The innovation show with aidAn mccullen – Act THREE

In this interview with Aidan McCullen on The Innovation Show, Byron discusses act three of Stories, Dice, and Rocks That Think, focussing on artificial intelligence. Aidan introduces Byron by saying, “there are a host of problems innate in humans that limit our ability to see the future clearly, can we fix them” you ask “debug our faulty intellects? Not a chance,” you tell us “there are reasons why we are the way we are, we are optimized for our purposes, not the least of which is thinking in stories, not logic. So we did something else instead, we taught rocks how to think…”  

Rocks that think is a metaphor, of course, for a computer…we learned what probability was, we understood the future and we learned how to predict it. And we did that with paper, pencil and the side rule until one day society’s complexity went past what we could kind of do with the legal pad and a ballpoint pen. And so we said we need to build machines, just like we built machines that did our physical toil, we need to build machines to do our mental toil.

FULL EPISODE TRANSCRIPT

Aidan  [00:00]: Stay hungry, stay foolish. And we’re back for the finale of Stories, Dice, and Rocks That Think. Before we start, I want to thank our sponsor, Zai, boldly transforming the future of financial services with a suite of embedded products and services, enabling businesses to manage multiple payment workflows, and move funds with ease. You can check out Zai at www.hellozai.com. We welcome back for part three of this brilliant book, Stories, Dice, and Rocks That Think, Byron Reese. Welcome back, sir.

Byron  [00:34]: Thank you for having me.

Aidan  [00:36]: It’s great to be back, I was showing you my pin here, I was doing my best to try and get a pin for each of the acts. And I’ve managed to get one which is a sculpture that looks like it’s thinking well, that’s I’m kind of bending it a little bit there. 

Byron  [00:50]: Pretty amazing that you even had that, Did you have to go out and buy it or you had it?

Aidan  [00:55]: I buy them whenever I see them. So I’m a total nerd. Like I buy them whenever I see them and just stick them in the bank. Do you remember that movie unbreakable? And there was a guy in it, Mr. Glass. 

Byron  [01:06]: Of course. 

Aidan [ 01:07]: And do you remember he goes into the comic store? And he hits off the comics and waits for one to fall?

Byron  [01:13]: Yes. I remember that scene exactly.

Aidan  [01:16]: That’s what I’m at with my pins. But anyway, let’s get into this, it’ll be no surprise to you that I loved act three, I really really enjoyed it. Great read and really enjoyed it. And as you know, I was on holiday when I read it. So I had that alpha wave state of reading and taking in everything. So I thought we’d start with these questions that you posed at the very top of Act Three, you say, “there are a host of problems innate in humans that limit our ability to see the future clearly, can we fix them” you ask “debug our faulty intellects? Not a chance,” you tell us “there are reasons why we are the way we are, we are optimized for our purposes, not the least of which is thinking in stories, not logic. So we did something else instead, we taught rocks how to think…” Intrigued? So am I. Over to you Byron Reese.

Byron [01:53]: Well, Rocks that think, is a metaphor, of course, for a computer. And I think that to set up our act three, what happened in act two, we learned what probability was, we understood the future and we learned how to predict it. And we did that with paper, pencil, and the slide rule until one-day society’s complexity went past what we could kind of do with the legal pad and a ballpoint pen. And so we said we need to build machines, just like we built machines that did our physical toil, we need to build machines to do our mental toil. I picked an arbitrary date of I to think 1952 when we spun up the first transistor computer, because that really is the forerunner of all the ones we have now, and that is where we are right now. 

Aidan [02:35]: I wanted to jump into some of the stuff you talk about like you were saying, in Act Two, the way you write is, you find this knowledge and you try and pepper it through the book, where you’re kind of like going, “Whoa, I never knew that.” One of the things I really loved was, as you say, our bodies run on about 100 watts of power, roughly a quarter of which is needed to power our brains, which is about a millionth of what a supercomputer requires to do far less. And you say we made huge leaps of progress over the centuries. And I thought we’d share the chapter on progress. And what I found really interesting, I never thought of that. That it wasn’t just people say, well, the way you build your businesses like you’ve done what your businesses do is to hire good people because you get more bandwidth. Well, this is energy. And I thought, well, it was this outsourcing of the energy requirement that was another way to actually progress humanity. 

Byron [04:24]: Yeah, let’s dive into that. Because there are really two things going on. There’s that one that you mentioned, our bodies consume 100 watts of power. And then, some time ago, we learned how to domesticate some animals. And oxen consume twice as much, twice as many calories as we do. So they run on 200 watts. And man, the minute you would like, get a couple of oxen, you were in business, you had your 100 Watts, and then you had another 400. And all of a sudden, you are able to vastly increase your output. You can tell we were built for these brains because I said that 25% of our calories are used to maintain them. When you’re a baby, it’s like 90% all you are is a brain with a digestive tract waiting to grow up. And you think about a baby barely moving, but their brain has to still do all this stuff as ours do. 

So we learned how to harness animals, and then we learned a little trick: all this sunlight fell on the earth a long time ago. And it’s really interesting why we have access to that sunlight, that energy. And in part, it’s because you have to picture way back in the day when you had mushrooms the size of trees. So that’s what lived on the land, no trees at that point. And when it would fall over and die, we hadn’t evolved the bacteria that could break it down. So it would accumulate. And then stuff would grow out of that, and then it would fall over, and then stuff would grow out of that, and it would fall over until it gets 200 feet thick or something. And then the heat and the pressure just press all that down, and it becomes coal. And that is all that sunlight that fell on the earth all those years ago. And eventually, the microbes did evolve that could break it down. But that’s why we have these huge coal deposits because we luckily didn’t have the microbes that could turn that stuff, and release it. And so we learned how to build machinery that even increased that number of watts, that we could burn dramatically. And now in the West, the average person uses about 10,000 watts of power constantly. So now our bodies are just this tiny, tiny fraction of the energy we have at our disposal. Now, that’s only half of really what gave us progress. The other half is something different, which is the way that we learned how to accumulate knowledge. 

Now, for the longest time, for millions and millions of years, every creature on this planet could only write down stuff to remember it in one place. And that was in their DNA. And it works great. It gets a monarch butterfly from Canada to Mexico and all the way back to the same milkweed plant it left from even though four generations of monarchs have passed like it’s all in there in the DNA somewhere. But then what happened that we talked about in Act One is we got language, and language, although at first, I said, well, the primary thing is it allows us to think, then it allows us to communicate, but what it really does, the cool thing about it is it becomes our new genome. Yes, your biological genome is still in you, but you have a mental genome as well. And you can store stuff there. So when somebody says, here’s how you could drive from Canada to Mexico and back again, we have to learn it one time, and remember it.  

And so all of a sudden, we could remember things, episodic memory, the memory of specific things in the past, that were supercharged. Then, though that would be a lot, that meant that not only did I inherit the accumulated genome of everybody who lived before me, but I inherited their mental genome or at least a portion of it. The parts that come down to us, the part that is preserved. In theory, it’s supposed to be the best parts, Plato, but not, you know, Plato’s brother who wrote limericks or something, right, like it tries to keep the good stuff. But just like your own, DNA is full of junk DNA. Our minds are as well basically, we have all these Gilligan’s Island episodes in there that take up a lot of space and aren’t all that useful. But then it got real, as they say, and we learned how to write, and then we became a species with a single genome. And that’s everything that’s been written. And again, a lot of junk DNA out there. But you come to this paradox, which is, I first learned about this when I read an essay back in the 80s called “I, Pencil” by a guy named Leonard Read, and he pointed out that nobody knows how to make a pencil. 

Not a person on this planet who could like mine niort make that Thirroul and then process it and turn it into steel and then roll the steel out and all of that, like nobody, knows how to make it. And then you say, well, then how does it get made? How does it get made? It gets made because the species knows how to make it, the genome of the species knows how to make it, you know how to do a little part and somebody else knows how to do a little part, somebody else knows how to do a little part. And that’s kind of crazy because you take something like a smartphone. Now your body has 30 different elements in it. A smartphone has 60 elements, that thing is harder to make than you are, and how does that come together? How do that cobalt and everything come and get refined to come together and all of it just the mind-boggling complexity of how you would build a smartphone is stored in the planet planetary genome? So that’s kind of the setup, we’ve learned how to essentially magnify our power consumption past our 100 watts. And we’ve learned how to supercharge our genome by taking it and making it mental and then making it in all the books. And so the last thing I’ll say about that is you are born to an accumulation of knowledge that Leonardo da Vinci, in spite of all of his genius never had access to. And Leonardo was born into a heritage, and a group of knowledge and all that Marcus Aurelius couldn’t have ever imagined and all the way back. So our progress accumulates, because of this. Now, it does all have to be carefully handed down from generation to generation, you drop the ball one time, and it resets it back to the original. And we start all over again. But that’s unlikely to happen, we have to understand that we’re kind of Guardians of that, but it kind of naturally wants to preserve itself. So that’s our world today, we magnified our power consumption, and we use technology to make that even more effective. And then we store knowledge now distributed in a planetary brain, not only in our individual brains. I love that. 

And when I thought about this, we talked about ants, we were talking a lot about ants, but you were talking about the ant working as one, the ant hive, and the same with bees, your beekeeping experience, not bookkeeping. And that idea of working as an Agora, as a hive mind is so important, but then I also thought about the monarch that we talked about, this handing on of the knowledge from generation to generation. But then there’s this transformational one that goes on with all the knowledge of the previous generations. And as you say, at this stage, each phase of progression happened quicker than the previous one. And then there is a jump beyond biology. And this is where we jump from brains that think to rocks that think, and this is the huge change where the vast intellect becomes something totally different again. I’m writing a new book about superorganisms and I’m trying to think, that your body is a superorganism. Why is that? Well, you’re made of cells. And those cells all live. And they all come together, and they make you. But what are you? You’re not a cell, you’re not a primary unit of life, the way a cell is, cells are made of only nonliving things. So that’s the beginning of life, right?

Our cells, you’re something different, like you’re a system of cooperating cells who have come together for some purpose we do not know. And they come together and they form you. You have a unity about you, you feel like one person, but you’re really a cacophony of these, all the cellular action. And that’s a big mystery, like, we don’t know how that comes about, we don’t know what exactly we are, we don’t know if we are a brain or a mind or soul or a body, or a system or an illusion. There might not even really be you. So the book tries to kind of get at what happens when that stuff comes together. So what we hope to do – I made that remark earlier about Plato’s brother who wrote the limericks or whatever – kind of everything we produce, goes in libraries and one way or the other, like, you can picture a library, being full of dusty books, no one reads. And that’s sort of where everything goes. It’s like that last scene of the Indiana Jones movie, that first one, where they wheeled the Ark into that warehouse, and it’s just all boxes. That’s sort of what our knowledge is like now, it’s very hard to find anything. I mean, we have search engines that help us find casual searches, but it’s hard to bring that information together. Even if you had at all like, just mentally, we’re not up to it. So what we said we should do is we should build machines that can intake it all, and they can answer all the questions we don’t know how to answer. And that’s what we hope. And then, after we did that, we realized it was no longer a computation that was the problem, it was the data, it was really hard to, like get clean datasets, and then to train models on it, you had to be involved, and we just gum things up. And so we said, well, let’s just start snapping sensors onto these computers, they’ll collect their own data, and then they’ll figure out the patterns in it, and they’ll make predictions. I should note before we leave this topic, I should note that I don’t really believe in AI, in the sense that there are two kinds of, I think, unrelated things, the word means. One of them is that we have AI like your GPS in your car or your spam filter in your email. We have carefully trained it to do one thing, and it does that thing. And it’s marvelous technology, it requires a lot of data about the past, it requires finding patterns in it, finding out when those patterns apply and using it to make recommendations about the future.

If we never made any more advances in computers, or artificial intelligence, or anything, we got 40 years’ worth of work to do, just because the gap between what we know how to do and what we’ve done already is so huge, however, least in the news, right now, there’s a lot of talk about a different kind of artificial intelligence and that is general intelligence. That’s what you see in the movies, right?  That’s like, C-3PO, or commander data, or Eve from Ex Machina, or Scarlett Johansson in Her or it’s those things, and that is not generally believed to be this other version kind of on steroids. To do that kind of stuff, you need a different approach. The future is not always like the past. And sometimes we don’t know anything about the past, like, humans have all these capabilities, creativity is an example that doesn’t just I don’t think come from studying the past. So can we build this other thing?

Can we build that computer that’s as versatile as us? I am in a small minority of people in the AI world who don’t believe it. Because I think it’s all predicated on an assumption that people are machines. And if we are machines, and that is right, like we’ll build a mechanical person someday, but it’s unclear to me that we are machines. After all, we have these brains we don’t understand, and we have these minds that emerge from that. And somehow consciousness comes from that. And just to assert that we’re going to be able to build that… I mean I could very easily be wrong, but I don’t believe that’s a really possible thing. But that’s good because we don’t need that, frankly, what we need is more of the other stuff, that kind of the bread and butter kind of AI that solves real problems and magnifies what people are able to do. And that’s what we know how to build. And I think that’s what we’re gonna have. So I don’t think there’s anything about the technology that’s inherently fearful like I’m not afraid of it. I just think that… Have you ever heard of cargo cults?

Aidan  [19:30]: Only the Serge Gainsbourg song Cargo Cults…

Byron  [19:34]: Back in World War Two in the Pacific. Oftentimes, as the allies were making their way through these islands, they would get planes, they would build makeshift airports and the planes would land and then they would offload all this cargo that the soldiers needed. And they always shared it with the local population who thought Wow, this is pretty cool. You build an airport, and then a plane lands, and you get all this stuff. Like, it’s incredible. So they just started building kind of imitation landing strips. Maybe they have the headphones that the radio operator used so they used two coconut halves like something out of the aforementioned Gilligan’s Island, they would sometimes build fake planes out of plants, the way duck hunters use decoys to lure in the ducks to lure in the planes. Of course, the planes never landed, because there was much more to it than that. And I think intelligence, human intelligence is like that. And I think people trying to build general intelligence are part of a difficult cargo cult, they think if we can just make this thing, and it does the superficial things like a human, then, by golly, it’s going to be a human, the planes are going to start landing, and it’s going to bring us the cure for cancer. And that’s what they hope. And I’m just not part of that. But I could be wrong like I said.

Aidan  [21:15]: I find it so interesting, man, you had your own podcast for years, and you interviewed all the leading experts in AI. And one of the amazing things that happens when you have a podcast is when you collect enough dots, which are the interviews that they start to connect in ways that you couldn’t have imagined before. And one of the amazing serendipities that happens is because you keep getting a different lens through which to see and this is why I personally, I get so much out of doing the show myself, like really, really great knowledge. And when I was on holiday, I was saying I was reading your Act Three, but I was also reading, in preparation for an interview with Ian McGilchrist on this magnificent book, and you would love it, man. It’s called “Matter with Things” and it’s about the divided brain left and right hemispheres. But it’s the most complete where as I said to him, it’s an oeuvre. It’s a French work, it’s 3500 pages, it will take you a year to read it because it takes so long to absorb the information. But the chapter I was reading was on intuition.

And he was talking about experts. And that when you look at any experts, including master chess players, and this, you’ve talked about Kasparov in your work, you’ve talked about him being beaten by deep blue in The Fourth Age as well. And it dawned on me that he was talking about how many expert chess players make the move really quickly because they make it instinctively and instinctively, that’s the right hemisphere of this creative brain. And all the AI is doing is looking at the analytical logical side, just scanning all the pre-programmed moves, and it doesn’t have any intuition. And that was the penny drop moment for what you’re saying there to me that you cannot make that, that is coming from somewhere different. That is coming from somewhere that we don’t understand, that is like the universal Agora intelligence. It’s coming from sensations in the gut, literally the brain in the gut that you can’t emulate in machines. So I just wanted to throw that in, because it was just this beautiful moment of these two books coming together that I was like, ah, it was serendipity. Beautiful.

Byron  [23:37]: Yeah. I mean, I would agree with all of that. I mean, I don’t think we are just our brains. There are these flatworms that actually have a brain. And if you cut their head off with their brain give it a week and it’ll grow back. And yet they remember things from before they cut the head off. There was a guy who would train rats to run mazes. And he would then operate on the rats and remove different parts of the brain. And he never could find any spot he could remove that would break their ability to go through the maze. Another kind of example is if I said, name an alphabetical list of animals. You’d go, A alligator, B, Badger… C…, like, you would be kind of doing that one at a time. Right? But if you look at a concert pianist who is playing this incredibly complicated piece, they aren’t hitting a note and then a question goes to the brain and says well, what next? And then it comes back and then they hit another note, and then it’s just okay, now what? There’s something else completely going on there. Like there’s all that kind of stuff that just tells us that I think our knowledge is distributed throughout our bodies. I vaguely kind of believe in cellular memory, that there’s epigenetics, I mean, there’s all this stuff going on that we just are not privy to. So to think somehow that we’re going to be able to engineer something of that complexity. I’m just not convinced. I guess that’s the way I would say it. I just haven’t been convinced.

Aidan  [25:22]: I loved the monarch, you gave me that gift of the monarch going around the planet. I didn’t know that beautiful story. And, and you plant your milkweed in the back, hopefully, they’ll come and they’ll be part of the journey for you. But one of the things that dawned on me as well as, you mentioned epigenetics there. And there’s this amazing study on mice, and they artificially created the fear of cherry blossoms by releasing the smell into the cages and then giving them a little mild shock. And then because of the quick cycle of the litter, the next generation, put little brain scanners on them, and they all had fear. And then the next generation had the fear and it was never originally their fear, and it’s stuff like that, like how are you going to program that? Like that is not programmable. It’s just amazing.

Byron  [26:13]: There are good examples of that when this little nematode worm eats this one bacteria. It makes it sick basically doesn’t kill it. But it grabs a hunk of that RNA and sticks it in his own genome. And then four generations, you get four generations, that they know not to eat that thing. We can’t reproduce any of these in humans. So we just have to assume that, we have some vaguely equivalent structure. Do I write in this book about C. elegans, the nematode worm, and the 302 neurons?

Aidan  [26:55]: You do, man. And I have it here. You say “four to five animals on the planet are tiny nematode worms, each about as long as a hair is wide. They reach that level of evolutionary success with a brain of just three 302 neurons. The industrious honey bee’s brain has a million neurons and uses them to build complex multigenerational societies. An octopus has half a billion neurons with which it may have achieved consciousness. And then there we are, with brains of 100 billion neurons,” beautifully said.

Byron  [27:29]: Oh, thank you. Let me talk about nematodes. So a nematode has got 302 neurons, he’s got 969 cells, got 302 neurons, the 302 neurons have about 7700 connections between them. And it’s thought in the connections that are the magic. And so there’s a group called the Open worm project. And what they’ve been doing for over a decade, is trying to program behavior in a hypothetical digital neuron, such that if they put 302 of them arranged just like the nematode, and they connect them, just like the nematodes. You want that thing to start acting like a nematode swimming around the computer. Now, that would be something like, okay, we have now said, we know how a neuron works. And we can model it. I’m a huge admirer of the project and I go check in on it a lot. I kind of liked the dedication to it. There are people associated with it, who say, they may never do it, they may never figure it out. And if we can’t figure out how the 302 neurons and two of them are mysteriously not connected to the other 300. Like, go figure. Anyway, if we can’t figure out how those come together and make a nematode worm work, what chance do we have, to kind of like, not just figure out our own brains, but how we process intelligence overall. That’s why I just am not. Well, I’ve said it already, that I’m not a believer, I think there are limits that we’re going to hit with what we can do with computers because they aren’t people. They’re fast, and they have all these wonderful things. But that doesn’t mean they can do anything that we can do.

Aidan  [29:30]: I thought Byron again, and by the way, the Fourth Age is a fantastic book. Some of those examples Byron mentions in the Fourth Age, but then gives a kind of an overview of artificial intelligence, give us a little primer again, in Act Three of this book. So I’m going to jump past that primer and get to the AI that you’re particularly interested in towards this collective intelligence or the Agora, this superorganism, which is machine learning. So maybe you’ll take us through that little bit building towards the crescendo of this act.

Byron  [30:03]: We kind of think we make decisions based on information and data. I think our great great grandchildren are going to see us a little differently. They’re going to see us as largely going through life, just sort of making decisions on instinct to your point, just sort of capriciously deciding stuff. Like, where am I going to eat? I don’t know, I guess I’ll go to that pizza place, you might go to the pizza place and not enjoy it or, or whatever, like you just make decisions all day long. And what do you have, you may have like a couple of pieces of data, or something you heard from somebody, that’s very different, we kind of guess our way through life, I think I use the phrase like drunken sailors on shore leave, we’re just like, wandering around making decisions. I’ll go to college there, I’ll take that job, I will move to that city, just like we know what we’re doing. Now, imagine a different setup. Imagine for a moment that everything you did was recorded. And don’t worry about privacy yet, believe me, we’ll worry about it in a minute. But just put that aside, just think about the technology for a moment. What if every word I’m saying gets recorded? Everything I look at with my eyes, whether my eyes dilate, or not. Every bite of food I eat, I eat with a utensil that has a sensor in it that tells you exactly what’s in that thing. Everybody I see, every place I go, every breath I take, every time my heart beats, like, imagine if you could actually record it all. We are in the middle of building that world. We record more and more, and not out of some massive big, let’s record everything. But people are like, I want you to know, I don’t want spam emails anymore. Well, guess what it has to read every email to figure out which ones are spam. So we kind of build this world, this data collecting world a little bit at a time. But we’re definitely building it. I don’t know how you’d stop building it. So kind of the long story of our species is, well, we learn stuff and then forget it, and then they die, and then somebody else comes along and learns it and passes it along to somebody else, and they forget it, and then they die. And then somebody else finally learns it, and they pass it along to somebody who butchers it and gets it all wrong, then they die. And that’s like the story of our world, you just wonder about all the stuff that people have come up with, and have forgotten.

Now imagine with that thing, I was just talking about this digital echo of yourself where every single thing you do generates data. And not just data, but data about the outcome. What happened when you did all that? And then imagine, just imagine we had 100 years worth of this, that goes back to 1922, imagine you had 100 years of everything everybody did and what happened? Well, now all of a sudden, you have something very different, you have a way to optimize your own life, you can say “I am thinking of moving to [blank]”, and then there’s all of this data that can now inform whether that’s a good decision or not. Now, it’s still your choice, nothing is gonna make it for you. But when I think in the book I talk about if you’re out metal detecting on a beach, you got your metal detector, and you’re sweeping, you can dig anywhere on that beach, you want to but the metal detector buzzes over something I dig there… That’s the purpose of the metal detector. Not making me dig there. But if I’m smart, I will. And I dig there and just pull tabs or whatever, any case, the system is gonna tell you this stuff, and eventually, I think over time, we’re just gonna be like, alright, now, I’ll dig there. Why, where else would I dig? And more and more, we’re going to let machines make more decisions for us with us, of course, having the final approval. Now that, with people of my age, I’m 53. That’s like, right on this border of like is that weird and creepy or not? Like, I think in two or three generations, the idea that some knowledge base of all the activity of all the people and all the learning from it will inform all of my choices. Yeah. If your life is the sum total of the decisions that you make, and you make 500 decisions a day, imagine if you could do it 3% better, well that compounds over every day of your life. And then imagine if you do it 100% better and 200% better. Like, what if you really get good at it, then you live an entirely different kind of life informed by data. And what it is, is a true society.

It’s like the life experiences of every person going together to make everybody else’s life better and that’s what you want. Over time our species learns, and we have not only the species-wide genome but now species-wide memory. And that is a different world than what we have. Now, I didn’t go and say, Well, there are a lot of ways this can go south. But we can come to those in a minute. Like, that’s the overarching thing of what it seems like we’re doing with data collection, computers, artificial intelligence. This was not my quote, but somebody once tweeted, “Orwell’s mistake was that he didn’t realize we would be the ones who bought the cameras. And our only worry would be nobody was watching.” Not that we’re like, averse to sharing our lives… And I’ll just say one more thing about that. I mean, we kind of know it, because if you think about it, you go back 20 years, 30 years, people didn’t produce anything like they didn’t produce much. They didn’t write like most people didn’t write ever, it was a lot of hassle. You get the typewriter out, and then who’s gonna read it? Where are you gonna publish it, and people didn’t really do art as much as artists did, and then people didn’t make movies, movie makers did, but regular people didn’t. And all these technologies come along, and then we find out people, everybody, not everybody, but you give people a way to distribute music. And all of a sudden, everybody starts making music. And you give people a way to distribute video, and boom, you get YouTube and you invent blogging, and then you find 100 million people have things they wanted to say. And so overall, these technologies are hugely empowering, because they do allow us to try to live to our maximum potential. And if in fact, we believe that knowledge is power, If knowledge is power, then how much empowerment would that be to have the life experiences of everyone who lived the last 100 years, informing every decision you’re making? Maybe that’s somebody’s idea of a very bad future. Like, even if it wasn’t misused, I don’t know.

Aidan  [37:46]: I loved this part of the book. And I’d really love you to share a couple of great examples of pattern recognition that we just can’t see. But then you give us some examples of ones that we did eventually see. I’ll give you an example personally. So I remember going to the dentist once. And this lady dentist was just looking at my mouth. She goes, are you from this specific point in Ireland, this specific town in the country? And I was like, kind of going.. yeah like she wouldn’t have known that. And I go, how can you tell? And she goes by the pattern of the decay on your teeth, I did it as my thesis in college. And you’re from this place, because the water it’s, a small town in the countryside, and the water there lacks fluoride and lactose. And this is the pattern I saw. And I was like, wow. And then you talk about it because you said this could go south. You talk about it going south, with hookworms in the south, which is an amazing story that I’d love you to share. And ones that I told my kids about, was camel dung, brown frogs, and milk for the love of God.

Byron [39:00]: Yeah, so there are two real examples from history. One is that in the early 1900s, a common cure if you got dysentery and you happened to live in Egypt, was follow a camel around until it went to the bathroom, and then pick it up I don’t know if it’s technically manure or feces or what you would call it from a camel and eat it. And that in fact, would cure your dysentery. Now, you’ve got to stop and think like, who figured that out? Not who was eating camel dung, to begin with, but there had to be enough people where some had dysentery and some didn’t. And they’re like, wow, all these people with dysentery got better.

Aidan  [39:45]: I was telling my kids about this on holidays and they’re only young, and my oldest son goes, “who’s the first person who did that?”

Byron  [39:55]: I don’t know.

Aidan  [39:56]: He’s like, “Hey, check this out.”

Byron  [40:00]: It wouldn’t happen in five minutes. So you’d have to be like, I think that camel dung I ate a day before yesterday… and it had to be fresh and warm it turned out because it had basically antibiotics in it…

Aidan  [40:14]: Hey, Byron, I did what you told me, man, it didn’t work out. “Oh, was it steaming? Was it steaming? Oh, no. It has to be steaming. Alright, I’ll go back…” You got the wrong frog, man. Was it brown? 

Byron  [40:23]: They’ve actually taken what lived in it and turned it into a convenient pill, which is not branded camel dung. And then another one was in Russia. To keep your milk fresh. They figured out if you put a brown frog in it, it would stay fresh. Now we know that the frog secretes a kind of antibiotic that keeps the milk fresh. But you’re in the same boat. Like who decided I’m just gonna put a frog in my gallon of milk. And there’s somebody who did it, maybe a lot of people were doing that I don’t know. Some people were like, I’m noticing my milk lasted longer. And then they’re like, Well, I didn’t put a frog in mine, and mine went sour. And they’re like, Well, you borrow my frog.  You got the green frog. Those are two not only do you have to think that’s one of those things that people figured out and forgot. I doubt the first person who ate camel… But maybe the first person who happened to eat camel dung noticed that it cured their dysentery and went around, making it their life’s goal to tell everybody that. At some time somebody probably had to learn it and somebody else and somebody else and somebody else had to confirm it like, “No, it really does work.” But then there were other things that we kind of didn’t find out.

That would have been in the data, like not having enough iodine in diets, you would be able to see that in the data. They believe it had like a five IQ point difference. But it could have been as many as 15 in some areas that had real iodine deficiency. You had hookworms in the South because they didn’t dig the outhouses deep enough. And you had to have them over a certain depth so that worms couldn’t get up. And if you have hookworms and you walk around barefoot, they’ll come into you, and they’ll make you lethargic. And it infected a huge number of people. And nobody knew that’s what it was. And then you say, “Well, why was it in the southern United States and not the northern?” And it’s because like by 1920, the North, which is wealthier, had indoor plumbing almost everywhere, but the South still didn’t, they still used outhouses. And so boom, you figure that out, hey, dig your potty hole deeper, and you’re going to be smarter. Now the thing, of course, is, there could be 100 other things like that we’re doing wrong. Like, our natural IQ might be 300 for all I know, but because we eat egg whites. Or I don’t know, who knows, right? We’re stuck at 100. Like, who knows what is in the data that would make all of our lives better?

Aidan  [43:23]: When I was reading about hookworms, all I could hear in my head was dangling Ding, ding, ding, ding, ding dang. I go, whoa, whoa, don’t do anything. Do you have hookworms? I won’t go there. But ultimately, I agree totally with you. And maybe I’m aware of that. But I naturally had these thoughts when I was younger. Surely there are patterns or not, I didn’t even use that language. The language in my head to think was kind of, there are loads of things like I got injured a lot when I was playing sport. And I was like, there’s no data to show me what I’m doing wrong. And I’m putting all this effort in.

And I would just hate to know that I was doing all this effort, and I was actually making myself injured rather than doing less and actually being more productive. And that’s ultimately what I’m so optimistic about, the combination of human and machine, the centaur coming together to create something absolutely, totally different. And where I’m going with that is you too, and I really remember this from our first episode together on the Fourth Age when we did that a few years ago, was you’re an absolute tech optimist. Like all this work, there’s a lot of dystopian thinking about AI, you’re a utopian thinker about AI and I thought, your final message on that… I have a quote by the way that I’d love to share, that really does encapsulate that. But before I even go there, your tech optimism is very welcome. And I’d love you to share why you are a tech optimist?

Byron  [45:12]: Well, I’m not one, like an a priori commitment to it, like, I will find a silver lining to anything. I think it’s a reasoned conclusion from just a very few simple things that I know. One of them is, we were a timid species, like it rewarded us. Because if you saw a big rock, and thought it was a bear and ran away, you were better off than if you saw a bear and said that thing’s just a rock, and stayed put. So, by being kind of skittish and nervous about new things, and all of that, served us well. But I at least have to start by saying, okay, that’s probably how I’m coded. And now I want to mentally, like overcome that. And so I put that aside and say, maybe my instinct would be to be fearful. But what are the facts? The facts, as I see them are, that I think humanity hit a low point. 60,000/70,000/50,000 years ago, we hit a population bottleneck. And you can kind of tell that from the genetic diversity we had, the less genetic diversity humans have implies the population got really tiny. Humans have low genetic diversity, two chimps, who live on opposite sides of a river have more genetic diversity than two people living in different hemispheres with different ethnicities and everything. Cheetahs, by the way, or the other extreme, we probably got down to 40 cheetahs.

So every cheetah alive is a clone, really, of every other cheetah, and that’s not healthy for species generally. But we got down to a bottleneck, and you can debate how small it was. Let’s just say we got down to 1000 mating pairs of humans, that would be a reasonable guess. And then you say, “wow, 1000 mating pairs of humans” and you wouldn’t have bet on us back then. Right? Like we wouldn’t be the ones you’d be like, that’s the species that’s gonna kill it. But it was and why? Because we learned this trick of multiplying what we’re able to do by accessing energy by creating technology, which is how to magnify our own abilities. And we’ve consistently improved the lot of life for not just enough people, but ever more people. And if you look at any country, you could say the United States is better than it was 100 years ago, and then is any country and you could compare them to 100 years ago. And I would be willing to bet that almost by any measure, you could imagine, look at life expectancy, look at average income, look at infant mortality, self-government, Status of Women, individual liberty, all these different measures of progress, probably whichever country you just picked, things are better now than they were 100 years ago. So that’s kind of the second thing. And then the third thing that I believe is that we’re good. On balance, more people are good than bad. We would not have survived I think if we were disproportionately bad. I’ll give you a real example. I recently sold something on eBay. And as I have for 24 years… And so I sold something on eBay. And I packed it carefully and shipped it to the recipient. And the Recipient opened it and then filed a claim against me and said I just sent them a brick and wanted their money back. I did not send them a brick. I sent them the item that they bought, but they were like, “No, all he did was put a brick in the box.”

And if you think about it, if very many people did that 2%, 3%, 4%, you would break credit cards, like they can’t handle that much fraud. Without you knowing the commissions of the rates have to go way up. The fact that credit cards can charge vendors 2.5% and then give a 2% rebate to the cardholder, tells you there’s very little of that kind of stuff. That the system largely works and it’s largely a trust-based system. So, if you start with all of that, and you say, well, our nature is to be somewhat timid, we want to mentally understand that’s a predisposition. Second, we’re using technology to care for more people and provide for more people. That manifests in progress in different countries, some regrettably, much slower than others. And people are overwhelmingly good, not bad, more people want to build than destroy. I think if you put all that together, and you say, “Okay, we’ve had 10,000 years now of pretty good progress.” I don’t know by what logic, you’d say, “yeah, but it’s over. That’s it.” Because I don’t know really, that anything’s remarkably changed. And so that’s why I’m an optimist. It’s almost an inevitability at some point. Like, at some point, you have so much information. And there was a time in our past where there just wasn’t enough stuff, like, wasn’t enough food for everybody. There wasn’t enough time for everybody to go to school. And there wasn’t enough leisure for everybody, because survival was a full-time job, all these things. Now we’re overcoming those things right and left. The United States, I’m sad to say, throws away enough food to feed all the hungry people in the world. Now, we still need to figure out how to be better people and make sure everybody gets it. But one by one, we’re kind of sloughing off these gating factors of our history. That’s why I’m an optimist.

Aidan  [51:47]: I don’t think I can top that, man, I have a quote, but I’ll leave it to people in the book. Maybe I’ll just mention the Easter egg you left in the epilogue, where the real reason for stories, one of the main reasons for stories, which is so so important, and to your point, they’re in a time of rapid change. This reason behind stories is so important. But maybe you’ll finish on that, maybe you’ll finish on that point because it’s probably the most important one of all the reasons for stories. And before you even do that, where can people find you? We said this before, but some people may be joining us for the first time. Where can we find you? You do keynotes, you do workshops, you also write prolifically, and you have another book in the pipeline. Where is the HQ for the hive mind that is Byron Reese?

Byron  [52:43]: I’m Byron Reese anywhere. So you can go to: www.byronreese.com or Byron Reese on Twitter, or Byron Reese anywhere. I mean, my email address is byronreese@gmail.com like, easy to get a hold of. So the book gives 20 purposes of stories. And that’s way at the front. And then there’s an epilogue on the last page. And it opens with sometimes the story doesn’t make sense until the very end. This is from memory. I may be getting part of it wrong. And, and I ask like, there’s kind of two ways to look at life, and one of them, one narrative of what we are, is you’re a bag of chemicals and chemical reactions really an electrical impulse, and you kind of careen randomly your localized area that defies entropy, you kind of careen around, and maybe bump into another bag, and then careen and bump into another bag.

And then finally, someday you die and you dissipate, and there was actually no meaning to any of it. That’s kind of a very bleak way of seeing life, then there’s another view, that says that life, your life is not just a series of connected events, connected minutes throughout your whole life that just sort of happened, and that’s where it leads into say, there’s actually a 21st purpose of stories. It’s the one I left out, it’s the big one, saved it for the end, Big Finish. And it’s that stories give life meaning that if you don’t think of people as bags of chemicals careening around and pointless, empty and all that, and instead you say that everybody’s life has meaning and purpose and that everybody’s life is a story, that it’s made of stories. Carl Sagan wrote that beautiful piece about like we’re made of starstuff like, all the heavy elements that were made out of must have come from exploding stars. The stars started out as hydrogen and helium, and then as fusion happens, the heavier minerals, and heavier elements form, and then the storm blows up. And that’s what you’re made out of, starstuff. And it’s a beautiful thing, but I think misses the point of what we are. Yoda was right, we’re not this crude matter. And instead we, I think, are stories, and so it ends with the question. “If we are stories, then kind of the question you have to answer in your life as well. Who is telling the story?”

Aidan [55:36]: An absolutely beautiful way to finish, author of Stories, Dice, and Rocks That Think: How Humans Learned to See the Future and Shape it. Byron Reese. It’s always a pleasure.

Byron  [55:50]: Thank you so much. I had a great time.

Aidan [55:52]: I hope you enjoyed that series, Act One, Two, and Three with Byron Reese on his latest creation, Stories, Dice, and Rocks That Think, thanks to our sponsor Zai, we are able to bring this increased content. Zai boldly transforms the future of financial services with a suite of embedded products and services, enabling businesses to manage multiple payment workflows, and move funds with ease check out Zai at www.hellozai.com I’ll see you soon.

PRE-ORDER Byron's Latest Book

STORIES, DICE, AND ROCKS THAT THINK

Stories, Dice, and Rocks That Think: How Humans Learned to See the Future — and Shape it. What makes the human mind so unique? And how did we get this way?

Podcast and Radio Interviews

Mobile Presence Podcast

Best-Selling Author And Futurist Byron Reese On The Power Of Brand Storytelling

As humans, we are hard-wired to tell and share stories. We also gravitate to brands that tell a compelling story that connects with us on an emotional level. So, how do marketers shape narratives that resonate with their audiences? In episode #471, our host Peggy Anne Salz talks with Byron Reese, author of the upcoming book Stories, Dice, and Rocks That Think. He shares insight into how stories have driven the growth and development of human culture, and he outlines tips on how you can tell stories that persuade your customers to take action. 

NickSav.show

Byron Reese podcast interview on AI, NICKSAV Film & Music SHOW

An Interview on NickSav.com discussing how artificial intelligence affects our lives, the difference between narrow AI and general AI,  whether being human is something more than a machine,  challenges and philosophical questions raised by advancements in AI, why optimism matters and can make all the difference, and how AI might redefine creative work  LISTEN

 

Everyday MBA

An Interview with Kevin Craine on Every Day MBA discussing “The Fourth Age”, how AI makes humans smarter, and how AI will change the job market.  LISTEN

 

Nonprophets [Super] Forecasting Podcast

An interview with Atief, Robert, and Scott on the NonProphets podcast discussing “The Fourth age”, the skills necessary for an AI filled future, where the fear of what AI will do comes from, and thoughts about consciousness and free will and the implications for robots and AI.  LISTEN

Association Forum

An Interview with Michelle Mason on Association Forum discussing “The Fourth Age”, technologies effect on the future of work, the difference between narrow and general AI, and the need to be constantly learning. LISTEN

RoboPsych

An Interview with Carla and Tom on Robopsych Podcast discussing “The Fourth Age”, the anxiety of technological change, and what makes us human and comparing and contrasting with what AI could be.  LISTEN

The Bad Crypto Podcast

An Interview with Joel and Travis on The Bad Crypto Podcast discussing “The Fourth Age”, what is AI and what will it do to our jobs, how will AI and robots be used for war, and how will AI and robots effect our dignity.  LISTEN

Tech it Out with Mark Saltzman

An Interview with Marc Saltzman on Tech It Out discussing “The Fourth Age”, what makes us human, and where technology could take us.   LISTEN

The Hoomanist

 An Interview with Simone Salis on The Hoomanist discussing “The Fourth Age”, technology multiplying human ability, can AI be creative, and how jobs will shift.  LISTEN

Radio New Zealand

An Interview on Radio New Zealand discussing “The Fourth Age”, what we think of ourselves as humans and what that implies for AI, the concept of emergence, and the economic opportunity of AI.  LISTEN

An Interview with James Kotecki on the Kotecki on Tech, discussing “The Fourth Age”, the inevitability of technological progress, technological optimism vs pessimism, the disruption of jobs, and conscious computers.  LISTEN

New Books Network

An Interview with Carrie Lynn Evans on the New Books Network, discussing Byron’s book “The Fourth Age: Smart Robots, Conscious Computers and the Future of Humanity.” LISTEN

DojoLIVE!

An Interview on DojoLIVE! by Nearsoft, discussing Byron’s book “The Fourth Age: Smart Robots, Conscious Computers and the Future of Humanity.” WATCH

WorkMinus

An Interview on WorkMinus, discussing Byron’s thoughts on technology removing dehumanizing jobs, amplifying human productivity and other ideas from Byron’s book “The Fourth Age: Smart Robots, Conscious Computers and the Future of Humanity.” LISTEN

DM Radio

DM Radio and Host Eric Kavanagh – Narrow AI: Artificial Intelligence and the Future of Work – Original Air Date: November 29, 2018 The Guests Stefan Groschupf, SalesHero Faisal Abid, Zoom.ai Byron Reese, Gigaom Micah Hollingworth, Broadway.ai   About the Discussion Hollywood has it all wrong with respect to Artificial Intelligence (AI), at least for now.  LISTEN NOW

 

 

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