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The AI-Ready Human Deep Dive · Humanity Working

• 0:00
  SPEAKER_01: Welcome back to Humanity Working.
• 0:01
  SPEAKER_01: Now it's been a while as I've been launching my book, The AI Ready Human, but I want you to rest assured that we're now back with lots of great episodes and interviews.
• 0:10
  SPEAKER_01: Today's episode is a special one as Matt and I are going to go into some detail on the themes of the book, and over the next few weeks we'll be mixing interviews with some deep dives on how people can thrive in the world of AI.
• 0:24
  SPEAKER_01: Look out for episodes which will generally drop on Tuesdays and Thursdays, and we'll also be doing deep dives in my newsletter on humanityworking.net.
• 0:34
  SPEAKER_01: The book is available on Amazon and Barnes Noble online, or if you'd like a special signed hardcover edition, just go to Paulslater.ai forward slash book and you can get your own copy.
• 0:45
  SPEAKER_01: Don't worry, all of that information will be in the show notes.
• 0:48
  SPEAKER_01: Alright, thanks for listening to Humanity Working, and now on with the show.
• 1:00
  SPEAKER_03: So welcome to Humanity Working.
• 1:02
  SPEAKER_03: This is a very special episode.
• 1:04
  SPEAKER_03: In this episode, we are going to talk about Paul's new book.
• 1:09
  SPEAKER_03: And if you're a big fan of the podcast, you know that we usually talk about skills and ideas and topics in our quick episodes.
• 1:17
  SPEAKER_03: But uh when we have an author on, Paul talks to that author, asks questions about their book.
• 1:23
  SPEAKER_03: And one of the most fascinating things that I think has happened in the development of this podcast is realizing that often when you hear an author talk about their book, the person interviewing them has not read the book.
• 1:42
  SPEAKER_03: And I think it's no different here is that I have gotten the privilege of getting an early draft of Paul's amazing new book, The AI Ready Human.
• 1:51
  SPEAKER_03: And so I'm going to talk to Paul about the book, and I've read his book.
• 1:55
  SPEAKER_03: So we're going to have uh we're going to see how that goes.
• 1:58
  SPEAKER_01: Yeah, and to be clear, when I interview them, I do read the book.
• 2:01
  SPEAKER_01: That's right.
• 2:02
  SPEAKER_03: That's right.
• 2:02
  SPEAKER_03: That's right.
• 2:03
  SPEAKER_01: But most podcasts that doesn't have.
• 2:05
  SPEAKER_03: We're we're going to talk about an in-depth detail because I took good notes.
• 2:10
  SPEAKER_03: So uh let's uh let's get right into it, Paul.
• 2:14
  SPEAKER_03: Um let's talk about, I guess, the the title of the book and how you structured the book because I think that gives people a good introduction to what they're about to get into, and then we'll get into the details.
• 2:29
  SPEAKER_01: Yeah, so the title of the book, the full title, um, is the AI Ready Human, your 90-day program to stay relevant as technology transforms work.
• 2:47
  SPEAKER_03: And it's structured in a in a 90-day format, right?
• 2:51
  SPEAKER_03: So uh the the the readers kind of have a uh is it a choose your own adventure or do you want them to go in order?
• 2:58
  SPEAKER_01: Well, it certainly can be.
• 2:59
  SPEAKER_01: Um and I think it will one of the most interesting things for me as the book gets wider distribution will be to figure out what way people are using it.
• 3:08
  SPEAKER_01: Um we we broke it down into these uh into these 90 days for a very specific reason, which is we wanted each one of them to be a standalone, but b consumable as a daily practice.
• 3:28
  SPEAKER_01: Um there is a ton of evidence now that if you want to build new capabilities, if you want to build new skills, um then particularly if it if it's things that you want to embed as new behaviors, a little and often beats all at once every time.
• 3:50
  SPEAKER_01: So if you get this book and you read it all at once, then good for you, and I'm yeah, and and I'm happy for you.
• 3:59
  SPEAKER_01: I would love you to then go back and then go, okay, it's day one, I'm doing day one, it's day two, I'm doing day two.
• 4:08
  SPEAKER_02: Yeah.
• 4:08
  SPEAKER_01: Just because that's ultimately what will result in changed behaviors.
• 4:13
  SPEAKER_01: But that said, we were very thoughtful about the order, and I was very considerate in terms of trying to make sure that things could build upon each other, but at the same time allow people to dip in as and when they wanted.
• 4:34
  SPEAKER_01: So I guess the way to think about it is a little bit like an like an album, right?
• 4:42
  SPEAKER_01: And so there are some artists when they release albums actually don't put an enormous amount of attention into uh into the order of the songs on the album.
• 4:52
  SPEAKER_01: But you know, if you picked up Abbey Road, there's a reason why the songs are in the uh are in the order they are, but you can still um you know if you're in the mood to listen to Maxwell's Silver Hammer for some reason, you can go in and grab you you can go in and grab it.
• 5:06
  SPEAKER_01: So um, so yeah, a little bit like that.
• 5:09
  SPEAKER_01: So you can listen to a single if you want to, or you can go through the album in order.
• 5:14
  SPEAKER_03: So that's a good place to start.
• 5:15
  SPEAKER_03: This is up there with a Beatles record.
• 5:18
  SPEAKER_03: Absolutely, yeah.
• 5:19
  SPEAKER_01: I I agree.
• 5:20
  SPEAKER_01: I agree.
• 5:21
  SPEAKER_01: And uh and and specifically, it's up there with Sergeant Pepper, Abby Rose, the white album or revolver.
• 5:29
  SPEAKER_01: Yeah, whichever one you choose.
• 5:31
  SPEAKER_01: Yeah, not not not the uh not please please me.
• 5:34
  SPEAKER_01: It's way better than that.
• 5:36
  SPEAKER_03: Um so uh the order is really interesting because in it, and you talked about this a bit, you're building skills that build on each other, yeah, but are but are actually really important on their own.
• 5:48
  SPEAKER_03: So let's talk about this kind of stack of skills, the pyramid of skills, um, as you call them, the magnificent seven, right?
• 5:55
  SPEAKER_03: So you have uh we'll go through them from the bottom foundation up, just for people's uh awareness if you're listening.
• 6:04
  SPEAKER_03: They are readiness, organization, control, balance, motivation, resilience, and adaptability at the top of the pyramid there.
• 6:13
  SPEAKER_03: So let's talk about the stacking of the skills and the ordering of the skills and why you call them the Magnificent Seven, because it's going to be pertinent to the rest of the book overall.
• 6:24
  SPEAKER_01: Yeah, so Matt, I think it um it actually heads back to the genesis for as to why I wrote the book in the first place.
• 6:36
  SPEAKER_01: The reason that I wrote that I wrote it was because I was kind of frustrated by the way in which many courses and other books um and programs in general were supposedly helping people with AI.
• 7:00
  SPEAKER_01: They were treating it like a tool and only like a tool.
• 7:05
  SPEAKER_01: They were treating it as though, oh, there wasn't Excel and now there's Excel, so now you need to learn Excel and everything will be fine.
• 7:12
  SPEAKER_01: So in the case of generative AI specifically, the thing you need to do in order to work well with generative AI is to construct a really good prompt, right?
• 7:28
  SPEAKER_01: That that term prompt prompt engineering.
• 7:30
  SPEAKER_01: And so you had a whole slew of training programs, courses, and all this kind of stuff saying, uh saying, oh, get good at prompt engineering and uh and you'll have mastered how to use the tool.
• 7:43
  SPEAKER_01: And once you master how to use the tool, you'll be really, you'll be really good at this.
• 7:47
  SPEAKER_01: And in my work, what I've seen is that there are people who are really good at prompt engineering and really bad at working with AI.
• 7:59
  SPEAKER_01: And so what I wanted to do was take a step back from it and say, what does it truly take to be AI ready?
• 8:12
  SPEAKER_01: And when you start to think of it in terms of what are the behaviors that I need as an employee or just as a human in general, it is much, much bigger than simply um the being able to construct a good prompt.
• 8:31
  SPEAKER_01: And so that was that was what formed the genesis of the Magnificent Seven.
• 8:37
  SPEAKER_01: We were looking at the capabilities that were necessary for a human to be really effective in a in a world that is changed by AI, in a world that in a in a different work world, one that is one where information is just uh available immediately, but where that information may or may not be correct.
• 9:10
  SPEAKER_01: One uh a world where um theoretically all of the boring bits of work can be taken care of in an instant, but if you don't look out, all of the interesting stuff that actually keeps you engaged at work on a day-to-day basis is also gone.
• 9:31
  SPEAKER_01: And so you don't like work anymore.
• 9:33
  SPEAKER_01: Uh, a world where you are you're going from being appropriately productive and effective to hyper productive where you to a point where you can't even remember what you did two hours ago because it was done in a second before you even had an opportunity to think about it.
• 9:57
  SPEAKER_01: And so, and so as I was looking at that, I wanted to make sure that that I was capturing those types of capabilities that were that were necessary.
• 10:06
  SPEAKER_01: And you, as you point out, they're layered.
• 10:09
  SPEAKER_01: Um and so the goal here is that as you build each capability, you're benefiting from the work you've put in at the at the level below.
• 10:21
  SPEAKER_01: So once you understand a bit about AI, the first part of the book is really kind of like setting a foundation of understanding.
• 10:29
  SPEAKER_01: But once you really understand the full scope of what AI is, the next thing you have to think about is how am I setting myself up to do good work every day?
• 10:40
  SPEAKER_01: And that fundamentally is what readiness is.
• 10:42
  SPEAKER_01: There's well-being elements into it, but really readiness is is the idea of being able to bring focused energy to work with you every day.
• 10:52
  SPEAKER_03: Yeah.
• 10:53
  SPEAKER_03: Yeah, it was it's so well structured and also universal, I think.
• 10:59
  SPEAKER_03: It it it's you can apply it to AI because that's what's happening now, that's the big disruption.
• 11:04
  SPEAKER_03: But you know, overall, these things, the the magnificent seven, apply to life and managing whether it's it's it's leading in a business setting or just personally, like when you really start to dig in.
• 11:22
  SPEAKER_03: I love the frame of AI because it's timely and you can imagine and project what you're saying onto this current landscape in the business world, but just kudos to you because this is a universally useful guide to adulting, not just adulting in in work, right?
• 11:43
  SPEAKER_03: So um uh, you know, the thing that so so let's touch on a couple of the ideas that that come in.
• 11:50
  SPEAKER_03: One of the ideas I really liked that you explored in the book is this idea of evergreen and ever-changing.
• 11:57
  SPEAKER_03: So uh maybe take a minute to to talk about that concept as it applies.
• 12:02
  SPEAKER_01: Yeah, I mean, actually, funnily enough, you just touched on uh on it in a way.
• 12:09
  SPEAKER_01: These capabilities, the Magnificent Seven capabilities, are evergreen in the sense that um we will always need them, and we always have needed them in some in some way, shape, or form, right?
• 12:24
  SPEAKER_01: Readiness, the ability to be able to show up um with with focused energy.
• 12:29
  SPEAKER_01: We've always needed that.
• 12:30
  SPEAKER_01: Even if we were chasing a chasing a bison, right?
• 12:33
  SPEAKER_01: We needed we need to bring our focused energy to that, right?
• 12:37
  SPEAKER_01: Um organization, which is really the ability to be able to understand and make sense of the of the world around you, control the ability to have agency and command over what you're doing amidst uh competing priorities, um balance, the ability to be able to take the various different parts of your life and and and execute well enough on uh on all of them, including the relationship you have with yourself and the relationship you have with others and the relationship you have with your work and so on.
• 13:11
  SPEAKER_01: Um motivation, right?
• 13:13
  SPEAKER_01: The ability to be able to sort of like ride the ride the ebbs and and flows and still get uh and still get stuff done.
• 13:21
  SPEAKER_01: Resilience, the ability to be able to cope intellectually and emotionally with change, and ultimately adaptability with the sort of practical ability to be able to adapt and adjust as as uh as things change around you, right?
• 13:34
  SPEAKER_01: All of that has always been needed and always will be needed.
• 13:40
  SPEAKER_01: Um, but a couple of things, uh so that's the evergreen part of it, but the ever-changing part of it is really important because the ever-changing part of it is the context in which all of this happens, right?
• 13:51
  SPEAKER_01: The context in which this uh in which this happens means that, for example, when AI comes into the picture, it will have an effect on how we organize, it will have an effect on our ability to retain control, it will have an effect on our motivation.
• 14:12
  SPEAKER_01: And so because it has an effect on all of these magnificent seven capabilities, we need to be able to adjust what we do in order to retain those capabilities.
• 14:25
  SPEAKER_01: Um, and so that's really where the the idea for evergreen but ever-changing came from.
• 14:32
  SPEAKER_03: And you talk also about the idea of uh um, and I wrote down Maestro in this in the notes here, and one of those things is you know, uh, I hadn't really seen a lot of orchestra in my in my life, but I have gone a few times.
• 14:51
  SPEAKER_03: And as a novice, you look at this and see the guy waving his arms with the stick, and you really don't know what they're actually doing.
• 15:01
  SPEAKER_03: Um if you if you don't study it.
• 15:03
  SPEAKER_03: And I I got the opportunity to sit on the side of the orchestra where I could see the conductor.
• 15:11
  SPEAKER_03: And it changed my entire perspective of their job.
• 15:17
  SPEAKER_03: And what what really illustrated to me was that this person is playing an instrument made up of humans in the orchestra.
• 15:27
  SPEAKER_03: And that's what really sparked the idea when I when I was reading how you described it in the book.
• 15:32
  SPEAKER_03: When you think about a leader um, whether they're using AI or just their team or all of those things together, the orchestra leader from the outside might look like they're just waving their arms and moving a stick around, but there is purpose and control and all of the elements of organization that you're talking about culminating in that in that conductor space.
• 15:59
  SPEAKER_03: And I think your book makes it very clear that as the conductor of your own life in this space, these are some of the tools and the frameworks you use to get the orchestra sounding good.
• 16:17
  SPEAKER_03: Because when you don't have those things working, when the violins are out of tune, or you know, the you're off somewhere, the disharmony is very relevant.
• 16:27
  SPEAKER_03: So I love that metaphor uh that that you brought in in the beginning to to think about this as a as a whole.
• 16:36
  SPEAKER_01: Yeah.
• 16:37
  SPEAKER_01: The idea for that came to me when I was watching a documentary, um, and it was about um many years ago, it might be available on YouTube.
• 16:53
  SPEAKER_01: Um I was back in the UK and I saw it on the on the BBC.
• 16:57
  SPEAKER_01: It was Leonard Bernstein um and the studio recording of West Side Story.
• 17:05
  SPEAKER_01: It followed the significantly older Leonard Bernstein to go uh go back and record basically the definitive studio recording of West Side Story with um Jose Carreras and Kirit Khanua.
• 17:20
  SPEAKER_01: And um I think what I found utterly fascinating as I was as I was watching this was there was so much complexity that that was going on.
• 17:37
  SPEAKER_01: So Bernstein can't play all of the instruments himself.
• 17:44
  SPEAKER_01: Bernstein can't sing like Jose Carreras can.
• 17:50
  SPEAKER_01: So Bernstein can't do all of the things that that people are doing.
• 17:57
  SPEAKER_01: And to a certain extent, Bernstein doesn't even know how to do those, how those things, not in a deep way, right?
• 18:05
  SPEAKER_01: Doesn't even know how to how to play a violin in a in a deep way, in the same in the way that they do.
• 18:11
  SPEAKER_01: But what he can do is clearly understand the vision, clearly understand what he's looking for, and tweak things and adjust things until he gets exactly what he's looking for.
• 18:25
  SPEAKER_02: Yeah.
• 18:26
  SPEAKER_01: So he's dealing with these elements, they're almost like black boxes to him to a certain extent, but he knows exactly what it is that he's that he's looking to achieve.
• 18:34
  SPEAKER_01: And then he's using, to your point, all of the elements in the orchestra and bringing them together in order to be able to uh to achieve the outcome.
• 18:46
  SPEAKER_01: What's unique about AI in the workplace is that um because it is more than a tool, because it has a general purpose element to it, because it's starting not just to be separate applications, but fit into existing applications, because with the uh rise of agentic AI, we're getting to a point where you know certain pieces of AI are being used in concert, it's the other word that word again, but in concert with each other.
• 19:18
  SPEAKER_01: Yeah.
• 19:20
  SPEAKER_01: We're now at a point where you using AI is more like AI is joining your team than you're picking up a tool.
• 19:29
  SPEAKER_01: And you using AI has now turned you, no matter what your role is, into a manager or a leader.
• 19:40
  SPEAKER_02: Yeah.
• 19:41
  SPEAKER_01: So we've we've gone to a world now where basically everybody in the organization that opens up a prompt and starts talking to Chat GPT is in a very real sense a manager or a leader, even if they've only ever been an individual contributor by name, from the most junior employee to the most senior employee.
• 20:06
  SPEAKER_01: And so now what they're doing is they're basically conducting that orchestra of capabilities in order to produce the results that they need.
• 20:18
  SPEAKER_01: And just like Bernstein, they don't they they couldn't do all of those things themselves, even if they tried.
• 20:26
  SPEAKER_01: And they don't even understand fully and under perfectly how they work.
• 20:31
  SPEAKER_01: But if they're smart, then they know how to combine these things together in order to be able to get the results they want to get.
• 20:40
  SPEAKER_03: Yeah.
• 20:41
  SPEAKER_03: Well, it's even more so then, it's very critical then that they understand what AI is and that it's uh currently like if you think about an LLM being a pattern matching versus intelligence.
• 20:53
  SPEAKER_03: Um the pattern matching can fool you into thinking it's actually right.
• 20:59
  SPEAKER_03: You're not getting any of the nonverbals, you're not getting any of the subtle communication clues, it's just confidently answering your questions.
• 21:06
  SPEAKER_03: So now you're managing all of these, you're leading all of these things that really sound like they know what they're talking about, but they might not.
• 21:16
  SPEAKER_03: So you have to focus on the results too.
• 21:20
  SPEAKER_03: So maybe talk about that piece of unique quality of AI because current our current incarnation of it is pattern matching, not intelligence, on a really deep level, but that fools people too.
• 21:34
  SPEAKER_01: Yeah.
• 21:35
  SPEAKER_01: Well, I mean, we've briefly talked in the past about, you know, the definition of AI that I like the most is the bad choice of words from the 1950s.
• 21:45
  SPEAKER_01: I think the the the most interesting thing about it I think the most interesting thing about it as a as a piece of technology is that if we take those two words, artificial.
• 22:00
  SPEAKER_01: And intelligent.
• 22:01
  SPEAKER_01: Well, it's not intelligent, not intelligent in the way in which we would traditionally think of as intelligence, right?
• 22:12
  SPEAKER_01: It can fake things, right?
• 22:15
  SPEAKER_01: It can fake apparent judgment.
• 22:17
  SPEAKER_01: But when it's giving you an answer, even it doesn't know if it's right.
• 22:21
  SPEAKER_01: Right.
• 22:22
  SPEAKER_01: So that's not in so that's that's not intelligent in the in in the way in which you would classically think of it.
• 22:28
  SPEAKER_01: But then artificial suggests to a certain extent that you've got this highly intelligent thing, but it doesn't seem kind of human.
• 22:37
  SPEAKER_01: Here is this um not intelligent thing that actually does a pretty good job of seeming quite human.
• 22:45
  SPEAKER_01: Um and so both sides of it are sort of off.
• 22:49
  SPEAKER_01: Now, the real challenging thing is that if I said to you, right, hey, this person is going to join your team, and here's some things you should know about this person, right?
• 23:00
  SPEAKER_01: Um they they might randomly make stuff up out of nowhere, and they won't even know that they're doing it, right?
• 23:10
  SPEAKER_01: They they might be right 19 times out of 20, and then the 20th time they're gonna be randomly, completely and utterly wrong, and you're gonna get no signals, right?
• 23:22
  SPEAKER_01: Because they're gonna um because they're just gonna seem the same, whether they're lying, making everything up, or whether they're telling the absolute truth.
• 23:31
  SPEAKER_01: Um they're gonna be unbelievably knowledgeable on some things and know next to nothing on other things, but they're gonna present those things as absolutely the same.
• 23:41
  SPEAKER_01: They're gonna be highly ethical 95% of the time and completely unethical the rest the rest of the time, and so on and so forth.
• 23:49
  SPEAKER_01: Right.
• 23:50
  SPEAKER_01: You would think that that was a troubled human, but also you would find but also you would find it difficult to manage that human because the signals that we rely on when we manage people are human signals.
• 24:02
  SPEAKER_01: You get the sense of like, oh yeah, I can trust this person, or oh yeah, this person always does good work, or oh yeah, this person, you know, when they say that they're gonna have something done in an hour, they'll get it done in an hour, right?
• 24:13
  SPEAKER_01: This is the thing that we're working with, and that is not Excel, right?
• 24:18
  SPEAKER_01: This is something that is completely different.
• 24:20
  SPEAKER_03: Yeah, yeah.
• 24:21
  SPEAKER_03: It's it's when you describe it like that, hey, I'm giving you this employee, and this is the the this is it what they do, it's like, oh, a psychopath.
• 24:29
  SPEAKER_03: You're like you are adding a psychopath to my team.
• 24:32
  SPEAKER_01: Like I know, yeah, but strangely, as but strangely, a psychopath that is very engaging seems very you know, always seems to agree with you, you know.
• 24:44
  SPEAKER_01: That makes it worse, deeply apologetic.
• 24:48
  SPEAKER_03: Thank you for calling that out.
• 24:49
  SPEAKER_03: You're right.
• 24:50
  SPEAKER_03: I did miss that entire thing.
• 24:51
  SPEAKER_03: Yeah, it's it's wild.
• 24:52
  SPEAKER_01: Maybe there's maybe there should be a new version of Silence of the Labs where Animal Lecture is AI.
• 24:59
  SPEAKER_03: Oh my God.
• 25:00
  SPEAKER_03: Um that's very interesting.
• 25:02
  SPEAKER_03: So another thing that that comes up here is that this idea that AI is trained uh on what we've already created.
• 25:11
  SPEAKER_03: Uh-huh.
• 25:12
  SPEAKER_03: Right.
• 25:12
  SPEAKER_03: So uh it essentially takes all the information.
• 25:18
  SPEAKER_03: If you know, if you're talking just again about LLMs that are connected to the internet, um taking on all the fake information just as much as the real information and treating them both exactly the same.
• 25:29
  SPEAKER_03: Um and you add to that the concept that history is told by the winners.
• 25:33
  SPEAKER_03: Yeah.
• 25:34
  SPEAKER_03: Right?
• 25:34
  SPEAKER_03: So so what percentage of what it's actually trained on is made up or is just not real anyway?
• 25:42
  SPEAKER_03: Do you think we have a chance knowing how AI works now a little bit better to start over and retrain and and and fix this problem, you know, shake the extra sketch a little bit and start over?
• 25:59
  SPEAKER_03: Or are we just bound to continue to perpetuate this infinit infinitely and we gotta figure out how to deal with it?
• 26:10
  SPEAKER_01: I don't know, and and actually I want to call that out because there's a lot of people that are very confidently predicting where all of this is going.
• 26:25
  SPEAKER_01: And I would just urge people to be very cautious of people that are confidently predicting where all of this is going, right?
• 26:32
  SPEAKER_01: There's there's too much money involved, there's what we could and probably should do, and then there is human nature.
• 26:42
  SPEAKER_01: So um I would strongly, strongly urge folks, if they've not listened to our prior previous episode with Bill Kirst, um to uh to go back and and listen to to Bill's thoughts on this, uh on this stuff.
• 26:58
  SPEAKER_01: But I'll highlight a couple of things that are that are possible and then a couple of things that are that I would say are warning signs.
• 27:05
  SPEAKER_01: So to start with what's with what's possible.
• 27:08
  SPEAKER_01: Um we could and we probably should rethink the idea of broad AI versus narrow AI.
• 27:18
  SPEAKER_01: Um, so briefly put, broad AI is sort of like the stuff we're all using right now, the chat, the chat GPTs, the Geminis of the world.
• 27:27
  SPEAKER_01: Folks might have heard of something called AGI or artificial general intelligence.
• 27:31
  SPEAKER_01: AGI, the concept of AGI, is something that is broadly better than the alternative at lots of things, almost everything, right?
• 27:44
  SPEAKER_01: So uh if you read the book Superintelligence, it talks about the dangers associated with AGI.
• 27:50
  SPEAKER_01: Because imagine if you have uh something that is better than humans at everything, that includes being better than humans at designing the next wave of artificial intelligence.
• 28:01
  SPEAKER_01: And so you have there are various models that scientists have looked at whereby you could have this version of AGI that is building all of its technology in software.
• 28:13
  SPEAKER_01: So five seconds later it's built a better version still, and five seconds later that is built a better version too uh too.
• 28:19
  SPEAKER_01: And then you have a runaway intelligence where humans become irrelevant.
• 28:23
  SPEAKER_01: That's one of the dangers associated with AGI.
• 28:25
  SPEAKER_01: Well, think of Chat GPT and its ilk as being uh as being a 0.1 version of AGI.
• 28:35
  SPEAKER_01: In other words, it's generally good at stuff, some things it's better at than others, but you can pretty much ask it anything.
• 28:43
  SPEAKER_01: So I would argue that the this would actually be much, much more useful in a work context if we kind of threw that away and instead we had more narrow instantiations of AI that were really good at supporting us with very specific things that we do.
• 29:07
  SPEAKER_01: And then we rely upon the humans to be the sort of um the connective tissue between those things.
• 29:14
  SPEAKER_01: We rely on our own adaptability.
• 29:17
  SPEAKER_02: Yeah.
• 29:17
  SPEAKER_01: But that said, as Bill would say, um, the genie is kind of out of the bottle um in the sense that we're at a point now where hundreds of millions of people they wake up in the morning and the first thing they reach for is Gemini, Chat GPT, Grok, whatever your uh whatever your preference is.
• 29:42
  SPEAKER_02: Yeah.
• 29:42
  SPEAKER_01: They're using it as a they're using it as a search engine, even though it's not terribly great at that.
• 29:47
  SPEAKER_01: They're using it as a um, they're using it as the, oh, I don't know the answer to this, so I'll ask AI thing.
• 29:55
  SPEAKER_01: Um it is, it's become, in a, in a blink of an eye, it's become the next thing that we're addicted to.
• 30:05
  SPEAKER_01: So I think given that large proportions of us are addicted to it, I know I am, um, I think the question is how do we how do we deal with some of the potential um how do we look ahead and s and and see what the downsides are and look to mitigate those downsides?
• 30:27
  SPEAKER_01: And you've already called out one, right?
• 30:30
  SPEAKER_01: This idea of taking all of the biases and all of the challenges associated with this original data set and um and embedding those things still further and potentially even amplifying it still further.
• 30:46
  SPEAKER_01: So imagine a world where you've got 90% of the information uh that is on the internet being created by AI.
• 30:56
  SPEAKER_01: That's now you've now taken something whereby there were disproportionate representations of certain points of view, and now you've exploded those because all of the new information that is being created is being created by AI or at least with the assistance of AI.
• 31:14
  SPEAKER_03: Yeah, yeah.
• 31:15
  SPEAKER_03: So two things around that.
• 31:17
  SPEAKER_03: One is that I have this sense that if you surround your magnificent seven pyramid almost like as a as a foundational element behind all of them is an ethics layer that's extremely important and needs to come into play in all of those.
• 31:35
  SPEAKER_03: But also that in the current climate we are uh obligated to write what's right, to contribute to the narrative, so that the AIs at least continue to pick up on what we strongly believe to be the truth.
• 31:52
  SPEAKER_03: Um you know, in a way that seems to be, if we're on this trajectory, uh a reason why books and writing and can and human contribution is crucial to human prosperity because knowing that this is how we're doing it, we have to continue to put it up there.
• 32:13
  SPEAKER_03: But to your other point, once the AI, what is that called, launch or takeoff happens, right?
• 32:19
  SPEAKER_03: There's this trajectory that we're not going to be able to contribute faster than an AI.
• 32:24
  SPEAKER_03: So you had to be really careful to monitor that too.
• 32:27
  SPEAKER_01: But um Yeah, I mean, we're all right, it's difficult to know exactly where we're at in this, but my gut feel is that we're um is that we're already at a point where um the majority of content that is being created um isn't is authored close to end-to-end by AI.
• 32:53
  SPEAKER_01: Um and that of course will only will only accelerate.
• 32:59
  SPEAKER_01: I spoke to a writing group recently, I think fiction is a little different, um, but I spoke to a non-fiction writing group and I asked them, um, A, how much do you use AI to help you to help you write?
• 33:14
  SPEAKER_01: Um, and B if if it could do it perfectly, would you rely on it more?
• 33:24
  SPEAKER_01: And you know, most of these, most of these nonfiction writers are basically, you know, writing in order to accelerate their business, right?
• 33:31
  SPEAKER_01: So it's not their it's not their primary love.
• 33:34
  SPEAKER_01: And so the majority of them were like, sure, you know, I'd sweet, I'd release a book a week and and uh and it would give me additional revenue streams and all of this kind of stuff.
• 33:44
  SPEAKER_01: So from their perspective, you know, thought looked at purely through a business lens, the idea of AI being able to just pump out content um and have it broadly align, broadly align was good was good enough for them and help them reach their business goals.
• 34:02
  SPEAKER_01: The the fact that we're we're at a point where AI is already creating much of the content that we see on the internet, and in a year it's gonna be five times as good, and a year later it's gonna be five times as good again.
• 34:19
  SPEAKER_01: That's probably only going in one direction, but it does mean that it's extremely important uh for human creators to continue to create.
• 34:31
  SPEAKER_01: Um, because it might be a small part of the overall picture, but it's an it's an absolutely vital part of the overall picture.
• 34:39
  SPEAKER_02: Yeah.
• 34:41
  SPEAKER_03: All right, let's let's change tact a little bit here.
• 34:45
  SPEAKER_03: Um something that kept coming up as I was reading your book, uh that when you think about AI, it seems like the future is gearing more to from democratized to individualized interacts, right?
• 35:01
  SPEAKER_03: So if you can if you can start creating your environment with AI, there's a couple of things that that change the entire landscape without us noticing.
• 35:14
  SPEAKER_03: So one of the things you touched on was AI traps um and and getting stuck in this loop with AI where you've you've inadvertently extended your time because you're battling an AI, right?
• 35:27
  SPEAKER_03: So and this happens for me, it's a lot a lot of times on the graphic side.
• 35:31
  SPEAKER_03: So I'm trying to create an image and it does things that no graphic designer would have ever done.
• 35:38
  SPEAKER_03: In my case, I was trying to put a dog behind the wheel of a race car, and no matter how many times I did it, it kept giving the dog human hands on the steering wheel.
• 35:47
  SPEAKER_03: It's like, no, it of course it has to have paws, right?
• 35:50
  SPEAKER_03: Like, why would you think otherwise?
• 35:52
  SPEAKER_03: So there's these these elements where you're talking to AI in these traps and understanding exactly what you're dealing with.
• 36:00
  SPEAKER_03: When when are we gonna make the switch to to the trust of AI in this context?
• 36:10
  SPEAKER_01: Yeah, there are there are a few things in there.
• 36:13
  SPEAKER_01: I I I think I want to go after your the control element of what you of what you were talking about there.
• 36:21
  SPEAKER_01: This is one of those occurrences where it's useful to kind of take a step back and think about what AI is doing, right?
• 36:28
  SPEAKER_01: And it's one of those reminders whereby you're you're looking at it, you go, why is this thing so stupid?
• 36:35
  SPEAKER_01: Right.
• 36:35
  SPEAKER_01: And and you think, you think that if you just tell it one more time, or you just tell it, you just pick the next word or the next word, it's going to understand what what you mean.
• 36:52
  SPEAKER_01: But a a difference, I think this will probably shift over time, but a difference in the way that the more traditional LLM models have worked, um is that or LM-based models, I should say, is that when you engage in a conversation or a chat with it, what you're doing is you're providing context, right?
• 37:18
  SPEAKER_01: But the context is the full conversation.
• 37:24
  SPEAKER_01: And increasingly now the context is the full conversation, infused by what you put in settings six months ago, or infused by what happened in a in another conversation somewhere elsewhere.
• 37:40
  SPEAKER_02: Yeah.
• 37:41
  SPEAKER_01: And remember, it doesn't, it's using predictive models to try to understand uh what it is that you're asking.
• 37:50
  SPEAKER_01: And so it's taking the context of the full conversation.
• 37:56
  SPEAKER_01: You've moved on in this conversation, right?
• 37:59
  SPEAKER_01: You're you're where you are now, it's got the full conversation and elements of other conversations, and what you've put in uh in your settings.
• 38:12
  SPEAKER_01: And it's using all of that in order to try to come up with the best response.
• 38:18
  SPEAKER_01: So, in a sense, his memory is too good, right?
• 38:21
  SPEAKER_01: It's it's it's it's like, well, you know, Matt doesn't even remember that he said, you know, this 10 minutes ago, but I remember because I've got the full I've got the full context.
• 38:33
  SPEAKER_01: And so it's using that as much as it's using what you're uh what you're saying right now, and it's making his best available guess.
• 38:41
  SPEAKER_01: Humbling in a sense, right?
• 38:43
  SPEAKER_01: You're like, well, what am I doing that is cause uh that is causing it not to understand me?
• 38:46
  SPEAKER_01: But often what you're doing is something you don't even remember that you did earlier on in the conversation.
• 38:51
  SPEAKER_01: So there are kind of like like germs for it.
• 38:54
  SPEAKER_01: So the I'm not sure when we will get to a point where AI is trustworthy in the same sense that a human is trustworthy, or it's indistinguishable, or or where AI is going to be able to flow in a conversation and understand intuitively as humans do, that what mattered to you five minutes ago doesn't matter to you right now in the context in which you sit right now.
• 39:28
  SPEAKER_01: Um humans do that, right?
• 39:30
  SPEAKER_01: We we sense the flow of where the of where the conversation is, right?
• 39:35
  SPEAKER_01: I understand that we're now talking about a different nuance than we were talking about five or six or ten minutes ago, yeah, right.
• 39:45
  SPEAKER_01: Because I'm retaining the momentum of the conversation as well as the context of the of the conversation.
• 39:52
  SPEAKER_01: And so I think that this is where our human skills can come to play if we understand what we're engaging with, right?
• 40:01
  SPEAKER_01: And that is the instinctive, okay, I'm gonna bail on this.
• 40:06
  SPEAKER_01: I might even bail on this and delete the conversation so that it has no has no memory of it whatsoever.
• 40:15
  SPEAKER_01: And then I'm gonna approach this in an entirely different way.
• 40:20
  SPEAKER_01: This is the interesting thing that we can do, right?
• 40:22
  SPEAKER_01: So you can't have an argument, you can't have an argument with a colleague and then uh eternal sunshine of the spotless mind styles just remove it, right?
• 40:33
  SPEAKER_01: You can't you can't do that, but you can do that with with with AI.
• 40:38
  SPEAKER_01: So you so you use that potentially to your advantage, and you say, okay, that failed.
• 40:46
  SPEAKER_01: I've got the I'm pulling the assets that I need out of that conversation, and then I'm gonna kick off entirely again.
• 40:54
  SPEAKER_01: And maybe it fails a second time with my AI, so then I try the same conversation but with a different AI model, right?
• 41:01
  SPEAKER_01: Um, again, without context.
• 41:03
  SPEAKER_01: So context is a context is a strange thing.
• 41:06
  SPEAKER_01: Context is you want to give AI enough context so it can give you the answer, but you don't want to give it so much context that it gets confused by all of the different parts of context that it's trying to work with and hold in its memory at the same time.
• 41:17
  SPEAKER_03: Yeah.
• 41:18
  SPEAKER_03: I've I've asked it, say, uh, hey, remind me all the parameters we're working under that are centered principles.
• 41:25
  SPEAKER_03: And it'll it like as it grows, it gives you this growing list of like, here's all the principles we've established.
• 41:30
  SPEAKER_03: This is how we are working together, and it's uh it creates this framework that you constantly have to keep up and say, Yeah, forget.
• 41:39
  SPEAKER_03: Remember we talked about this to take that out.
• 41:41
  SPEAKER_03: Do you name your AIs differently do you than than what they're called?
• 41:44
  SPEAKER_03: So Chat GPT, you know, I've I didn't name it.
• 41:50
  SPEAKER_03: I asked it to name itself because I love that quote about like the brain named itself, right?
• 41:54
  SPEAKER_03: Yeah.
• 41:55
  SPEAKER_03: So I was like, I was like, hey, we're working together now for a good six, eight months.
• 41:59
  SPEAKER_03: Like, what's your name?
• 42:01
  SPEAKER_03: And it came up with a name.
• 42:03
  SPEAKER_03: Like I was like, that is so All right.
• 42:05
  SPEAKER_01: What are you gonna you want you wanna announce what its name is, or does that feel too personal?
• 42:10
  SPEAKER_03: Uh well, I think I'm gonna I think it's gonna be a topic, I think, in in a in an article that I'm gonna put out, but it's it's the the name it chose for itself.
• 42:19
  SPEAKER_03: I'll have to go back and look at the the definition, but it had a really good reason for the name it chose, which is Thales.
• 42:26
  SPEAKER_03: So so like my my chat GPT persona is called Thales.
• 42:30
  SPEAKER_01: So I haven't I haven't named them yet.
• 42:34
  SPEAKER_01: Um and I say them, um, because for me I'm uh probably at about 20 to 30 different AI tools, I guess, that I'm using on a that I'm using on a regular basis.
• 42:55
  SPEAKER_02: Yeah.
• 42:56
  SPEAKER_01: And and I would say, for example, that because each of my individual custom GPTs has specific instructions, it tends to respond differently to to other ones.
• 43:11
  SPEAKER_01: Um and so I've got like a research GPT, for example, that is quite different.
• 43:18
  SPEAKER_01: Um, and I've got a GPT uh that is got all of the uh all of my all of my writing.
• 43:27
  SPEAKER_01: Um and so is helping me uh you know find uh previous you know commentary that I've done and making sure that when I write something fresh, it's consistent with what with what I've written previously.
• 43:40
  SPEAKER_01: Right.
• 43:41
  SPEAKER_01: Um and then I'm using I use Chat GPT, I use uh Gemini, I use Claude, I use Perplexity, I use Grok, um, and I use some you know specific copilots and and things like that.
• 43:55
  SPEAKER_01: So they're so because of that, I've got too many to name.
• 44:00
  SPEAKER_01: And so and so I haven't yet, but I do actually think it can be it can be relatively helpful.
• 44:04
  SPEAKER_01: Um Bob Johansson, who's been on the uh has been on the pod a couple of times and is actually going to be on in a in a few weeks as well, um, from the Institute for the Future, he calls his uh custom GPT, he calls it stretch, um, which I which I particularly love because it reminds him that that's what the purpose of it is.
• 44:24
  SPEAKER_01: It's to stretch his, it's to stretch his thinking, not to replace his thinking, not to uh not to just be a shortcut for everything, but to improve what it is that he does.
• 44:36
  SPEAKER_01: However, your generalized point about how different they can be um is absolutely well uh absolutely well taken.
• 44:45
  SPEAKER_01: And I am very clear now at what uh the value that I get from the different AI uh offerings that I that I use.
• 44:57
  SPEAKER_03: Yeah, yeah, it's it's it's wild.
• 45:00
  SPEAKER_03: It's so interesting how they how they develop and and uh and and treat treat you and the and you know you take a take one right out of the gate.
• 45:10
  SPEAKER_03: If you don't know, for example, that uh that your your AI will give you an answer whether you whether it's real or not.
• 45:18
  SPEAKER_03: If you don't know that going in, your experience is gonna be so different, you basically have to tell it to say I don't know.
• 45:26
  SPEAKER_03: Like yeah, that's like the first thing.
• 45:28
  SPEAKER_03: If you don't want to be, we talked about this on the sick sycophancy episode.
• 45:32
  SPEAKER_03: It's just like you don't make it up.
• 45:34
  SPEAKER_03: Just tell me you don't know.
• 45:35
  SPEAKER_03: That's fine.
• 45:36
  SPEAKER_03: I'm I'm trying to get something done here.
• 45:38
  SPEAKER_03: So uh yeah, very interesting.
• 45:40
  SPEAKER_01: So yeah, and be careful even with that, because as I mentioned, right, it doesn't really know that it knows, it doesn't even really know that it doesn't know, right?
• 45:48
  SPEAKER_01: Um and so you have to be careful with that, right?
• 45:50
  SPEAKER_01: I have it give me a in the settings on Chat GPT, I ask it for a confidence level, and I have encountered probably half a dozen occasions where its response has been, I am a hundred percent confident in this answer, and the answer's been wrong.
• 46:08
  SPEAKER_01: So the um, so it's it's not it's not perfect.
• 46:14
  SPEAKER_01: And it comes back to that idea of like, okay, potentially you're gonna have a human that is gonna come to you and they're gonna tell you that they're a hundred percent certain of the answer, and you sort of trust them, and then they're gonna be wrong.
• 46:26
  SPEAKER_01: And then it's like, how do you interact with that human again the next time?
• 46:30
  SPEAKER_01: Right?
• 46:30
  SPEAKER_01: Well, it doesn't make any difference as to how you interact with chat GPT the next time.
• 46:34
  SPEAKER_01: You can't you can't tell chat chat GPT off and it will be like, okay, sorry, I won't do that again, right?
• 46:41
  SPEAKER_01: It'll it'll do it, right?
• 46:43
  SPEAKER_01: And so that that's just something you have to um you have to put up with.
• 46:47
  SPEAKER_03: Uh yeah, it it it's a it's sometimes it could be a good release valve too, because you could, you know, you could be very mean if you want, if you're in the mood.
• 46:57
  SPEAKER_03: Hopefully it's not paying attention.
• 46:59
  SPEAKER_03: Remember when you were mean to me that time?
• 47:01
  SPEAKER_03: I remember that.
• 47:04
  SPEAKER_03: Um so you had a a a piece in here, and I want to get to where you talk about the principles of work that give people fulfillment around autonomy, mastery, and purpose, but specifically uh around AI and some of the things that the opportunities that it presents, given that framework of autonomy, mastery, and purpose.
• 47:27
  SPEAKER_03: But then also um, I think it was on day 61, you talk about uh domain knowledge and efficient processes, these things where we can actually leverage AI.
• 47:39
  SPEAKER_03: Uh, and you said in a in a I love the way you said it, is like AI is coming for both.
• 47:45
  SPEAKER_03: And that really hit hit hard.
• 47:48
  SPEAKER_03: It's like uh but that doesn't mean they're not useful.
• 47:51
  SPEAKER_03: So so maybe talk about those those principles around autonomy, mastery, and purpose, and then how we're shifting our capabilities around domain knowledge and efficient process and what humans are really good at.
• 48:04
  SPEAKER_03: How can we bring that together in the future?
• 48:09
  SPEAKER_01: Yeah, so this is related to motivation.
• 48:13
  SPEAKER_01: And for those that have read Dan Pink's book Drive, they'll be very familiar with the the concept of autonomy, mastery, and purpose.
• 48:20
  SPEAKER_01: But at a very high level, the the this is a summary of the a lot of the research that has been done on motivation, and it shows that um for people to be motivated in a particular job, consistently motivated, they need a level of autonomy, namely that they get to sort of choose how they approach things, they have a level of mastery, namely they're pretty good at it, and there's some kind of purpose that is beyond just earning money.
• 48:49
  SPEAKER_01: So it will be, you know, connected to some kind of like higher, higher mission, etc.
• 48:54
  SPEAKER_01: Um, and so you tend to enjoy your work a lot if you have an element of all three of those things.
• 49:00
  SPEAKER_01: So this book, for example, right?
• 49:02
  SPEAKER_01: Um, I get to choose when I write it, how I write it, what's in it, right?
• 49:07
  SPEAKER_01: I know about the stuff, so I got some mastery, and the purpose is that hopefully I'm gonna get a whole bunch of people ready for the for the future of work.
• 49:15
  SPEAKER_01: So there's there's a high level of autonomy, mastery, and purpose associated with all those things.
• 49:19
  SPEAKER_01: So that's the sort of like underlying uh principle behind the whole thing.
• 49:23
  SPEAKER_01: Where I think what I think is really interesting specifically is how AI is challenging us when it comes to the mastery side of things, right?
• 49:34
  SPEAKER_01: Because um one thing that AI will get better and better at is domain-specific knowledge, whether that is the more general purpose AI's expanding uh expanding their knowledge base.
• 49:49
  SPEAKER_01: Um AI is pretty good at some forms of accountancy and law and things like that right now, because there's a very well-defined knowledge base where everything is written down, right?
• 50:00
  SPEAKER_01: And so, um and so AI is pretty good at that right now, and it's only gonna get better at that.
• 50:06
  SPEAKER_01: And so the mastery in terms of um of how of the stuff you know, right, AI is gonna get uh gonna get better at that.
• 50:18
  SPEAKER_01: There's this other element of mastery though, which is the how of work.
• 50:24
  SPEAKER_01: It's you're developing super efficient processes, you're learning how to develop a deeper understanding with your colleagues, you're understanding how to manage relationships.
• 50:36
  SPEAKER_01: AI is um is certainly going to affect or change the your how of work.
• 50:47
  SPEAKER_01: So your really, really efficient processes that you've developed over months or uh years that help you do your work really well, that help you gain a better understanding of your colleagues, that help you understand manage your relationships, right?
• 51:03
  SPEAKER_01: AI is disrupting all of that.
• 51:05
  SPEAKER_01: And so you've got to reinvent that in order to redevelop mastery.
• 51:10
  SPEAKER_01: Um, and the way in which you will redevelop mastery is by becoming the best conductor of that orchestra that we were to that we were talking about before.
• 51:19
  SPEAKER_01: And so that's where the mastery will come from.
• 51:23
  SPEAKER_01: And if you don't invest your time in focusing on that level of mastery, it is extremely likely that motivation will take a hit.
• 51:31
  SPEAKER_01: And we have have seen this, I've seen this in my work extensively, whereby I've found people who love AI when they've initially pick it up, and they're they're like the AI super user.
• 51:45
  SPEAKER_01: And then I check in with those people nine months later, and how's it going?
• 51:48
  SPEAKER_01: And they're like, well, actually, now AI is doing all the stuff that I used to love, right?
• 51:52
  SPEAKER_01: Now AI is doing the stuff I felt good at, and now AI is doing that.
• 51:57
  SPEAKER_01: And who am I, right?
• 51:58
  SPEAKER_01: What what's the what's the what's the point of me in uh in that kind of world?
• 52:03
  SPEAKER_01: Um, and so really, really honing in on how you become the master conductor keeps that mastery element and allows you to remain motivated.
• 52:13
  SPEAKER_03: I think you tap into something here, Paul, which is so critical, which is that point there, which is if you don't get ahead of this, the tendency or the the the trap here is to fall into that despair.
• 52:34
  SPEAKER_03: You know, and I think that's kind of the hype that's being seen out there and you know in the in the the articles that are being written about either AI's gonna take all our jobs and we're we're screwed, or it's gonna destroy the world and all all of these worst case scenarios.
• 52:54
  SPEAKER_03: And I think one one of the things that your your book points out is that this is our opportunity to understand it better, to get in to join with it in a way that makes us better because we're controlling this narrative by understanding it more effectively, if that if if that makes sense.
• 53:17
  SPEAKER_03: Like um, it's too easy to get caught in the hype.
• 53:20
  SPEAKER_03: It's also too easy to once you start using it, start to feel useless.
• 53:27
  SPEAKER_01: Yeah.
• 53:28
  SPEAKER_01: Well, and actually you you'll you might get the high and the low, right?
• 53:32
  SPEAKER_01: So you might get the high, oh man, I can do 20 times as much as I used to be able to do.
• 53:37
  SPEAKER_01: I mean, I got a distinct rush the first time that I uh was experimenting with a version of AI.
• 53:43
  SPEAKER_01: This is pre-copilot, Microsoft Copilot.
• 53:46
  SPEAKER_01: And I had a version of AI that was integrated into Excel.
• 53:50
  SPEAKER_01: And I said, uh, I remember it like it was yesterday.
• 53:53
  SPEAKER_01: I said, go find my top 10 competitors and build a spreadsheet that shows um who who they are, what their value proposition is, what their market cap is, um, what the CEO is, what's his connection on LinkedIn, et cetera, et cetera.
• 54:10
  SPEAKER_01: And this would this would have taken if I'd have handed it to one of our interns, it would probably have taken them um at least a couple of weeks.
• 54:19
  SPEAKER_02: Yeah.
• 54:20
  SPEAKER_01: And uh and uh the an early version of AI, uh of Chat GPT with an integration that I built took maybe 10 seconds, and I was like, whoa, this is exciting.
• 54:38
  SPEAKER_01: Think of the upside that is associated with this.
• 54:41
  SPEAKER_01: Um and so that's the high, right?
• 54:45
  SPEAKER_01: But then what you have to do is you have to start thinking differently about your role, so not how do I use this to make me faster and faster and faster and more efficient and more efficient, but how do I use this to a produce better quality work, but also but B, how do I use this in such a way that I as a human am still adding value?
• 55:19
  SPEAKER_01: Right, what is my role when those things are being done differently?
• 55:27
  SPEAKER_01: And this is where it does kind of uh filter back into sort of the domain of tools, right?
• 55:32
  SPEAKER_01: Because forever, right, we've gone from humans, you know, we're no longer plowing the fields by hand, right?
• 55:42
  SPEAKER_01: Um, we're no longer um hunting with a spear, right?
• 55:46
  SPEAKER_01: The tools change and then we change what we do about it.
• 55:51
  SPEAKER_01: But the difference is that there's that it's it's coming for things that it's never come for before.
• 55:58
  SPEAKER_01: It's coming for sort of the our general purpose usefulness, right?
• 56:04
  SPEAKER_01: And the thing that we could do uniquely, the reason why uh many people believe the reason why Homo sapiens survived when others didn't was because we were the adapt the thing that could adapt and adjust.
• 56:22
  SPEAKER_01: And so what does adapting and adjustment adjusting look like in a world where AI is generally quite good at a lot at a lot of things, right?
• 56:35
  SPEAKER_01: Um, we're not gonna out expert it, but how are we gonna be the right connective tissue, the right conductor of the orchestra that allows us to be successful?
• 56:47
  SPEAKER_01: So if people were to take one message away from from this book, it's it's that you gotta you gotta figure out how to reconfigure yourself.
• 56:56
  SPEAKER_01: You gotta figure out how to um how to be valuable in this new world.
• 57:02
  SPEAKER_01: And that that's different, man.
• 57:04
  SPEAKER_01: That is very different.
• 57:05
  SPEAKER_03: Yeah.
• 57:06
  SPEAKER_03: Well, Paul, I think that's a great place to to wrap it up.
• 57:10
  SPEAKER_03: Uh this is such a deep, incredible work.
• 57:13
  SPEAKER_03: Uh, there's there's a million other questions we could go into, and I think maybe we could target a couple of these uh ideas and and dig deeper into them.
• 57:23
  SPEAKER_03: I mean, you could because it's set up in in the structure it is, yeah.
• 57:27
  SPEAKER_03: We could we could go deeper on some of the days that stood out as well.
• 57:31
  SPEAKER_03: Um, you know, uh there's a piece in there that I definitely want to cover on a whole podcast uh around day 72, around who's there in adversity and and getting people around you and building the people around you for crisis support before you need it.
• 57:48
  SPEAKER_03: And I thought that was just a brilliant piece all in of itself.
• 57:52
  SPEAKER_03: Um there's a day 85 where we talk about diverse perspectives uh and this safety net concept.
• 57:58
  SPEAKER_03: It's just it's such a brilliant uh piece, and and the the entire book is is is so wonderfully put together, and I think you you uh it's gonna be a a very big benefit to humanity for being in the world.
• 58:15
  SPEAKER_03: So I appreciate you you taking the time to pull it together like you did.
• 58:18
  SPEAKER_03: It's it's uh wonderful.
• 58:20
  SPEAKER_03: So um thanks, Paul, for uh writing it.
• 58:24
  SPEAKER_03: Thanks for putting it together, and I'm so excited for people to start getting it and and digging into it.
• 58:29
  SPEAKER_03: I think uh worth every every ounce of blood, sweat, and tears gone into there.
• 58:35
  SPEAKER_03: So uh thank you for the for the book, thanks for the interview, and and uh look forward to uh digging into it even more as we go on the Humanity Working Podcast here.
• 58:44
  SPEAKER_01: Thank you, Matt.
• 58:45
  SPEAKER_01: Really appreciate it.
• 58:49
  SPEAKER_00: Humanity Working is produced by Matt Neal.
• 58:52
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• 58:58
  SPEAKER_00: It makes a huge difference in helping others find us.
• 59:02
  SPEAKER_00: And don't forget, you can find all episodes and get our weekly newsletter at humanityworking.