Transcript 0:00 Welcome to AI Glatson, where the future isn't just imagined, it's felt, and I'm your co-host, Peggy Smedley Dennis Dreher, your other co-host. Together, we're flipping nostalgia on its head. That's right. 0:14 AI Glatson is more than a word, it's a mindset. It's about preferring the dreams of the future to the experiences of the past. 0:22 In this show, we'll explore visionary ideas, challenge assumptions, and spotlight the people who always light the spark of something new. 0:33 These are the people who go where no one has gone before in all areas of life on Earth. From tech and transformation to recognition and legacy, this is where emotion meets innovation. So let's stop chasing normal, 0:49 and let's start designing a future worth remembering. So let's go. Too often we hear that history kind of repeats itself, and but the age of all of this data, we're repeating progress and amplifying risk. 1:06 In our discussion today, Dennis and I are gonna map out what many consider the extremes that define our digital destiny. 1:14 And with all that in mind, what's really interesting is we, it, it, it might be time to take on a Glatson lens on this cultural lag to help us benchmark all the AI hy- hype, perhaps the cycles against the historical technologies and ask all of the tough questions. 1:35 So we'll look at both the utopian and distortive narratives. Dennis, before we get to that, I think what might be important is for you to give us some examples of how you've used AI Glatson in your work. 1:49 So maybe we should start that today. Okay. All right. That sounds good. So one of the key ways that I've used AI Glatson recently, not really recently, [laughs] actually, it was a couple of years ago. 2:01 So soon after ChatGPT... Actually, it was probably ChatGPT-4. Soon after ChatGPT-4 came out, I really wanted to get a good feel for how we would be using AI 10 years from now. 2:14 And by AI, I don't mean just ChatGPT, of course, any kind of AI and any kind of automation that has a level of intelligence to it. 2:24 And I wanted to get a, wanted to get a good feel for that because, of course, the company I work with, it's an online platform, and we've, we've been integrating automation into our platform for the past 12 years now. 2:37 And in fact, in 2015, I was, I was told that my work would no longer be required because we had automated it. 2:46 And then, of course, six months later, I get a call back saying, "Hey, Dennis, why don't you come back and help us out with this, that, and the other thing?" 2:52 Automation, in my experience, in my own experience, has always been a lot more... The reality of it turns into something else in my own experience, right? 3:04 From, like I said, back in 2015, I was told we wouldn't be needed anymore. But 3:10 anyway, the, my point there is I already had a feel for what that felt like to be told, like a lot of people were being told a couple of years ago, that their jobs may not be needed anymore because we now had these amazing chatbots. 3:27 Anyway, so I had that feeling. I had a, I could carry that out a couple of years maybe. But also, like you said, history repeats, so I started looking at what kind of patterns, 3:41 not so much trends, because of course, when people think about the future, they often think about trends and trying to throw those into the future, but I'm looking more at how patterns have changed rather than necessarily trends. 3:55 And so one of the key patterns that is often applied to technology is cultural lag. Cultural lag basically is a theory from the 1920s about how [laughs] 4:11 using academic words, it's how material culture changes faster than non-material culture. So basically saying how technology changes faster than politics, 4:23 how technology changes faster, e-e-even things that are not necessarily called technology, but how maybe the art world changes faster than, than society changes in general. 4:36 So it's about how things change, but then as that theory grew and began to notice how, how 4:44 technologies are often associated or often accompanied by very utopian images of how this technology is going to change the world and make us, make the world a better place, and there'll be no more death and whatever else. 5:00 But then it's also accompanied with a lot of dystopian images, uh, very Blade Runner images that the world will be overrun with populations and it'll be raining all the time with acid rain, and it'll be a horrible environmental impact. 5:17 And so technologies come out, and they're accompanied by these very opposite, uh, images. And so when ChatGPT was released, we saw the hype come out really strong. 5:30 This was the answer to everything that AI had been searching for. And then, of course, people started going, "Okay, if this is the answer for everything that AI's been searching for, what about Skynet?" 5:43 And [laughs] so the dystopian images started coming out pretty quickly as well. And so between that... So I started wanting to feel AI Glatson, 5:54 and I started using cultural lag to think about, okay, here's the way we were thinking about the internetWhat was it? 30 years ago. Good gravy. 6:03 [laughs] 30 years ago, we were thinking about the internet and how it was going to be amazing, and yet at the same time, there were a lot of people talking about 6:12 concerns about marginalized parts of society, as well as over-reliance on digital technologies, that it was gonna be a, 6:23 it was going to be a boon for democracy and at the same time it was going to be the destruction of personal connection because we were going to be connecting via the internet rather than face-to-face. 6:36 And looking at how we responded to the internet, I was comparing that to how we're currently responding to, and still responding to the large language models like ChatGPT and Claude and Perplexity and Grok and all the other chatbots. 6:52 And really just trying to f- get a feel for, okay, h- how are we going to... how is this technology going to become normal? And how are we then going to think about it the same way we think about the internet? 7:05 We take the internet for granted. We don't really care too much anymore whether it's going to af- how it's going to affect society because we already know it does affect society. 7:16 It's more a question of how do we, how do we ensure that effect is positive? And- So if I'm hearing you, so if I'm looking- Mm-hmm... 7:24 at this right, when we look at utopian and we look at dystopian narratives, like what you're saying with the internet, we're talking about the early discourse by repeating the themes of kind of this boundless of opportunity, but yet there's this existential risk. 7:38 That's what we're talking about here. Mm. And I think about it, so are you saying that as leaders, as executives, we need to ca- draw these parallels? 7:47 That's what I'm hearing you talk about, is that there needs to be this balance of optimism with amount of caution, which everybody's saying, do we think about the future of work? What's gonna happen? 7:59 In governance frameworks, we've got ma- the, our leaders talking about we've got to start governing what's gonna happen with AI, what's gonna ha- anticipate both the opportunity for innovation with all this disruption that's happening, and that's what the internet did, right? 8:14 Mm-hmm. We all said- Mm-hmm... what's gonna happen? But now when the internet settled down, we figured out what's gonna happen, what's it... where is it going to be, how are we gonna manage it? 8:23 Now we're at that same stage with AI, but AI has a, an, another level to it right now. So I think- Yeah... that's the part we're still not understanding. 8:32 So if we're gonna draw some parallels between early i- internet narratives right now, I think, can we say, is that what we're at right now when you say with Iglltson, this whole idea, are we at this? Is it utopian level? 8:48 Are we at this other i- idea of dystopian? Maybe there are some, some different things we need to draw here, because I think leaders have to think about that. 8:59 But as I'm hearing you talk right now, are there these proof points that we need to use to distinguish temporary cultural anxieties we need to be thinking about from- Mm-hmm... 9:10 enduring maybe structural shifts in AI adoption? 9:14 Because it, the more I hear you talk, 'cause you've talked about a lot of different things, there's those media cycles, there's all this pop culture stuff, there's- Mm-hmm... 9:23 public opinion, there's all these different things happening, and it seems like it, it's just a lot going on. But there's something different than what happened with AI, the internet, than what's happening here with AI. 9:37 Yeah, by all means. In a lot of ways, I think we're still in the information superhighway. If you remember the- [laughs] Yes... when the internet came out- Yeah. Exactly... 9:44 everybody was talking the information superhighway, and it was gonna be amazing, and I think we're still in that phase a little bit with AI. Like you say- It's all a rush... it's a little bit different. It's all a rush. 9:54 We're all in that- Yeah... superhighway rush. Okay. And, and at the same time, we're also getting to a Y2K period with- Big crash. The Y2K crash. For those who not, might not know- Right... what Y2K was. 10:09 [laughs] Worried that it, we're all gonna have... everything's gonna shut down and stop when Y2K came. When 2000 hit, everything was gonna stop, and that's what we're threatening here with AI. 10:20 It's gonna shut everything down. We're all gonna be unemployed. Yes, exactly. Okay. And, and of course, the thing is, at the moment, we see a lot of stories over the past, 10:30 I'd say six months, a lot of news stories with Kim Kardashian. I don't know if you saw this one. She was talking about how her... I, I think it was the bar exam. 10:41 I think she was trying to pass the bar exam, and she was using ChatGPT to help her study for the bar exam. 10:49 And, and she ended up failing the bar exam, and she blamed it on ChatGPT and said ChatGPT c- gave her the wrong advice, gave her the wrong answers, gave her the wrong everything. And so we begin even in at a, at a, 11:05 even at a celebrity culture level, we're, we're beginning to see cracks in the ChatGPT story, in the large language model story, that AI is not always actually accurate, and sometimes it gets things wrong. 11:20 And then of course, we have [laughs] at a very large corporate level, we have large consultancies that have submitted reports to government bodies, and those government bodies have found out that the reports are actually riddled with hallucinations, and that either nobody's edited these papers after having ChatGPT print them out for them, or whatever the point is that these large consultancies have not taken the responsibility to deliver a good product, whether they used AI or not. 11:53 But the point, of course, is that they used AI. 11:55 So we're seeing cracks in the- So if I'm hearing you, first of all, anybody listening and Kim Kardashian used ChatGPT or AI to study for the bar exam is the first big mistake. Come on. 12:07 [laughs] I'm just saying right now, that's the mostRidiculous thing I've ever heard, but then she should have failed the bar exam. I'm just saying, that's crazy talk. 12:15 But again, if we learn anything from history, and it repeats itself, and I started this- Yeah... the whole discussion on that by saying we have cultural spikes here, and again, that's it. She didn't learn anything. 12:28 She doesn't pay attention to history. 12:30 She doesn't learn anything, and we've got this cultural shift and shift in everything, and she never paid attention to history, which why she's failed the bar exam, because she's not paying attention. 12:40 Because now we have labor market shifts and all this in governance. She needed to understand in order to pass the bar exam, you need to understand history overall. How are you gonna pass the bar exam? 12:50 But leaders must learn to distinguish, and if she wants to be a lawyer and needs to understand this, that the headlines ne- can't be the core of transformation. 13:01 What needs to be the core of transformation needs to be understanding where did we-- where have we been to where we're gonna go, and how it all interrelates. Mm. 13:10 And I think that's what we're talking about here is understanding all of this together, and I guess what you're-- what we're talking about is that's what's happening here right now. 13:21 I think I'm trying to understand with what we're looking with AI and where it, it is. It's not gonna be a silver bullet for everybody. And I feel like there-- some people are looking for it. 13:32 But I guess the question, maybe this next question for you is, maybe we should be talking about it more, is could AI be the Iglatson silver bullet for the post-scarcity economics or the rhetorical outreach that we're talking about here? 13:48 Because I feel like we're getting over- overly excited about where it could be without reeling it in a little bit and understanding that you can't use AI for everything just yet. Yeah. 14:01 It learns from all of us, and if all of us have learned anything, we're super flawed. [laughs] Exactly. 14:07 And it needs time to learn, and then if it's only learning from us, it's also learning there's a lot of mistakes in the things that are out there. Exactly. Exactly. 14:18 And this, of course, comes down to a philosophical question of is AI ever going to be able to be what hum-- what science fiction has claimed it should be? 14:30 Um, is it ever actually going to be able to achieve a level of consciousness? And as a futurist, of course, I have to say there's a possibility it's plausible. 14:38 But then on another level, I think there's a lot of philosophical arguments a-against that as well, 14:44 that these machines may never actually be to-- be able to achieve the kind of superhuman intelligence that we-- that science fiction wants it to. 14:54 And so the question then is, okay, if it's-- even if it, even if it ever does achieve a superhuman level of intelligence, how do we actually wanna use it? 15:07 That's-- that really is the core of my question at the time, and still is my question on some level, that how is it we as a society want to use AI? At the moment, it's making a lot of mistakes. 15:20 And not even just things like ChatGPT, not even just the large language models. We can see mistakes in [laughs] old-fashioned AI with older types of automation. You can look at, w-what is it? Fujitsu, I think, in the UK. 15:36 I don't know if you've heard about the post office scandal. There was a, 15:41 for the past twenty-five years, there's been a computer program that was supposed to help these, I think they're kinda like franchisees, the postmasters at, in the UK. 15:53 It was supposed to help them keep their records and keep their accounts. 15:58 And that system completely failed them to the point that they were-- some people were being thrown in prison, some people were being fined for money that never existed, but was this system was saying the money was missing. 16:12 But it, the system was actually generating money that was never input. Okay, I'm not explaining this very well. 16:19 But one way or another, look up the post office scandal in the UK, [laughs] and you'll understand what I mean, that AI in general is seeing a lot of cracks in the, in, in the makeup, that it's not everything it's cracked up to be. 16:33 And the whole point there is how can we then use this automation to... How can we still get value from it even if it's wrong? 16:48 And effectively, w-what I hear you saying when you ask me if this is a silver bullet for Iglatson, I think on some level it is. It helps us stop and think about when the machine gets it wrong, can we stop and think about 17:04 what the machine might be, [sighs] what the machine might be, what kind of value we can get from the machine? Sorry, I'm not quite getting there. So if... Let me put it to you like this. 17:17 Hallu-- the machine, the LLMs, they mis-- they hallucinate a lot, but there can be value in the hallucinations, 17:26 and the value we can get from the hallucinations is by using our own brains as human beings to think about what the machine's gotten wrong and what that might say about us as a human, as society, and what it might say about humanity in ten years. 17:43 So sometimes, there have been a number of times that a mach- a large language model has told me something completely false, and I've stopped to think about, okay, what does that mean? 17:53 What if that could be true ten years from now? It's not true right now, and I know it's not, but what if it was true ten years from now? 18:02 For instance, I'm-Th- this is an example of a pr- research project that I was doing for a animal rights Creating new forms of economies, taking it further out. 18:12 In other words, it's destabilizing economies or establishing new economies. Thinking broader in terms is what you're saying? 18:19 'Cause, uh, as I hear you talk, and again, maybe I'm misunderstanding, but as I hear you talk about it, we're all talking about it's gonna displace jobs, but think the bigger picture. 18:28 In 10 years from now, could it be doing things from creating new forms of scarcity in different ways? 18:35 So the idea of being able, we talk about climate change and how it can improve things, but are we talking about that it can do things and make predictions in a different way that society can have new projections on things that it didn't imagine because now it's hallucinating things that might improve our society overall? 18:54 Is, is that- Yeah, yeah... how you're looking at it? 18:57 So the hallucinations themselves aren't gonna be any good, but if we can take them and refine them the same way we do with gold and turn them into something, so if we can stop and think about what if this hallucination, like I say, what if this hallucination were true 10 years from now? 19:15 We can stop and think about an innovation that might actually come out of this. 19:21 Now, getting to that innovation requires a lot of analysis and thought and usually some sort of collaboration between multiple people to actually think through what that could mean. 19:32 But I've, with my own work, I've had a number of times where I've been able to suggest to clients, or I've done a project with clients, and the clients have springboarded off of a hallucination 19:47 that led to them actually developing new ways of doing things for themselves, for their organizations, that they never would've gotten to without hallucination as a, as an inspiration. 19:59 So that inspiration in my mind is like a cultural renaissance in their own way. [laughs] They just came up with something that's cool that they might not have come to on their own terms, an interesting way of looking. 20:09 So again, we've looked at something more positive than always thinking so negative of what's coming out of this. 20:14 We're running out of time for this, but I wanna know if we had to think about this, and we're talking about all of this again as dystopian and utopian with AI and looking at, at IGladstone, in your mind right now as we try to summarize this for those who are listening, and you're, you've been s- looking at this and saying from this from a, from this whole perspective, what would you want people to think about right now and say, okay, you wanna summarize this and help them wrap this up and say, "This is the way we wanna think about it when we are putting it together with the internet, where we've been at this point, and where we might be going"? 20:53 So I, I think to summarize, really just always be aware that any new technology comes with really good images and really bad images and narratives, and be aware that the truth is gonna be somewhere in the middle. 21:11 And it m- as with nuclear energy and nuclear weapons, of course the truth is, [laughs] really is somewhere in the middle, but we're still not sure exactly where in the middle I think in a lot of ways. 21:24 But that's because your nuclear technology is, has that kind of power to it. Mm-hmm. So the question then of course is does AI have that kind of power to it? 21:34 Can it be constantly in flux that we never really know where in the middle the truth actually is? I don't think it's that powerful. Y- yes, it's not going to blow up the entire world the way nuclear energy does. 21:49 It's not, but at the same time, it's not going to provide endless energy either. It is one more step in digital technology that, in the same step that we had with the internet, it's one more step from there. It's, 22:09 it's not as big as a lot of people try to make it out to be, e- either big positively or negatively, and we just need to think about how do we actually want to use AI for our organizations. 22:24 Thinking on that before we wrap up, do you think there's so much hype put behind this right now, that is what has got more people overly excited about it because they need to just take a step back and look at it like we looked at the internet and say, "Look, it's going to settle itself down"? 22:42 And at that point you're going to be able to look at it just like whether the glass half full or half empty. 22:48 You're going to be able to make some real decisions based on that and not have to rush in and over be society and political. 22:56 We're gonna be able to make some real decisions at scale, and at resource efficiency, all the things we want, automation production or energy demands. It's not gonna overpopulate one way or the other. 23:08 We're gonna be able to look at this, but right now we don't have these unintended consequences that we're looking at right now. Correct. Exactly. 23:17 We're going to have unintended consequences pop up, just people failing tests. Those things are gonna pop up, but we'll... Regardless. Yeah. But not because of AI. They're gonna pop up regardless. Yeah. 23:30 And whether they're because of AI or not, it's, I think one of the main things is that so often in society we're looking for, so often when dealing with AI, we're looking to unload responsibility onto something else. 23:47 [laughs] We're unloading responsibility onto AI, and if we do that, then we lose the ability to maintain control of our own decisions, if we unload our, all of our thinking onto AI. 24:03 And so- So then our next conversation I want- Yeah... I'm gonna cut you off there if I may. Sorry. It's all right. 24:07 Because I want, I want us to really go on this idea that everybody's weighing that AI is the silver bullet or just another shiny tool. Mm. 24:16 I want our next conversation to address that, because that's where I think we can leave off and let our listeners understand. We'll leave them hanging right there wondering what you think. So we'll come back- Okay... 24:26 in our next show and really dive into that discussion, 'cause I think that's where I think it'll be the most important for us. Sounds good, Peggy. Thank you very much. All right. Thank you. 24:38 [upbeat music] That's it for today's Journey into IGladstone, where the future is crafted with heart and emotion. Remember, legacy isn't what we leave behind, it's what we build looking forward. Thanks for joining us. 24:51 As always, share your thoughts with us on X @connectedworld, or follow us on LinkedIn and continue the conversation there. Remember, we broadcast live every Tuesday at 12:00 PM Central. 25:02 Please check out our website at connectedworld.com or our show website. Until next time, keep innovating boldly for the promise of what's to come. [upbeat music]
