Technology, Connected - Can Democracy Survive AI? Yuval Noah Harari on Jobs, Creativity and Data

Episode Date: February 21, 2025

In Chapter 9 of Nexus, Yuval Noah Harari examines whether democracy can survive the data age and what happens when artificial intelligence begins to compete with humans in work, creativity and decision-making.Mark and Jeremy discuss Harari’s argument that AI could disrupt intellectual professions before many manual jobs. They also examine whether the deeper risk is not simply unemployment, but the loss of human agency, economic independence and purpose.The episode explores four principles Harari proposes for democratic societies adapting to AI: benevolence, decentralisation, mutuality and rest. These principles are intended to limit concentrated power, distribute control and give institutions time to understand technologies before adopting them at scale.In this episode, we discuss:Whether democracy can survive increasingly powerful AI systemsWhy intellectual and administrative jobs may be automated before manual workWhat Harari means by benevolence, decentralisation, mutuality and restWhether human creativity can remain distinct from machine-generated outputWhat children should learn in a labour market shaped by AIHow free digital services exchange convenience for personal dataWhether individuals should own or control the data generated about themHow AI could affect human agency, meaning and political participationThis isn’t only a discussion about whether AI will replace jobs. It’s about who controls the systems that make decisions, how democratic societies can hold those systems accountable, and what remains uniquely human when machines can produce language, images and ideas at scale.--TIMESTAMPS:(00:00) Tech optimism(01:29) Chapter 9 first impressions(03:14) The race for raw materials(06:02) Benevolence, decentralization, mutuality, change & rest(15:30) Automation assumptions are wrong(18:18) Motor skills and social skills in 2050(20:06) The flexible superpower (23:11) Creativity: the last refuge of the human condition(26:53) Does AI have exceptional test?(28:50) Reverse creativity(31:45) Go "Move 37"(33:52) Bank algorithm says no(37:15) Your AI girlfriend--Learn more: https://www.thinkingonpaper.xyz/technology-book-club/

Disruptors and Curious Minds, CEOs, founders, book lovers. Welcome to the Thinking on Paper Book Club. I'm Mark. This is Jeremy. And if you're listening to this, thank you. Thank yourself for being a critical thinker. Thank yourself for reading between the lines and understanding the importance of bringing your own conclusions to the impact of emerging technologies on business, on your culture, on your life, on your family.

In a world that celebrates the humdrum, you are special. Thank you for reading books with us. We're on chapter 9 of Nexus. And you know what, Jeremy? I'm feeling optimistic today. Because if we ignore for a moment the ongoing damage to the ecosystem, we can nevertheless try to comfort ourselves with the thought that eventually humans did learn how to build more benevolent industrial societies. Imperial conquests, world wars, genocides and totalitarian regimes were useful.

Woffal. Did I say useful? woeful experiments that taught humans how not to do it. By the end of the 20th century, some might argue humanity got it more or less right. Yet, even so, the message to the 21st century is bleak. If it took humanity so many terrible lessons to learn how to manage steam power and telegraphs, what would it cost to learn to manage bioengineering and AI? The question from chapter 9, Jeremy, as ever, first impressions.

first I want to deliver a public service announcement akin to your introductory statement synthesis cannot be outsourced contrary to popular opinion it actually happens in here through inputs this way this way and this way so yeah let's talk about so Mark's feeling positive I'm going to tiptoe through some kind of intermediary pre-positivity before we Hold on. Can you hear that? Do you hear that? That was the sound of my optimism bubble bursting, I think. Fair enough. Sorry about that. Short-lived, like a quark in the small world of micro particles. In the quark glue-on soup of life. Love it. All right. So it starts off with a pretty cool statement that, you know, that democracy is this,

this partnership between bureaucracy and mythology. I thought that was pretty interesting. And we run through bad use cases of technology. You know, the theme in this chapter is like, you know, hey, technology in and of itself can't end the world. It's humans mismanagement of new technologies that cause a lot of issues, right? So let's talk about the technology of imperialism, right? So that was a technology, right? We're due to the industrialization, you know, things becoming more industrial, these technologies that were invented, required raw materials.

And raw materials, the race for raw materials, sent people all over across the world, conquering other people for raw materials to feed their technologies. Millions of indigenous people crushed to allow other nations to level up, right? So again, this is the bad use of technology. We've been called imperialism and technology stepping a bit further. And we'll jump back in the positivity here in a second. So we talked about, you know, Stalinism, Nazism has been a theme that he's explored and is in a framework that he's explored. This is really interesting. The idea that Stalinism, Nazis and brought about the idea of industrial murder.

I was like, whoa, industrial murder. That's a hell of a way to say that. It's spot on. And then obviously the Industrial Revolution's effect on extinctions to other species and that sort of thing. And like you said, Mark, if we had trouble with these technologies and this was the telegraph and the steam engine, what's going to happen as we move forward with AI and, you know, all the other things that you're talking about? Well, I think the point of Chapter 9 is that if we replicate what came before, then the answer is not a very, Nice one for humanity.

I mean, okay, every time a technology emerges, everyone fears the apocalypse. That's not new. Like this fear of AI isn't new. The Luddites during the Industrial Revolution. But he says that, okay, the Luddites were right, kind of. There was a downside to the Industrial Revolution. Yes, everyone became more well. than they had ever been

and there was huge positives from it there was the downside it ended and changed traditional social, economic and political systems there was before the revolution and after the industrial revolution they were not the same

and yeah you mentioned war I've had enough of Stalin I don't want to talk about Stalin anymore he seems to go on about him in every single time to turn the corner yep yeah ecological collapse he speaks about the downs side of it. And he proposes a way forward, the democratic way forward to, can democracy live in this world, in this AI world, can the democratic way? And he lays out the structure, the patterns, the things that we need to follow from the democratic way to survive. So as we've talked about

Google changing their AI principles, I don't mean to harp on this. but I think it's a, there's an interesting analogy. It's like literally Yuval and Stalin, the turdine. Swatum. Yeah. So there's a list of principles that he alludes to in here that are kind of principles for democracies to follow related to the proper use of technology. And there are four of them.

Before we kick that off, here's a quote that I found pretty cool. Technology is rarely deterministic. Yeah. meaning it's just like it's not going to it's not going to buy itself wreak havoc but actually now that I think about it yeah we we get to curse wiles point in time and space and and you know maybe it starts to become deterministic but hey we're staying positive today let's talk about these principles so the first one he calls benevolence meaning you know if if these networks are collecting my data the networks that collect my data should help you me rather than manipulate me. It seems pretty straightforward, but I think a lot of people don't look at that when they're building something, especially, not even nefarious, building something to make money with, right? Yeah, and he uses the health system. Doctors know everything about us.

Our boss, to some extent, knows a lot about us, and they don't use that information to manipulate us. They use that information to help us. It's benevolence, the first principle in it. what does he say? I love the idea of him calling the business model being flawed, like big tech business model being flawed because we pay for these services. Oh, all of this stuff is free. It's great.

You know, like a Gmail account, oh, it's free. It's great. Or, you know, this entry level account for Dropbox or whatever. Oh, it's free. Well, we pay for it with our information, right? So that's the tradeoff. And he references, you know, we won't go, we won't pay Nike. with our information and get a set of shoes.

But I would argue, I think there'd be a lot of people that would give them information if they were sending out sets of shoes. What do they want to know if I get a pair of Air Jordans out of it? They're about 300 quid these days. So yeah, they'll give them my address, my email address. So that's number one, number two is decentralization. A democratic society should never allow all its information to be concentrated in one place, no matter whether that hub is the government or a private corporation.

Don't cross the streams. They're saying don't cross the streams. Don't allow access to all the databases to everybody. Here's an interesting quote there. For the survival of democracy, some inefficiency is a feature, not a bug. Interesting. Is that about self-correcting mechanisms?

Yeah, you can't, I don't think you can optimize those yet, right? There has to be a, well, we'll talk more about self-correcting mechanisms because you have to understand the technology that you're attempting to correct, which is a big challenge. Let's talk about mutuality. Yeah, the third democratic principle. And dare we say our theme of top down and bottom up comes up again, Mark. Tell me about mutuality. If democracies increase surveillance of individuals, they must simultaneously increase surveillance of governments and corporations too. My note for mutuality is, I don't have much hope for this one.

I can buy into benevolence and decentralization, but the idea of this kind of mutual exchange of information. I mean, you don't think the Trump White House is going to let me peek in their meetings and take a listen to what they're doing and look at their data exchanges for me to make a better decision and hold them accountable. You don't think that is a possibility? No, if they know more about us, while we simultaneously know more about them, the balance is kept. I mean, yeah, no. Come on.

But as an operating principle, like. Oh, yeah, as an operating principle, yes, I agree. Yeah, applying them in real life. Reality has a nasty habit of like playing with your principles, didn't it? I also think his fourth is change and rest. I think he'd run out of nouns as well as he had been elements, decentralization, neutrality, and change and rest. I thought that was, so the change one I understood.

And here's an interesting, you know, quote from a repression can take the form of denying humans the ability to change or denying them the opportunity to rest, right? So racism, caste systems, you know, these were opposed as, if you go counter to them, you're going against the laws of nature, the laws of God, enter intersubjective realities, again, imposing a balance of truth and order on a group of people, right? And, you know, the idea that, you know, denying changing between casts or denying the ability to be considered equal as humans, kept the order of oppression on top there. piece, or I'm sorry, the rest piece, I didn't really grab.

I didn't really grab this bit. I was thinking of it more of like we are in constantly in flux. Our neurons are forming and reforming with like our neural network. They're plastic. Things are changing. We're never the same. The rest part, we all need a rest. I don't know, but he goes from that to the balance of, and I quite like this example,

but I'm going to take. my disagreement out on this as well. He talks about non-rigid AI and rather than an AI predicting your illness, so this is a continuation from the changing rest, rather than the AI predicting your illness, it helps you avoid being ill. And this is like this different way of looking at it. And I was thinking about the paperclip experiment in last week's show. We were talking about how miss a lie, how you can, If your goals are misaligned, then you can end up in a very bad state. And if the AI's goal is to make you feel healthy or remain healthy, what ends might it go to to make sure that you remain healthy?

I don't know. Killing everyone in all the power stations, shutting down all pollution. There's plenty of incredibly psychotic ways that an AI could go about ensuring your health and safety. You know what I called that? I wrote down in the book margin, The Tale of Two Algorithms, the predicting illness to feed decisions to other entities to make decisions about lending you money

and what your insurance rate should be and all of these other things versus helping you avoid illness by, you know, say, hey, Mark, ding, ding, ding, time to go out for a run. Hey, Mark, put down that cupcake, right? Some of those things. Tale of two algorithms. Yeah, yeah, I love it.

like that. We should write a book about it. It was the best of times. It was the worst of times. And people are very aware, I think, of this idea of being surveyed to such a point that the AI or the computers know, for example, that you have something growing inside of you and it's not good and they pass that information onto your insurance company and your insurance company increase your price plan and then you can't get a loan because the insurance company know that you're going to have cancer in five years and that kind of AI feeding that wheel. And if you have the two AIs and you have one that isn't feeding that wheel, but isn't feeding a different flywheel about making you healthy and maybe, you know,

then you get the loan and you, good things happen. Well, this is interesting. You know, I've brought up open mustard seed before on these shows. And it's like the precursor to, you know, personal data sovereignty. You know, it was a non-block chain solution, a database-driven solution. I think it was out of MIT. But like blockchain could,

could have an impact in this where you capture and own the on-off streams of data and you have your own, you have like APIs. Like normally when, you know, apps have APIs, you could have APIs that turn on and off the feed

one way, the other way, um, to where the data is used, how you want to use it. But the only way to make sure for certain is that you actually own a digital thing that no one else controls, that no one else sponsors, right? Hey, here's a free thing that you can use, but I need all your shit. It's, it's, it's, it's, it's, it's, it's, it's a thing that you own independently. And you know by operating these levers, your data is not going here and you're allowing a little bit of it to go here.

Um, I think there's an opportunity there somewhere, but I don't know that, I don't know that it will be allowed. zero knowledge proofs. We should check, listeners, check out our blockchain episodes and connect some dots, some technological. Synthesis cannot be outsourced. Automation, you want to go there? Automation, exactly.

Yeah, the first part is about surveillance. The second part is about automation. And you know what they say about the assumptions being the mother of all effort, don't you? Assumptions which are wrong. He has three assumptions. about automation, which I have a feeling

you might disagree on on one of them to some extent. Maybe not. Maybe your opinions changed on that. Let's find out. Assumption number one about the future of AI. AI will

not take intellectual jobs. I think we all know that, don't we, by now? AI will not take intellectual jobs? Yeah. Like it was kind of the assumption was that AI would take all the menial tasks, wasn't it? Whereas in fact, it will take all of the jobs where you need to use your brain. What's an intellect?

What's an example of an intellectual job? Copywriter, designer, architect, doctor, lawyer. Okay. And you don't think AI will take some of those jobs? Yeah, that's just, yeah, it will. Oh, okay. So the assumption, the assumption was wrong. My mind, I'd be wording it in the right way.

Should have let chat GPT set that one up for you. I should have, but I didn't because that's why I'm here. And that's why you're here listening to this because you think for yourself, you think on paper, you read books. And yeah, you make mistakes as you try to understand it. Anyway, so yeah, the nurses will be safe. The doctors won't. I thought that was really interesting. So my brother's a doctor.

He's an anesthesiologist, super talented guy, trained. in the art of keeping someone barely alive so life-saving procedures can happen. I mean, there's an art to that. There's a physical aspect to that. And what I thought was interesting about some doctor's jobs being threatened, the idea of the doctors that assess, diagnose, and recommend could probably see some kind of AI-tubeau. tools start taking over some of that stuff. We're already seeing that kind of stuff. But I don't think an AI robot is going to be in charge of the machine that manipulates the drugs that, you know, keeps someone barely alive. But then on the nurse side, I thought that was really

interesting. There's a lot of physical aspects to nursing that that robot hands just can't do yet, right? And AI won't be able to do, right? Yeah. That's like those intricate skills, yes. So here's the quote, people who want a job. in 2050 should perhaps invest in motor skills and social skills as much as intellect. Yeah, well, that's why I said I'm going to quit and go chop down trees. That's my job. I'm going to butcher this stat completely. So apologies to all the doctors out there. For me, getting it completely wrong. Please tell me the correct statistic. But I want to say, I want to ask, what is the second biggest killer?

in the United States each year and it's medical error. Really? So let's fact-check that. I might factor-check that in real time. But yeah, it's one of those things where misdiagnosis over wrong quantity of drugs or whatever. It's high. I wouldn't have been the two, but it's high. It's very high.

I don't know the exact number, so. But it's high. It's more than it should be. Okay. Well, let's, so here's, here's a couple of things that stood out to me. And this, this was referenced in our Paki McCormack episode, Call to Humanity. What was it?

What was the title? Most human wins. Most human wins, right? So listen to that, because we break down the whole 35-page paper with, with thoughts. Would love you to read it, too, because, you know, you can read and think on paper and write a little bit. But very similar suggestions from Harari on this. one, right? So beyond the, you know, be on the lookout for these for these next automation targets, right? I was writing down continual tweaking, continual learning, refining what you do,

repositioning what you do rather than sticking to one lane because, you know what's going to be the next superpower, Mark? The next superpower that people should be majoring in is flexibility. And not just flexibility in one moment, almost malleability. Right? Like being able to retrain and adjust to a market, a job market that is just going to change so rapidly that we're not going to be able to jump in and say, hey, I'm going to go to school. I'm going to be an accountant. I'm just going to be, I'm going to go work for someone. I'm going to be their accountant. And at the end of 30 years, I'm going to bounce out and do some stuff. It's going to be way different for those jumping in. And for those of us still in. thought on kids and what the next generation and what we should be teaching our kids and where we should be pushing our kids and where we should be encouraging them to read, think, learn, right, get better. Before we debunk the other assumptions about automation in the age of AI, number one AI,

well, yeah, okay, and make that assumption wrong way. Creativity is unique to humans. Another common but mistaken assumption is that creativity is unique to humans, so it would be difficult to automate any job that requires creativity. Creativity is often defined as the ability to recognize patterns and then break them. If so, then in many fields, computers are likely to become more creative than us because they excel at pattern recognition. I'm, what is it about this question? I think that, I don't think any other question in AI at the moment gets people's blood flowing more than the question about AI and creativity.

I see it all the time on social media. I see it all the time on television and newspapers. It's like you have the AI is not creative, the human touch. I can do it. I can't. And then you have increasingly more people like Yuval here who say, well, that's not really true, is it? So the definition of creativity is kind of close, right, to the way I think about it. I talk about creativity as a unique rearrangement of found elements, right?

and you know a found element could be a chord it could be a rhythm here I go with a music analogy again right it could be you know a topic right and you put a you kind of put a song together but you know no one owns a G chord no one owns 4-4 rhythm but there are these like found elements that you kind of put your stamp on and the the human element I've got a friend who's a drummer he's a drummer for perpetual groove he helped me out with with kind of a two-month crash course in in getting my fundamentals as a drummer a little bit better. But I saw him post recently that he's committed to never use a click track ever, ever in recording or ever in live, which a lot of drummers do.

And that's like the element. That's your feel, right? It's your stamp. It's like because you're not always here. You're a little bit here or a little bit there. It is a hot button though, Mark. It is like. It is a very, I think it's a very hot button because people,

It's almost like the last refuge of so many people. Like it's the last refuge of the human condition is your creativity and the threat that, if not now, very soon, that will be taken away from you, gets people's backup. And I understand the passion. I understand the vitriol. I understand the disagreement. Let's, let's, oh, go ahead, finish.

Well, I'm increasingly. in the camp of Yuval to a degree, I think that creativity isn't binary. I think there are many, many layers to it, and we don't need to go very far into the past to realize that some people are more creative than others. So I don't think you can really say creativity is unique to humans. Maybe you can say great art or ultimate creativity,

some level of it. But most people aren't very creative. Sorry, people. The people listen to this are, obviously, you're creative. Well, I think, I think here's, I'll debunk that, Mark, and we could riff on this for days. Go, go, go. I think everyone has creative potential, but I think a lot of people, through self-talk, through getting it beat out of us in school, like, all of these different things. Labelling is a very, very, very, very powerful, powerful destroyer of creativity.

I'm this, not that. I'm not creative. Well, have you ever given yourself the space to try to be creative? In order to be creative, you've got to be willing to look a little silly, you've got to be vulnerable, you've got to put bad shit out, and you've got to keep putting bad shit out, and then from there you start to learn a little bit about that. But let's approach this objectively or try to approach it objectively as Harare is. computers definitely are great at pattern recognition. They're better at humans at pattern recognition. So if we had a thought experiment here and said, all right, let's look at, I don't know, let's look at like four blocks, four elements,

four things that could be combined in only a certain number of ways. Say four things, 20 different ways that these things could be combined, right? And then you look at the, combinations of that. And then you notice the patterns, the computer notices the patterns, and then you assign it and say, computer break the patterns. And then they come out with, you know, 120 ways to break those patterns and those combinations. If you look at it specifically as recognizing patterns and breaking patterns, could they

identify a bunch of different options? Probably. Could they identify what the coolest option is, what the option is, what the option that would resonate with 24-year-olds who love EDM and, you know, nacho cheese and velvet couches, like, I think that might be. So are you asking if it could have taste? I'm saying that it might not be able to have taste necessarily. Can it create the available options? Sure. Could it create an option that resonates with a taste profile, maybe that it creates for itself, because then it would have something to point

to. It would have to first create a taste profile and then say, hey, align all the breakable options into that taste profile. I don't know. I'm kind of, is my exceptional taste? Is that a result of just my experience? And if it is just a result of my experience, then it can be learned. Well, here's exceptional taste. So check this out. You've, Are you familiar with, have you messed around with like garage band and recorded stuff and like you used apps? I've been in a garage band or a garage band as I call them. Yes. Oh, you don't use Apple stuff.

You probably haven't used garage band. My brother has used garage band. I am familiar with it. Yes. Okay. So it has these like little plugins, right? That plugins are like equalizers or compressors or, you know, reverb modules, all these ways to affect sound that can stitch together a song in an interesting way. So there are plugins where you used to have to be like, oh, I've got to be an audio engineer and understand acoustic principles and all these things to kind of like listen and feel and tweak.

And sometimes you could create not just based on those principles, but based on the sound that you want to, right? But now there are preset modules. There are preset settings in there that are almost like Mark's EQ from the 1960s, right? and they've basically been able to encapsulate that EQ preset, right? So that's like encapsulating a bit of taste. But then like Paki McCormick says, and I'm continuing to like fall down this rabbit hole, as Pachy McCormack kind of said, then you start getting to higher levels of abstraction. So instead of being in the weeds of, you know, I need to boost, I need to boost 100 hertz,

you know, by 1 dB, you're focusing on something bigger than the EQ sound of the kick drum. You're focusing on something at a higher level of abstraction, knowing that that is already a Lego block. Can I ask you a question? I don't care if it's not really about AI. We're talking about creativity. We're talking about what comes next. So I think it's relevant.

I want to ask you about what I like to refer as reverse creativity. And I was thinking about this yesterday because I was, watching a Rabeato video, and if everyone, if you don't know who Rabeato is and you like music, check him out. And he was breaking down a Pearl Jam song, Black, okay? And it's incredible, but it's one of the first songs Pearl Jam wrote, like Eddie Vedder was 20, I think, when he wrote the lyrics to it, McCready, yeah, they were 20 years old. And it's, it's a genius, it's a masterful, it's just a perfect song. And, listening to recent pill jam stuff and doesn't have the same it's like and you see this with a lot

of bands you see it with writers you see it with artists you see it with people in every creative domain that they release this work when they're very young that's never beaten in fact their work their creativity at least according to our taste goes down and down and down a lot of the time not all the time a lot of the time um you know bowie you get people like that go against that but a lot of people do that and reverse creativity Jeremy we're like unlearning how to be creative and if you can unlearn you can learn I would I'm a big fan of unlearning um I think one of the most powerful questions I've ever asked anybody is what is what what is one thing that uh you would unlearn that there that you have unlearned that has had the biggest impact on your worldview right

because we get into these patterns, we get into these hard-coded beliefs and systems that we have, and we start to rely on those things instead of wanting to understand, wanting to, when we're younger, I think we want to just get after stuff, right? We want to, you know, push back on things. And, you know, like the NASA test, the Beth Jarman and I can't remember the other psychologist back in the, we referenced this in a previous episode, how divergent thinking, the ability to think divergent goes down is reduced as we get older. So maybe there's a correlation between that and, you know, artists as they get older,

having, you know, their divergent thinking kind of drop in a way. It's weird to say, like, that an artist would lose the capacity to divergently think. But athletes, you know, lose the ability to dunk a basketball when they're 80 years old, right? So I don't know if it's a similar thing. Unless you, LeBron James. Right. He's 40, man. He's not 80.

Outliers. Okay. I think that links quite well to Move 37 in Go. We all know Move 37 in that famous game of Go, don't we, when the AI beat the best Go player

that's ever lived with a move with an alien move, with an unfathomable move and he uses this word unfathomability. We just don't know why. And I think that's quite, like a link back to creativity. We don't know why.

I know anyone who's read the creative act, we don't know why. I mean, if we're taking it from the ether, okay, computers not doing that, but we don't know why. Why? That's really interesting. I never thought about, like, the creative act or how someone makes something from nothing is like a black box, too, just like an algorithm is a black box, just like AI as a black box. You don't really understand how all these, what do you call them, opaque and impossibly intricate little pieces of, let's see, opaque and impossibly intricate chains of minute signals, that could apply to the creative process, right? I can't crack your brain

and understand why you made this decision or that. You probably couldn't even walk me through why you made certain creative decisions necessarily. They just came as these really cool aha moments. Which is exactly what he speaks about with the explain your decision, this new human right, the right to an explanation. And he speaks exactly about that,

doesn't he? A lot of the time, when you ask somebody why, they say, because X. And then he goes down if you ask AI, why, and anyone who's used the new Chinese AI can see that it goes through its decisions. It's like, because ABC,

D, E, FGA, all the way, around the alphabet, around and around and around and around again, thousands of reasons why. I always better at explaining why. Well, not necessarily. So let me point back to something earlier. Let me see where I can find this. There's a point where people become apathetic when there's too much information thrown at them,

or it's too complex of information, right? So say you get an algorithm, you go for a loan mark, and, you know, your, your result is determined by algorithm and you don't get the loan and the algorithms required to give you an explanation. The explanation comes back. It's so convoluted and like so, it's like your, your battery life and your cell phone was, you know, 20%. You didn't shave today. You didn't use the proper soap when you were washing your hands and you wore a hoodie and you, you, you, you, put an unequal amount of pressure when you're walking between your right and your left foot. Like all of that shit, you're just, you're just like, why didn't I get the damn loan? Like my, my credit is great.

I always pay back my stuff. I've got it, I've never had a check bounce, like all the important things, but there's throwing a spew of stuff at you where you're just like, well, what can I do, you know? When people are overwhelmed by a deluge of unfamiliar technical details, they might react with despair for apathy. When I read that, I reworded that. When people are overwhelmed with doom and gloom of AI taking over the world, they might react with despair and apathy. Nexus. Read Nexus too many times and that's all you have. I was going to ask you a question about what you just said, but I forgot what he just said. Speaking of reactions to getting denied by alone, let's talk about emotions, right? So emotions and emotional intelligence, I wanted to bring this up earlier, computers outperform

people in emotional intelligence because guess what? They don't have emotions. Yeah. Assumption number three, AI can't replace jobs that need emotional intelligence. Yeah, therapists, psychologists. Wow. Wow. Because they don't have the baggage of like, you know, having a quick trigger anger button, right? Or, you know, they don't have the baggage of maybe the, you know, the person who's reacting to something, you know, they're not hung over and short-tempered and all of that kind of stuff. They're just there, they're recognizing stuff. And there's experiments,

aren't there, where people in a blind test, they prefer. I'm a bit dubious of these blind tests where they pit a doctor or a real psychologist or a real therapist against a chat GPT. Because anyone who's used chat GPT, surely they can tell what the chat GPT saying, it's an AI, because they don't speak like or at least not really so i'm a bit deuce about that but this one is the second hot button isn't it if creativity is the most divisive and it gets people's blood boiling the most maybe i can't replace jobs that need emotional intelligence is the second yep and and that and that pops into this this i wrote down big question for ai applications so for anyone that's that's considering you know using ai for

or something. This should be like the foundational first question in the flow chart. You know the if this, then that diagram and flow and matrix and stuff, okay, do they A want to solve a problem or do they B want to establish a relationship with a conscious entity? And A or B, I would say, you know, AI right now hyper-focused and great to solve a particular problem, right? But if I want to hang out with Mark, you know, and in, and like this, like we're doing right now, or go down to the pub and have a beer with you, you know, that is going to be a little more difficult to pull off and probably darker and dangerous to pull off. If that option were ever available, that scares the shit out of me.

What's that film? Her, is it? Yeah. but if your goal is to get better for emotionally, physically, psychologically, then you give me the best human or machine. Right, we're going on. Let's move on to a question I want to ask you. I think the final part of this,

which keeps me up at night. The only thing that really keeps me up at night is this. Gas. What my never-ending turmoil in the job markets look like? What do we need to teach our kids to survive in the never-ending turmoil of the job market? Flexibility, malleability, Bruce Lee move like water, be driven by curiosity so you can dive into stuff that you need to dive into. but it turns out that you're already interested in it, right? Because you're a curious individual.

You know, if you can maintain that curiosity, because you're going to have to learn something and then relearn something. And then before you know it, the rug gets pulled and you have to change again. And certain systems now do that thing. So you have to take what you learned swimming in this little pool and jump into a brand new pool that you're going to swim in for 18 months or two years. and then that pool is going to dry out and you'll have to jump into another pool. You're not going to be on a raft anymore with a cocktail with your feet up and, you know,

kind of pointing down with your countdown to retirement clock. It's going to be, and this isn't bad. Like this isn't a bad thing. This is like this is staying kind of true to your curiosity and true to what's meaningful to you, right? because you should be able to kind of bounce around and shift a little bit as you as you figure yourself out. As long as you take care of the general money side of what needs to come in, I guess. Cushing the blow we need to prepare in advance. In particular, we need to equip younger generations with skills that will be relevant to the job market of 2050.

Unfortunately, nobody is certain what skills we should teach children in school and students in university because we cannot predict which jobs and tasks will disappear and which ones will look. emerge and so like you said well okay this guy i think i have the same critique of this as i did in our amazing episode of packing mccormac's thinking on paper xyz check it out is it still leaves a lot of collateral damage with the people who simply can't or won't or refuse or don't have access to these ways of thinking these the schools the parents the systems the communities that are doing this. So what happens to the 99%?

Yeah, I think, I think it's kind of a forced evolution maybe in a way. Like here's one, here's one job, I think, that that would be really good. What about, what about algorithm explainers, right? Someone that can take the complexity of an algorithm and translate it into the stories that humans understand, right? into that. AI does that better than a person. That's not a job. No?

No. That's pattern recognition and explaining. No. They've read every book in the world. They know all the stories. No. Next. Okay. All right. I put down here, I put down here, we need algorithm explainers like Catholics need priests. We don't need algorithm explainers. We need, I thought you were going to say cat sitters then, so yeah, that would be a good job. Something involving animals.

Well, but no, you can't have a technology babysitting a technology. Yeah, exactly. So that's what, like, a person. I think that physical and I think physical work like that, I think a lot of the jobs will come there. I think that our desire to, however creative AI gets, we will, I want to see people running. I want to see people playing the guitar. I want to see people singing. So I think there's still a lot of room there.

In terms of actual job, that's a good thing. Should we try and name five now? And I don't think that algorithm explainer counts. We've got cat sitter. No, I think algorithm explainer absolutely counts. I'm going to hold to that. And I'm going to continue to define that job description as we move forward. Listeners, what do you think?

Is algorithm explainer a lot? likely job in 2050 or will that be done by an algorithm? And listening, please put your ideas for jobs that will exist in 2050. We'd like to hear them. All right. Last piece of the puzzle for you curious listeners out there, you thinkers on paper. Let's talk about digital anarchy and land the plane here. So bots pretending to be humans, 2020 study, 40%

of the tweets on Twitter were produced by bots. Pretty interesting. This is an unfair one-way street, though, because bots can connect with people on an emotional level and influence them, but we can't do the same thing to bots. I thought that was a really interesting thing to point out. Not a fair fight.

And is scale now unscalable? Is scale now unscailable? What I mean is our ability to connect and communicate with people all over the world in near instant real time, is that now not scalable because the point, we're at the point at which, like, things that aren't human can now influence that thing. So do we need to like pull back to sitting on rocking chairs with, you know, tea and talking to each other?

Are we going to start seeing a pull back to the more human level of things? Who knows? Stay tuned. Conversational anarchy, digital anarchy, I think if 40% of the content on Twitter is written by bots, an extra 40% is written by people using bots. So that's 80% of the content on Twitter is written by algorithms and there's probably more than that. Yeah, conversational anarchy, I like the idea of, I don't know if I like the idea, I like the way he explained. If bots are having conversations with bots and democracy is all about conversation. At what point does democracy become a conversation between?

between bots, between computers. What did you think of the counterfeit analogy? Money market counterfeit analogy? The counterfeit analogy. So he talks about Daniel Dennett philosopher that talked about the idea that, you know, money markets create trust or there's trust in money markets because there are measures to limit counterfeiting money, right? So if everyone's able to counterfeit money, the value of money would be greatly diminished.

So then we start thinking about, all right, he says bots can participate in conversations, but they need to announce themselves as bots because you lose trust. And it's like losing trust in money. You lose trust in exchanges and communication in this self-correcting mechanism. But we have it rooted in the idea of counterfeiting or preventing counterfeiting in the money markets helped increase trust. What if we issued something like, hey, there's no counterfeit humans allowed. in conversations or there is, but you have to announce yourself.

I am not human, Mark. You know, I like it in principle. I mean, it's an interesting idea. It's an interesting idea. I'm not sure how you make it a reality. I mean, that's a bit like content at large, isn't it? This article was written with the help of an AI. This article was written by AI.

This, yeah. I like the idea. It's a bit like, what's that TV show where all the bots are walking around with a big sign on them saying, I am a bot and ostracized from society. And everyone boos when they walk past. All right.

So we need to open up the Thinking on Paper merch store. The first T-shirt and hat combination is going to be massaging the Hamiltonian. And the next one will be not a bot. How about not a bot? Not a bot. They would sell like hot bots we should do now. Let's try it. Cool.

All right. Well, time to land the proverbial plane mark. Chapter 9 is done. How many more do we have left? We have two totalitarianism, which is short, and the Silicon Curtain. Maybe we can do both of those next week. Because we have to choose our next book, ladies and gentlemen. drum roll we haven't we haven't decided yet so choose hey choose it for us let us know what give us a give us a

yeah send it send an email to hello at thinking on paper dot xyz with your book recommendations or put them in the comments and if we choose your book you can come and do this whole thing with us and and and we'll have a blast but uh yeah thinking on paper dot xyz you can find us on youtube spotify there you have it be disruptive stay curious Don't be a bot. Read books. See you next week.