AI research looks good and that is the danger

Well, first of all, thank you for having me. it's you know, great opportunity to speak to you and to the people to your listeners as well. answering that question is always a really difficult one for me. I get asked I get asked it a lot. and the only answer that's really true and satisfying for myself at least, that's usually unsatisfying for everybody else, is go to music conservatory and start as a classical clarinetist. That's how I got started. And and for me, I I think it's important to start there because finding my way to business, finding my way to business innovation, finding my way to being, I guess you can call me an entrepreneur, and a you know, a founder, starts with doing what you love and kind of just continues along the the line of doing what you love. I started as a classical clarinetist and as a professional musician and found after some success that it wasn't exactly what I had thought I was gonna be. I was twenty-three, a professional musician and not really knowing where to go with the rest of my life because I realized I'd gotten there and that this was the next 40 years. And I wanted to use my brain a little bit more. So I took the leap of going back to school and becoming an anthropologist and really following that. I was unlucky enough to be one of the people leaving academia or leaving a PhD program right around the time when the 2008 housing cris destroyed the the global economy and basically crushed academia into a a, you know, small square, small cube. So it was a point where it was kind of like, well, if I'm not going to be a professor, what am I gonna do with myself? And this was just at a point in the world when the design thinking turn had really gotten started and really started making an impact in the world. And I was one of the beneficiaries of that. There were a few people ahead of me, you know, people like Genevieve Bell, who was the anthropologist at Intel for many years. But it turned out that people started to actually think that anthropologists had an interesting thing to say in this design thinking world. And so I got myself a job at a consultancy and essentially was a researcher for many years and then learned the business all of the business stuff kind of on the job basically. So it was it was a full School of Hard Knocks MBA kind of approach to things of learning innovation and business practices and the whole world of business. But being an anthropologist, it kind of helped me because what we do is show up and learn about something new and try to become as close to a native speaker of that language as we can get. And so I did my thing and and over time became a fairly effective consultant in the design thinking and sort of innovation strategy space. And then eventually started to realize that I could run my own shop and you know, sort of turned turn my the skills that I had learned on the job into the skills that I use now. so that's really kind of the trajectory. It was really just following my own interests and then finding out what I'm good at, finding out what I'm not good at and finding out where what other worlds of in you know might be waiting for me in the future and just sort of following my nose. So that's really how I got here. I certainly didn't set out to to become a business person or an you know an entrepreneur or a business owner or anything like that. This is as much a surprise to me as it is to anyone.

Yeah. Well there's two things. I I'll start with what I do now. because I think design thinking has I I would argue it's kind of dead actually as an idea, but I I'll talk about what I do now and we can go back a little bit and talk about how that's different from what design thinking was like let's say fifteen years ago. Right now I run a consultancy, which is human futures, where we position ourselves as a strategic partner. So essentially what we do is we provide strategic advice for companies all over the world, companies, governments, NGOs, and we provide strategic advice aimed at trying to get something done. In the world. So is that a new product, new service, new experience, new business strategy, new business culture, new way of working, new market, you know, all of these kinds of things. in and we specialize really in the innovation space. And what that means is it's new, something that's new, something that's either never been been there before, or something that's filling a gap, or something that's kind of an interesting. Connection or conglomeration of things that can actually help serve a company, serve their customers better. So and what we do is we provide that strategic advice on the basis of really heavy-duty, hardcore, rigorous research, which is both insight and foresight. And what we are grounded in is what we call the human futures approach, which is an integration of insight and foresight working together as a seamless research practice. And essentially we learn about the world on behalf of c our clients. We tell them about what the world looks like outside of their front door, and we help them figure out what they're gonna do about it. And it's really not that more complicated when you really think about it. But in the practical application, what that means is Answering difficult questions that they have about where they are in that moment in their business and trying to help them figure out what they need to do in order to be successful in their ambitions. And that's kind of where the difficulty starts because that's going to be different for every client. You know, if you're in healthcare, if you're in automotive, if you're in retail, if you're in luxury, if you're in food and beverage, you know, we work for our everybody, all over the world. and A lot of times those those are difficult decisions. And the the practical side of that is we also have to work with a really wide range of people in different functions within the team. We work from everything from the board and the C-suite all the way down to like a product manager. and so that means that every single application of what we do is completely different because the people that we're working with have different requirements, different places, different perspectives, different needs. different difficulties that they're facing depending on where they are in the organization. And so we have to be adaptive to what they need to know. And so we become essentially storytellers of the things that they need to understand and then facilitators and kind of guides for how to work out of work their way out of where they are.

Well, things you should know is it's the first book that we're gonna do. The intention is that we're probably gonna do this every year. instead of it being a research report, like a lot of the other agencies or a lot of other companies produce every year, what it is is it's a resource for people. So it's a collection of about 80 to 100. What we call in foresight, we call them weak signals. They're essentially indicators of change and indicators of difference in the world that are actually creating and crafting the world that we're all living in. So things you should know is a collection of stuff you really need to know if you're going to be in the innovation space. You know, what does the manosphere actually mean and what what impact does it have on things? How is AI going to change things really? what does income inequality actually really mean for for business? How are things like resource scarcity, which we're all facing right now, how is that going to impact businesses globally? What does it mean to have one of the most powerful countries in the world suddenly kind of remove itself from its responsibilities that it had set for itself for the past 80 years? You know? How do we how do we deal with these kinds of things? So what it is is it's a book a book of signals to provide people with an understanding of at least what those signals mean so that they can be a little bit more thoughtful and a little bit more careful about how they talk about them, how they use them and how they integrate them into the way that they you know, do their work.

Realistically, it's not even a single signal in this. The the thing that we constantly have to remind people about, well, there's actually two things that we have to remind people about. One is that no matter what the change is, whether it's a technological change, whether it's a governmental change, whether it's you know an economic change. It's people that are behind it. It's human beings. That's the actions, thought, beliefs, and you know, mistakes of real human beings living their lives that are actually behind all of this change. You know, one of the things that we try to fight against when we're doing this kind of work, and it shows up in the book, is that, you know, things like technology doesn't drive social change. People drive social change through technology or with technology. And that reorientation is extremely important because if you miss the human story behind all of this, you're not really understanding change well enough. You're certainly not going to be prepared enough for it. And you're also not in a position to understand how you as a company or as a human being can participate in that change and help work towards a better future for everybody. So one of the things that these signals are trying to do is kind of peel back the story so that we're actually talking about what's really going on rather than just this sort of like hype cycle, you know, worry about this stuff. The other side, the the the other signal that shows up all the time that people are frankly sick of hearing about, but is just absolutely true is climate change. You know, one of the interesting things when you do foresight and human centered research like this is that the one major external factor that is and isn't being driven by human change is the climate. It has a huge effect on all of us. And it's the one thing that links us all together as a species. And, you know, understanding the implications of that helps you not just to understand that climate change is a problem, we should do do things something about it, but it's more that we are all integrated and connected. And we are all integrated and connected on a rock, which is our home. And if if we don't get this right, there are major consequences. And we are starting to see those consequences. And those consequences show up in smaller things than, you know, like higher gas prices or food scarcity. They show up in the movement of people. You know, a lot of the migrant crisis and a lot of the the things like the the population decline are Inextricably linked to climate change because we live in a finite system and we're running out of space and resources. And that's going to affect the way that we behave in ways that we can't anticipate very easily. So a lot of the thing that we keep talking about in this space is that, you know, climate change gives you not just a signal to worry about, but also it shows you how the interconnectedness of everything is such an important facet in in doing all of this kind of stuff. And that should show up in business strategy that should show up in the way that resource and supply management chains and are being handled it should show up in innovation strategy it should show up in the way that technology is manifested it should show up in the way that we you know integrate together it should show up in the way that we cooperate so a lot of times what we're doing in in this kind of stuff and it shows up in the book as well is is kind of the metacritical story, the story above the story that matters. So we're kind of what's what's underneath and what's above is really the the the major kind of point that we're trying to push home.

Yeah. It's a really, really thorny subject because and we have to start a little bit further back away from AI because AI is just it is t in a very real way another stepping stone in the story of human progress. And what I mean by that is that we have been telling ourselves this story that human beings started in the caves banging rocks together. And we have grown over the years, and we figured out how to smelt copper, and then we figured out how to smelt bronze, and then we made iron tools, and then from iron tools we moved on to, you know, nuclear bombs and computing and stuff like that. And all of this is about this sort of inexorable direction where the human species moves to perfection off into the future. so AI. Is just another stepping stone in that sort of story of progress in terms of like we are moving from the Stone Age into the Iron Age, into the information age, etc., etc., into the AI age. and so it has a social cachet behind it, but which is really more about a myth. It's more about the story that we tell ourselves that AI is the next step in our evolution because we are an evolutionary species that's now in control of our own evolution and we're going to use AI to push into this brave new world, et cetera, et cetera. and a lot of the tech companies, frankly, are using that to their best advantage. They are the owners of the future, according to their hype, because A look at AI. You know, we now have we're pushing towards this super intelligence that's gonna either destroy us all or make us gods, you know. the story is actually a lot more prosaic and it's a lot more boring than that. It's a tool, and it's a tool that we have to figure out how to use, and it's a tool that will evolve, and our use of it will evolve over time. and so one of the things that we were trying to do with that series was just introduce the fact that actually one of the stories that's missing in the hype cycle is that. AI is not going to solve all of everybody's problems because all of those problems, for the most part, are created by us as well. You know, a lot of the management stories about the fact that you've got a workforce that's not as productive. If you throw it, you know, the story is if you throw AI into the mix, it'll be more productive, or you could even get rid of the workforce and be, you know, even more productive that way. The lack of productivity of that. team of that group is is not because of the lack of AI or the lack of tools to do that. It's it's a human story that sits behind that. And so one of the things that we were trying to do with the with the series was show people how to provide a purpose and a social role for AI so that its use and the use case and its its role in work reveals itself without having to build something. We don't need to build necessarily. We can we can use it as a tool, but what how are we going to use it as a tool? What is it actually doing? How does it integrate into teams? How do you build a team around an AI system in order to develop it? And part of that series, we were arguing that instead of you know replacing the team and replacing the research process, because what we did was we we we wrote the entire series from within the perspective of all right, if you're gonna use it for research purposes, what does that actually mean? And we could talk about that. in terms of what that means for research consultancies, in a second. But if you're going to use it for research purposes, how can you best use it? And one of the most important things that you do is you say, all right, we have a research process. Who does what in each each of the stages of this research process? And Just asking that question immediately opens up the other question of all right, what does the AI do in this? Are we going to do how is it going to be the researcher? Is it going to be the analyst? Is it going to be the storyteller? Yeah, like where in this system does it work? And what we were arguing is that actually the most productive thing for an AI system there is not to be the specialist, but to actually just be the researcher system. And the moment we called it a research assistant, immediately everything it's supposed to do, everything it shouldn't be doing, everything it all the limits that we're gonna be putting on it, all of the requests that we're going to be giving it, all of the things that we have to design it to do within that process, suddenly immediately become clear because everyone knows within a research context what a research assistant is and what they're for. And so we're like, okay, so now we have a research assistant that needs to do this kind of work and it can't do this kind of work. So How do we build the the AI tool in order to fit that particular role? And so what really is Trojan Horsed into that article series is the right way to find a future for AI within a human, within a set of human activities. You know, what we essentially set out can be pulled out of the research context and put into any other context. So that's really what we were trying to do. And we're really trying to do this because so many people get lost in the hype cycle. And I get it. The hype cycle sells a lot of product and it it you know gets a lot of investment. there's a practical reality to why people talk about AI in the way that they do, but it has very little to do with AI. ultimately AI. Is a really cool computing tool that we still haven't figured out how to use. And really, what defines one of the things I've always said is what defines this moment in our development and our relationship with this tool is it's kind of I've been calling it the pre-Cambrian explosion of of AI. And this is true of any innovation cycle, to be honest. Any new thing that comes along immediate goes through this period where Everyone just tries everything and it's just chaos. It's just like what what sticks? And you know, in the the Pre-Cambrian era, it was a moment in the evolution air the evolution of life on earth where life just tried everything. You know, what does it look like to have nine eyes and 15 legs? What does it look like to have a hard exoskeleton and 65 you know hands? It tried everything and then stuff started to die out. And so that's what's going on right now is we're just trying everything and seeing what sticks. And eventually the good ideas from this period will survive and everything else will kind of die off because it's a little dumb or not feasible or you know, too expensive. And that's ultimately going to be what AI is. So in 10 years' time, we'll have a much more sensible kind of perspective of what AI is. but right now the development of AI is being pushed forward by people who have other goals with the technology. And that's fine, you know, that's the way of business, the way of the world, but it, you know, it it just means that AI is just a little bit silly right now.

That's a really great point. and there's two sides to that, which is I and I think you're absolutely right. AI has the ability to fill in your own knowledge gaps in a way that makes you think that you're the smartest human being on the planet when in fact you're just, you know, you're an augmented person at that point. which is an interesting pathway. You know, what is what is the future of augmented people actually look like in terms of someone with two brains? That's an interesting question that that we ask, you know, in a lot of the foresight work that we do. but the other side is that the and this is kind of the human side of things, is that ultimately the people who are designing this. Are people who came off of what we used to think of a c as kind of the app period, the period of apps and, you know, high-touch app UX and, you know, Instagram Doom scrolling and stuff like that to keep engagement high? These are still tools that are coming out of companies that think like that. They think like they did 15 years ago and have done for the past 15 years because it's made them a lot of money and it's worked really well. so the whole tech industry to a certain degree is still worried about, you know. Weekly average user or weekly active user. and so keeping the largest number of weekly active users on your platform is still the goal of most tech companies. And what that means is that baked into these AI systems are all the little Easter eggs and all the little UX nudges that keep you engaged. So it's designed to tell you that you're the smartest, most clever, interesting human being that's ever existed on this planet. So you'll keep using it. You know, so and it's that's how the tech world works. And so it's not surprising that they haven't moved beyond that because that's how they've built their, you know, trillion dollar companies. And so it's it's kind of a double-edged sword. And so what we're dealing with right now is AI that is built on the legacy of the past that hasn't broken through its purpose statement yet. And we haven't really figured out how to use it. And we haven't really entered into the mature stage where we actually understand what it's for and have grown into like the UX principles and the use cases that actually will define what the future of AI is. We're still in this transitional moment right now.

Well, what's interesting is that right now, because of the AI tooling, and it's not necessarily the tools themselves, because I actually don't think that AI is particularly good at research. you know, being a specialist researcher and seeing the outputs of a lot of these tools, they it's really not good. it looks good, it feels good, it's easy, but it isn't good. And it's really dangerous because of that. But because because of that problem. And because everyone is trying to, you know, create a company where, hey, you can get rid of your entire research team and even all of your customers. You don't have to interview a norm a real person ever again, you know. And you can have it all in seconds. All of those promises are shifting the research, consulting, and innovation world pretty substantially. and as a result, you know, human futures has to adapt. And you know, one of the adaptations that we're doing is changing the the procedures that we're using to actually execute these projects. So now we're actually providing services where instead of running a research, you know, 10, 15 years ago, we used to we used to run projects where clients would come along and they would sort of come along for the ride and experience the whole thing. And it was kind of an experiential journey for them, which was transformative for their thinking and really important, but it's slow. It's really slow. I mean, it's fast compared to other kinds some other kinds of of this type of research, but it it's pretty slow for business. and innovation. Now, what we're doing is we're speeding up the tempo. So essentially, we're changing our our research practice where instead of doing research for hire, where we take them on the journey and we do the whole thing, you know, in a a single process with them, we're doing 80. percent of the work beforehand. So we have a continuous scanning practice, we have a continuous insights practice, we have data science, we're managing all of this information where essentially what we're able to do now is half to 70% of a project before the project's even been contracted. Which means that we have the insights, we have the foresight perspective, all of this stuff, and we can compete with the tempo that of the expectations that AI has brought. So people expect, you know, immediate results. We can provide that now. And then tailor it to the circumstances that our customer and our clients are are needing. so what you get is the best of both worlds. You get the speed and rapidity, but you also have the expertise and the the direct knowledge with real human beings and real situations. and so that's been a major change for us. And the other side of it is that for many years we've been running Human Futures as a for-profit research consultancy, but we've also been teaching. We've had a strong learning and development upskilling and education program in the background where, you know, we do courses, we do training, we we help build teams, we help build departments. We are we've recently launched the Human Futures Institute, or actually relaunched it. It was sort of something a a little bit different a few years ago. We're we've relaunched it as a training and research center. And what that means is that we're now providing the courses and the training to anyone who wants to to learn the human futures method, advanced foresight and advanced insight methods. for applications in strategy, business strategy, forecasting, futuring, certain kinds of anthropology, and also just in innovation and in business in general. So you know, we've been doing this for 17, 18 years for the most part, and we're now pr providing the the sort of the benefits of what we've learned over the years to whoever wants to come. So we do that both for kind of as one-offs for educational things for companies. We tr we design entire educational opportunities within organizations, but we're also now providing courses to individuals who want to learn and be certified in our particular blend of insight and foresight working together.

well, if it's consulting work or sort of commercial stuff, then human futures dot com is probably the most best way. we will be launching officially human futures institute at human futures.institute tomorrow, actually. So that that's gonna go live tomorrow. yeah, everything has a a reach out and you know, you can just email us directly and and you know, we'll we'll pick up the phone.

Likewise, thank you very much for having me.