they've been programmed to do, but they're not so good at doing tasks they haven't

been programmed to do. Who to thunk it? So um, But he was he was using this this idea of frames as a way of explaining this concept of These are the These are the sort of contextual information buckets that you need to each a computer system in order for it to be able to do the thing you designed it to do, and whatever environment that might be, whether it's you know, a robot moving around rooms or

autonomous some submarine exploring underwater features. Anything. Really though, I would suggest that, well, I guess I'd have to guess because I don't know for sure, but I would guess that Minski would agree that if the human mind can figure out things without having to be told them, a computer potentially can too. It just needs the right equipment. It needs the right process is to be able to know things that without being told them it would need

to be able. It would still need some frames, right Like for example, if I, uh, let's say that that your mind is completely wiped, Joe. So let's imagine it's last Tuesday, because we all know what happened that day. Uh, and I were to produce for you a coffee mug and I point to this, and I say, this is a mug. Sometimes people refer to it as a cup, and it holds liquid. This is where the liquid goes. As a human being, what's liquid, We've already covered that,

We've already gotten to that part. Though that stuff we already covered. This is actually pretty advanced in the day. This is like four pm on Tuesday, and so, but at that point you would you would be able to recognize another cup, even if it were a different color, different size, even if it were a slightly different shape. Let's say it's like a novelty cup, so it's in the shape of a tartist or something, you would know.

You might not know that that's a tartist, but you would know that that was a cup, and you would

be able to use it as such. Whereas computer systems, or if you haven't built in any sort of machine learning so that they can actually start to extrapolate information, they can't do that right if it's if it might not even recognize the same cup, if the light in the room is different, or if it's a little too far away from the camera, are a little too close because the size will look different to it by perspective.

So uh, you know, you would still need those frames at least to exist for some amount of information so that the machine could know what to do. But the goal of course and artificial intelligence is to get machines sophisticated enough where those frames can be more basic that you don't have to map out every single possibility in order for a machine to be able to understand that the machine itself would be able through perhaps even trial and error, learn how things work. Like if you taught

the uh the the machine how certain doors. Like let's say that you've got ten different varieties of doors in this other scenario we mentioned, and you teach it about five of them and how those five work, and it has all the basic information of how all the doors work, but the other five are slightly different variations on it. And you have taught it how to uh do trial and error so that it can actually experiment when it owners a door that doesn't fit the five that it

was taught. That would be more like he will it will do science in order to break on through to the other side. Right yeah, it might just turn into a robotic kool aid man, you know, and just crash through. But your goal is so that it actually learns and experiments and continues to uh grow its own knowledge. Okay, Well, let's look at another one of Minsky's influential ideas, which

is his society of mind theory. Now, he had a book called Society of Mind I think in nineteen eighty five, right, Yeah, before that, he had started really playing around with this concept all the way back in the nineteen sixties, and what really inspired him was that he started to work on a very basic robotics system. Uh. And it was a very simple exercise and artificial intelligence. Simple in the sense that it was elegant, not simple as in it

was easy to do. Yeah, and Minsky had done some work with with robotic motion and the manipulation of of arms and claws and stuff like that, right even back when he was in school. This was one of the great stories from that piece in The New Yorker that Minsky tells. So once the Harvard zoology professor John Welsh offered Minsky access to his lab and his equipment after Minsky found out that scientists didn't know how the nerves in crayfish worked and uh Minsky told The New Yorker,

I became an expert at dissecting and crayfish. At one point, I had a crayfish claw mounted on an apparatus in such a way that I could operate the individual nerves. I could get the several jointed claw to reach down and pick up a pencil and wave it around. I'm not sure that what I was doing had much scientific value, but I did learn which nerve fibers had to be excited to inhibit the effects of another fiber so that

the claw would open. And it got me interested in robotic instrumentation, something that I have now returned to, trying to build better micro manipulators for surgery and the like. Yeah, So in between his UH Frankenstein like experiments with crayfish claws and developing UH micro mechanical systems for surgery, he was experimenting with this very basic artificial intelligence robotic arm apparatus.

And it consisted of a computer that did calculations, a camera that could focus in on what needed to be manipulated,

a robotic arm, and then a series of blocks. And the idea was that if you could UH teach the computer system what certain terms were, like I want you to build a tower, that you would then be able to teach the robot how to pick up a block, how to manipulate it so it's in the right place, how to stack the blocks so that they're stable, and also to teach them things that people kind of grasp pretty quickly once they get out of the infant stage of their lives, like if you're trying to build a

tower and you've got three blocks stacked on one another and you need to put you know, your instruction is make this tower four blocks high. One solution is not to grab the block that's on the bottom of the tower, pull it free, and then try and place it at the top. Was the one I was thinking, was you would it would it necessarily understand that you have to lay down the lowest level first, right if you try and all, right, well, you know, let's let's start from

the top and work our way down. That doesn't you can't do that. This is something we've talked about before. But I do think it's an interesting thing about artificial intelligence that's often overlooked is the basic locomotion and physical interactions with objects is a kind of intelligence. Absolutely, It's it's not at all just like, well, that's the dumb thing the robots do, and artificial intelligence is getting them to be chatter bots, you know, to pass the Turing

test and have have conversations. I mean, knowing how to move things in your environment in a smart ways absolutely artificial intelligence. Sure, yeah, you know, knowing how to handle any particular you know, object so that you are not damaging it, that you can move it effectively, you might even want to program in things where the robot knows I cannot move this particular object because either it's too delicate or it's too heavy, or whatever it may be. Yeah, okay,

but back to MINS. So when Minsky was working on this, he began to think about all the different elements that are necessary in order to make this task possible, and he began to look at kind of discrete facets of intelligence that are required in order for you to do this, and that's where he had this breakthrough, this idea that

led to the society of mind idea. So in the nineteen seventies he began to develop this theory and he published a lot of essays on the subject, and he worked with an m. I. T. Mathematician named Seymour Papert on several of the early ideas. So the book came out in ve and the argument he makes is that the mind not the brain, that the human mind is made up of individual parts called agents and agents It's important to note have no mind of their own, So

agents themselves have no emotion, they have no thought. They are aspects of the mind itself, and each agent is responsible for a particular aspect of intelligence. It's through their cooperation that conscious thought emerges, according to this society of mind theory, and it's really about how the mind works at a conceptual level as opposed to the biological level. This is an idea I've encountered before in cognitive science, but I wasn't aware in the past that it really

came from Minsky. Um. But I think there's a lot to this. I think this is a very I would consider this a very plausible and convincing way to think about what consciousness and intelligence are. And even if you are hesitant to argue for that, at the very least, it is a very compelling way to think of artificial intelligence. How do you get a machine to do any particular thing that would require intelligence on behalf of that machine? But if if you're not convinced, maybe we should look

at an example. And this comes straight from the book. In fact, I read the book. Um. It's very easy to read. Uh. Each idea is about a page long, and each chapter is a collection of between eight or nine ideas, maybe more a fewer depending upon the chapter in their thirty seven chapters. UH and I Love I actually also watched the beginning of a lecture that Minsky gave. There's an open course on m T where you can go to m I t s website and watch a

lecture series led by Minski himself from two thousand eleven. Oh, that sounds fun. I kind of want to get on that. It's pretty cool. And at the very beginning he talks about how he really liked Society of Mind, and the main reason he liked is that so each idea is like a page long, and if you don't like it, you can totally skip it and go to the next one. It's really easy. Like this other book I wrote later, the chapters are much longer, and if you don't like

an idea, you kind of have to just keep going. Uh. You can't really hear the students, but I would hope there was some good natured chuckling going on at any rate.

So he gives an example in his book, and he presents a very simple scenario, the idea that you are told to pick up a cup of tea and you're gonna you're gonna drink from this cup occasionally, but it is immediately What I'm thinking of is something you mentioned on the podcast a few episodes episodes ago, which is the office simulatory pick up the cup and throw it. Just just start throwing things across the virtual reality office.

That that video is hilarious, by the way. So from his book, he says, let's think about all the elements that go into picking up a cup of tea uh in the in this idea of society of mind that's made up of agents, he says, you're grasping. Agents want to keep hold of the cup. And he uses the word want as in not not that they have an actual motivation, but that's their purpose. So you're grasping. Agents

want to keep hold of the cup. You're balancing. Agents want to keep the tea from spilling out your thirst. Agents want you to drink the tea. You're moving, agents want to get the cup to your lips. So he argues that these four agents working together, although each one is independent and that is important, they're independent of one another, but they're working together in concert, can accomplish the task

of allowing you to drink your tea. And more importantly, you can do this while doing other things like you could. His example was walking around like at a like at a tea party type deal, and you're having conversations with people, and you're just casually holding your tea and occasionally sipping it. But you're not thinking about that, right, at least not

consciously thinking about it, right. But clearly your brain is doing all this work, right, It's not like you're just magically holding this cup and keeping the liquid from spilling out and all that kind of stuff. But he said that you know consciously, you're not really aware of it. Uh. So my example, I said, you could, uh, you could drink your tea while not interrupting other stuff you might be doing, such as telling the Queen of England that

hilarious story about the time you got drunk on the tube. Um, because as soon as I think tea, I'm like, well, clearly I'm If I'm drinking tea, I'm obviously having as as I am want to do. And so Minsky would go on to argue that the concept of agents is a necessary concept. He argues that if we cannot and this is a quote, explain the mind in terms of things that have no thoughts or feelings of their own,

will only have gone around in a circle. So, in other words, he says that if your definition of thinking requires you to talk about smaller elements that also think you're you're not really describing thinking, You're just you're just shifting the definition around two different parts of the brain. This is something that parallels uh and analogy that I remember coming across in the works of Daniel Dennett, the cognitive philosopher, and he so he presents this idea of

the Cartesian theater. Have you ever heard this, I've heard the term. Well, essentially, he says, okay, so some people think that look there is what your eyes do is that they take in light from your surroundings and they paint a picture. And it's like the brain projects that picture as a movie screen for you to see. But

who's doing the seeing? So then you have to imagine that really inside your brain is a small is a little brain that gets to sit in the movie theater of your mind and watch the screen that is made by your eyes and so, but who's seeing within that

brain in that movie theater. So if you keep postulating a little person inside you that is the audience of your thoughts or the audience of what you are perceiving, it's an infinite, infinite grass right right, And that's not helpful if you want to have an actual meaningful conversation about how is this working? Um. So the book divides up concepts into these categories that kind of mentioned that, where you have like maybe up to eight or nine

of these one sheet descriptions collected under these categories. And those categories include things like holes and parts, kind of what I was referring to earlier, conflict and compromise, the self, problems and goals, and lots of other ones like I said, They're thirty seven in that book, and each section details Minsky's ideas on how the human mind processes this information

on a conceptual level. So Minski uses the example of building blocks early on in the book to demonstrate all those all the considerations one has to take in order to complete that simple task. So, uh again, you know, back to that idea of I want you to build a steeple. I don't know what a steeple is. A steeple is going to be two green blocks and one

orange triangle that goes on top. And then once you teach it, then it, you know, it knows how to do that, but it has to you have to give it the all you know to find all the agents to identify things like a block versus a triangle, how to pick that up, how to place them, the fact that the blocks have to go on the bottom and the triangle has to go on the top, all this kind of stuff. Um. And he says that once you break it down into those basic parts, then suddenly these

these uh advances and artificial intelligence become possible. Um. And like I said, you can take an open course on the Society of the Mind on the m I T website. You can actually find that for free. So if you want to check it out, even if you just want to see some of the lectures and and hear what the man himself had to say about this idea, you can go and do that. And I highly recommend checking it out at least you know, satisfied your curiosity for

given a good ten fifteen minutes. The first lecture is two hours long, and there are a lot of lectures, so um. But yeah, and that this kind of leads to that idea of common sense and common sense is one of those things that we kind of innately understand as human beings. But what does that mean for artificial intelligence? Yeah, and this is one of the things that I think got mentioned most often, like in the obituaries after he passed away, a lot of publications mentioned that he was

interested in giving computers common sense. But what does that really mean from Minsky's point of view, Well, it goes back to that that description I talked about earlier, like if you're building a tower, you can't we know, you can't take a block from the bottom of the tower and put it on the top, or you can't start at the top and work your way down. Gravity obvious

to us, but maybe not obvious to a computer. Right, So things that are are common sense we often kind of dismiss as being easy or simple, or it's just a matter of fact, and therefore it's not anything to to really worry about, except if you're building an artificial system to do those things. The artificial system doesn't know any of that, so you have to teach it. And I think his point is sort of the common sense is not as simple as we think it is. It's

actually it's actually quite hard. We think common sense is something that's very basic or very simple because it's intuitive to us, but it's not basic. It's not simple. Common sense is incredibly complex. Yeah, he he had a quote um that says, a common sense is not a simple thing. Instead, it is an immense society of hard earned practical ideas, of multitudes of life learned rules and exceptions, dispositions and tendencies, balances and checks, which I think is a good way

of putting it. Like it's stuff that once we humans have come in contact with it. You got it right, It's like this little, this little box in our brains gets checked and we understand that concept from that point forward, even if we encounter it in a different context in

the future. Not so with machines, at least not naturally, which is why it's a big problem in artificial intelligence that if you can create a machine intelligence that is able to mimic that sort of uh feature of human intelligence, you're you're way ahead of the game. So um uh yeah, it's it's interesting too because you've got this, I like

your fun fact in here. Well, yes, the fun fact is that did you know that Marvin Minsky was consulted by Stanley Kubrick as I don't know exactly what you call it, maybe sort of a science advisor for two thousand one of Space Odyssey. I did, but only because Minsky would often have Kubrick over to his house for parties, as well as Arthur C. Clark and Isaac Asimov. Minski moved in some awesome circles, like like people who were really interested in robotics, not just from the academic side,

but from the literary side. We're all uh in contact with him at the time. He taught re Curse Wild, didn't he? He may have. I don't know that for a fact. I do know that he he had conversations with Albert Ein's line and said he couldn't understand a word of it. Um he uh. He was friends with Heindline, So I mean the guy was like, he was like the guy who knew everybody. So it would not surprise me to learn that he had taught Kurtzwile we have

some other stuff to talk about. He has another book called The Emotion Machine, which came out in two thousand six, and this is sort of following up on some of the same ideas earlier in his career. Yeah, it's a it's most people refer to it as a sequel to Society of Mind. His central argument, and this one is

that emotions are really just different ways of thinking. Yeah, and I've read several quotes of his along these lines where he talks about he's sort of urging people not to underestimate the the cognitive content of emotions, if that makes any sense. He certainly says that you know, the ability to have these emotions, whether or not their different methods of thinking, uh, hey, they lead to greater intelligence.

That it creates a new capability of looking at information, and it is an interesting way of looking at it right, Like, like if you are thinking about something and you're angry, you might come to a different conclusion and learn something that you otherwise wouldn't have if you were happy or sad. Well, it also for me, raises an interesting question, which is that we naturally make a distinction between thoughts and feelings.

We think there are two different species of things. You know, I have feelings and then I have thoughts, And I can have thoughts about feelings, and I can have feelings about thoughts. But are they necessarily different species? Are are feelings maybe just another type of thought? Are they just thoughts?

And this kind of brings us to that amazing documentary Inside Out, which a lot of people have said, you know it was it's based on some of the most current information and scholarship on emotions and memory, and thought, yeah, I really haven't seen it. I know, so, I know some people who liked it a lot. I I saw it so anyway, when I described my reaction to Inside Out, which I thought was entertaining, but that's about it. Most people think I'm dead inside because like that movie destroyed me,

I cried, like crazy, like what's wrong with being dead inside? Yeah? Look, a lot of Pixar's movies affect me deeply. That was just not one of them. However, I did think it was a very interesting approach with emotions their connection to thought and memory, and it seems very similar in many ways to what Minsky was saying. Now, not everybody was totally thrilled with this approach. Some people thought it was an interesting way of understanding the mind, but a misleading

way of thinking about how the brain actually works. So neurologist Richard Rustack wrote up a review about his you know his work on emotions and criticized part of Minsky's approach, saying that Ski failed to show how emotional functions relate to brain activity. Now, he acknowledged that Minski explains this by saying our knowledge of the brain changes so quickly

that it becomes outdated rapidly. But then Respects says, well, how can you possibly draw any meaningful correlation between brains and machines if you also are arguing our knowledge of the brain changes so quickly as to essentially contradict itself, So you can't make any conclusion if part of your argument states our knowledge of the brain changes so quickly

that it changes our understanding. Like, how can you conclude anything if at the very start of your argument you say, listen, I'm not gonna write about the brain because our knowledge of it changes so quickly. Anything I write will be out of date by the time this book is published. But they're totally like machines like that, he says, You know, that's a logical Like there's there's a disconnect there now.

Respect also wrote that he had some reservations about some of Minsky's other assertions, many of which seem to draw conclusions of about how the brain works based on how large complex computer systems work. So Restack wasn't so sure you could support such a connection. But he also said, it may turn out that Minski is completely right. We just don't have the science to support it one way or or you know, deny it one way or the other. It's it's just that without knowing, we can't be sure.

But it may turn out that these are absolutely on target. We just we just can't be so so sure of it right now. But he did say you could learn a lot about how the mind works by reading Minsky's book, you just wouldn't learn about how that relates to the way your brain functions. So again, the mind being this more nebulous platform that rests upon the brain, like it's a manifestation of the brain's abilities. Um, and that we can learn more about how the mind works, but not

so much necessarily about the neurology underneath it. Um. Just pretty cool, any hope coming through for my theory that the brain is just for cooling the blood and we really think with our tone nails, h I'm gonna I'm gonna say that science does not currently have very much support for that particular belief, but shine on you, crazy diamond. They also said Galileo was wrong. Okay, and moving on,

let's talk about Minsky and the concept of free will. Yeah, Minsky had some really interesting thoughts on this, and I want to read a quote from his paper Matter, Mind and Models, and this was cited in another thing I read about him. But this quote goes, if one thoroughly understands a machine or a program, he finds no urge to attribute volition to it. If one does not understand it so well, he must supply an incomplete model for explanation.

Our everyday intuitive models of higher human activity are quite incomplete, and many notions in our informal explanations do not tolerate close examination. Free will or villa is one such notion. People are incapable of explaining how it differs from stochastic caprice, but feel strongly that it does so. Stochastic caprice, in

case you're wondering, would mean random whimsy. Yeah, so he's saying that even though we can't really explain, we can't give any good account of where free will comes from, we insist we must have it, and that it is different from just random impulses that we have that we act on. Yes, but he continues, I conjectured that this idea has its genesis in a strong primitive defense mechanism. Briefly, in childhood, we learn to recognize various forms of aggression

and compulsion, and to dislike them, whether we submit or resist. Older. When told that our behavior is controlled by such and such set of laws, we insert this fact in our model inappropriately, along with other recognizers of compulsion. We resist compulsion, no matter from whom and whom is in quote, it's there. Although resistance is logically feutile, this resentment persists and is rationalized by defective explanations since the alternative is emotionally unacceptable.

I think that's a very interesting insight. Yeah, And and it applies to more than just intelligence, Yeah, you know, because it It actually reminds me of any time where we encounter something we've never encountered before, and by we, I mean humans at large, and we naturally, as curious beings, want to understand that thing we've just encountered, and often in our first attempts we will we will create explanations that don't necessarily correlate to any kind of reality in

order to explain it. And it's only later on, as we start to peel things away that we really see what's happening underneath the surface. Yeah, and then totally he goes on to apply this same reasoning, uh about the origins of our resistance to, you know, the idea of determinism, and and our and our tendency toward free will as

a kind of rebellious impulse against compulsion. Uh. He's like, well, hold on, now, if we create intelligent machines and they have something like consciousness, will that inherently bring with it the illusion of free will and the resistance to the idea of compulsion by physical determinism. Would a robot with consciousness also insist that it has free will? Yeah, it's an excellent question that right now remains in the realm

of philosophy. One day it will not be though. One day it will be a reality whether or not, and it may turn out that the answers No, I don't need to worry about that. I don't know that that's going to be the case, because I I believe very strongly that, uh that our our concept of re will is based upon ultimately the activity going on in our brains.

So if we in fact build a system that is truly simulating that activity, it stands to reason that whatever entity is created from that would also experience that same feeling that it possesses free will. Yeah. And even if you argued, no, I built you so that you can make me toast. It's you know, that's that doesn't matter. If someone told me, no, I built you so that I can make you toast, I would they say, I'll show you why you built me exactly. So, Hey, we

talked about the future on this podcast. I have to assume that Minsky, given all his thoughts about artificial intelligence, made some comments somewhere about what he thought the future would be like. He talked about the future. And he also months before his death, he had there were a few different interviews where people were asking him his opinions on the current state of artificial intelligence. And I think

those answers are really interesting too. But uh, you know the New Yorker piece that that you dug up from nineteen eighty one, it was actually called like it was talking about his vision of the future. Although spoiler alert, if you read the whole thing, there isn't a lot in there about that. It's mostly about a profile of him. Yeah,

though it is a really good one. It's fascinating. It's just that the headline might be a tad misleading, but uh, or or it could be more of like a broad approach like you know, he he saw this stuff happening well before it became reality. In fact, his work is what allowed a lot of the artificial intelligence uh developments

to to take place in the first place. But one of the things he talked about was he could envision a future and remember this, in which a with a relatively small amount of technical improvements in robots would see automatic factories in space dead on. And we do have robots working in a lot of factories doing automated work, just not in space. Oh wait, I forgot. You have not seen the factories on the far side of the moon. Well, Jonathan,

you are in for a pleasant surprise. Yeah. Uh, this actually reminds me of a terrible movie by the Asylum I once watched, and which robots were being built in a space station orbiting the Earth and then sent down to Earth. And I thought, what a huge waste of resources. Just build them on the Earth. Build them on Earth if if that's where they're doing work, why would you ever build them in space? It's too expensive? Uh So Yeah,

that obviously has not panned out. But we are seeing a lot more of automated systems in factories around the world, a lot more robots being employed to the point where we're seeing like the thoughts about robotic drivers and robotic drones delivering stuff to us. I mean, it's it's pretty far along in that respect. Now, where did Minsky come down on that? We talked about the possibility of machines developing aciousness? Was was he thumbs up to that? Uh?

It's interesting. I would argue that his answers, depending upon what time of his life you were looking at, Uh, went a little back and forth. It was always a

little vague to me. But he did say that he could see a future where machines have minds of their own, and their minds would be aware of the various parts that make up those minds, kind of the agents, if you will, and that what each of those agents would be capable of doing, and be able to use that knowledge to solve any problems that the machine would encounter.

It's not the same thing as consciousness, however, Necessarily it may just be Oh, I have this task that I've never had to do before that I have got to complete, but it's similar to all these other things I know how to do. Therefore, I'm going to employ all of these agents that help me do those similar tasks to complete this one. You wouldn't argue that that in itself

is a manifestation of consciousness. I think if you were like that rotten so and so wants me to do this thing and didn't even tell me how to do it, We'll fine, I'll do it, but I'm not gonna be happy about it. Then he'd be like, Okay, that's a

pretty conscious machine. So I'll show you why you created me, right. So, so, you know, I would hate to ascribe a position when I myself, I'm not entirely certain where he fell on that he may himself have been like, this is a philosophical question that fascinates me, but I don't know what the answer is, or I don't know what I feel the answer will be. Um. So, but you mentioned that right before his death he had thoughts about where we

stand with AI today. Yeah, they were not um complimentary thoughts. Actually, you know, he he was very dismissive about certain things, Like there was a Washington Post piece that was published shortly after his death, and it contained a lot of little nuggets about Minsky and what he felt, how he felt about certain developments, you know, recent developments and artificial intelligence. So, for example, they asked him about UM IBM S Watson.

I think a lot of people would argue that IBM S Watson is a very impressive display of artificial intelligence. It's not, or at least a very impressive display of word play. And that's kind of what Minsky would say. He said he called it an ad hoc question answering machine,

that it wasn't intelligent, it was just a question answering machine. UM, which is I think if you would go to maybe the Watson chef style, where it's starting to try and invent things based upon other things, it's not doing a great job, but it's trying, I think it goes beyond

question answering machine. But that was his opinion, and he also talked about how he felt AI developers were making a mistake aiming for what he called the top of the AI problem, So, in other words, trying to create systems that on their surface appear to be similar to human thought, but they lack the foundation of what thought is really all about, and therefore it's just it's kind

of like a chat bot. It's just it's simulating it enough so that it seems intelligent, but there's nothing underneath it to actually support that supposition. I guess from his point of view that the problem might be that it's uh that it's lacking these agents, right, the society of mind,

the basic agents that populate the society that becomes thinking. Right. So, in other words, instead of having agents, it's simply uh, trying to follow a program that mimics the way humans would respond to situations, but without that underlying you know, network of agents that are actually making it happen. Uh, it's kind of like skipping those those those found that

foundation in order to just get the result. But that means that the underlying system is not as robust as what you would need to have a truly intelligent uh computer. He also said in an interview with M I T Technology Review that the last decade of AI was about

quote improving systems that aren't very good end quote. So he contrasted that with the era of the nineteen sixties, the early era of artificial intelligence development, when he said that they were having major breakthroughs on the order of every couple of days, that he and students would talk about these ideas and come up with new approaches and new concepts about thought that would lead to enormous potential breakthroughs in artificial intelligence. So these days it's every two

or three years you might see a breakthrough. And part of that, he argued, was that we rely too heavily

on so called experts in AI. He was actually calling back for the days when he would work with students who, again because they don't know what's impossible, end up asking questions and coming up with ideas with those constraints, and therefore push forward the discipline much further than people who have a preconceived idea of what is and isn't a possibility, that have already placed limitations on themselves that they aren't aware don't really exist. So it was interesting, I, you know,

I I can see his point. Also, there is something to say about when you get to a when you when a new discipline is created, you would probably expect advancements in that discipline to be extremely rapid early on, because there was nothing before. But as you build and build and build by necessity, usually things slow down. You just you know, you've you've explored, you you've picked up all the and I hate the phrase, but you've got you picked all the low hanging fruit. Why do you

hate the phrase because it's overused. I worked for consultants for seven years. I hate low hanging fruits. We come up with an alternative expression, the eazy cheese. All the easy cheese has been eaten, and it's it's the difficult to get cheese. That is, it's the only cheese that's left. You've you've picked You've picked up the deli counter cheese. Yeah. Yeah, the really good stuff that's like under a heavy glass case and it's guarded by wolves. You just haven't been

able to get to that yet. I go to a lot of weird cheese parties. Alright. So that kind of wraps up our discussion of Marvin Minsky. Obviously, like you said, Joe, there there's so much more we could have talked about. Um, the guy was absolutely fascinating. He has had an enormous impact on the discipline of artificial intelligence, and I have

no doubt will continue that impact will continue into the future. Uh. And if you guys enjoyed this, let us know if you have other people you would like us to talk about. If if I mean, I would love to do a full episode on Ada Lovelace. I think that she was an absolutely phenomenal person and uh, it would be really interesting to do a full rundown on on her ideas

and how how much of a pioneer she was. Uh, but you know other people too, like people who are still alive would be great too, Like we it doesn't have to be someone from I think they must be dead. Okay, alright, So if you have an idea of someone you would like us to profile, living or dead, let us know send us an email. The address is f W Thinking at how Stuff Works dot com, or you can always drop us a line on Twitter or on Facebook. At Twitter we are f W Thinking. Just search fw Thinking

and Facebook's little search bar will pop up. You can leave us a message there. We read all of them, and we will talk to you again really soon. For more on this topic in the future of technology, I'll visit forward thinking dot com. Brought to you by Toyota. Let's go places,