When Science Fiction Becomes Reality: AI, XR and the Path to the Singularity - Toshi Hoo, Director of the Emerging Media Lab at Institute for the Future

Are we ready for a world where AI and technology shape every corner of our lives?

In this episode of The TechEd Podcast, host Matt Kirchner sits down with Toshi Hoo, Director of the Emerging Media Lab at the Institute for the Future, to explore how technology is transforming the way we communicate, collaborate, and connect. From the breakthroughs of generative AI to the concept of the singularity, Toshi shares cutting-edge insights into what’s next for humanity—and why curiosity might be the most important skill of all.

With decades of experience in emerging technologies and strategic foresight, Toshi offers a compelling vision of a future that feels as exciting as it does uncertain. Together, Matt and Toshi unpack the promise and pitfalls of technological change, from AI’s creative potential to the ethical challenges it presents.

Listen to learn:

• A better understanding of generative AI - and why tools like ChatGPT don't actually give you "answers"
• Could the "holodeck" be more than science fiction? Toshi's work in XR and AI suggest it could be a real tool someday soon.
• Toshi's surprising connection to famed futurist Ray Kurzweil and what we know about the singularity
• How AI modeling enables more accurate scenario planning, helping organizations prepare for a range of possible futures and make smarter decisions today.
• Why curiosity isn’t just a personality trait but the defining skill for thriving in a world of rapid disrution.

3 Big Takeaways from this Episode:

1. Generative AI redefines creativity but also challenges our trust in technology. Generative AI doesn’t give deterministic results, as the same inputs can yield different outputs. This non-deterministic nature enables creativity but also raises issues with reliability and accuracy. Educators should keep this in mind when having students interact with AI-driven tools in the learning experience.
2. Immersive technology like XR and AI is on the verge of delivering "holodeck"-like experiences. The combination of AI and XR tools can create real-time, interactive simulations for collaboration and learning. These systems could allow users to explore environments from historical settings to molecular structures. Imagine how immersive learning can become with this technology!
3. Thanks to AI, modeling and scenario planning are becoming democratized, empowering organizations to anticipate diverse futures. Modeling tools informed by AI can simulate complex systems such as city planning or healthcare data. These tools enable organizations to test strategies across multiple scenarios and adapt effectively.

Resources in this Episode:

To learn more about Institute for the Future, visit: www.iftf.org

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Transcript

Matt Kirchner: 0:08

Matt. It's Matt Kirchner on The TechEd Podcast, the number one podcast in all of STEM at Technical Education. Welcome back. We're gonna have an awesome episode today talking all about the future of technology, as our audience knows. I spend my fair share of time traveling around the United States and beyond, going to conferences, speaking at conferences, sharing all the great things that are happening in and around STEM and technical education. And so it was that I found myself at the Alliance for innovation and transformation in higher education their conference in Phoenix, Arizona, early August of 2024 and I met today's guest, and you are just absolutely gonna love what this individual has to say. I listened to his keynote, and I was just absolutely enamored with the message we're gonna share today with the audience of The TechEd Podcast. Our guest is Toshi, who Toshi is the director of the Emerging Media Lab at the Institute for the Future. And Toshi, first of all, welcome. It's great to see you again. Thanks, Matt. It's great to see you again. So tell me about the work you're doing the Institute for the Future. I mean, that's a pretty big name for an organization. And of course, you've got the title of director of the Emerging Media Lab. But let's just start out kind of 30,000 feet Institute for the Future. What it is that you do and why you exist? Sure.

Toshi Hoo: 1:29

Well, Institute for the Future is a non profit, Independent Futures research, design and education organization. We were actually the world's longest running futures organization. We were founded way back in 1968 by some of the original computer and social scientists who were working on a little project back then called the ARPANET. We now call it the internet. When it was first started out, it was just a government project looking at how you could make a distributed communication system. The vision for it was, oh, this is just going to be used by military and academics to have computers talk to each other. But our founders started saying, Well, wait a minute, what if this kind of real time information system, what if this scaled out? I mean, that was all point of it is that it was could be so distributed that everybody in the world could use it to have, you know, real time share of information, real time communication, that might change the world, right? That might create a different future than we're imagining right now. And of course, that's basically what did happen. And our founders really have spent the next several decades really developing a set of methodologies around strategic foresight, as it's officially called, or more informally, futures thinking. And the institute, let's see. We work now with large companies all around the world, government agencies, large foundations, NGOs, associations like the one we met through a fit. We don't actually believe that anybody can predict the future, but we do think it's really critical to develop new practices, new methodologies for thinking and discussing possible futures, because we believe that actually the way the future is created is by people thinking about it and talking about it and making pathways towards the futures they ideally the preferable futures they'd like to see. And the Institute has a number of different labs looking at all sorts of different types of futures, everything from future of food, future of governance, we have a future of learning and education. The lab that I lead and Institute for the Future is called the Emerging Media Lab, as he said. And the you know, the ML, as we call it, is really looking at the future of what I like to say, the future of human communication, collaboration and connection, all through the lens of emerging media technology as well as emerging media mythology, meaning not just what are the tools, but more importantly, what are the new stories we can tell that we couldn't tell before? What are the new conversations we can have that we couldn't have before? Also, very importantly, who's going to be involved in that conversation, those conversations and that storytelling. So we take a very broad definition of media to be any sort of tool or platform that helps humans communicate, collaborate and connect.

Matt Kirchner: 4:06

Awesome. So you invented the internet. Is that? What you're telling me you invented the actually,

Toshi Hoo: 4:11

one of our founders, Paul Bannon, invented a little thing called packet switching, which in 1968 was the idea of wrapping data with a little wrapper protocol that could be handled anywhere in the world. Coincidentally, at the same time, same year that the shipping container was invented. Wow, before that, materials were shipped around the world to kind of random freighters, and the shipping container is exactly the same idea as a data packet. Like, let's wrap it into a standardized packet, and now it can, like, seamlessly move around the world. And arguably those two inventions in 1968 the data packet and the shipping container, kind of led to the globalized world of where we can move around things and information. You

Matt Kirchner: 4:49

know, what a transformative time you think about a year like 1968 I didn't realize, by the way, that the shipping container had been invented all the way back in that period of time. You know, of course, if I'm not mistaken, that was the same. That that both Bobby Kennedy and Martin Luther King lost their lives and assassinations. And so a hugely transformative year for the United States and the and the globe. I'll tell you. There's one other incredibly transformative thing that happened in 1968 that doesn't get talked about as much as as it should be, and that, of course, is the birth of Matt Kirk, no. And then eventually The TechEd Podcast changing, right, exactly. So it's just an incredibly, incredibly transformative year. We'll give the audience a moment just to do the math on how old I am now that I disclosed what year I was, what year I was born. But what a transformative time. And so you've been thinking about this for a long time. At least the organization has. How long have you been with the organization? Toshi, so I joined Institute for the Future in 2016 so I just celebrated my eighth year. Congratulations. Yeah, thank you so much. And it's been a wonderful, weird, wonderful, amazing, unusual journey. Yeah, what kind of a background leads to a role like that as director of the Emerging Media Lab? Well,

Toshi Hoo: 5:58

I've been interested in media and technology, actually, from a very young age. I got exposed to computers back in the early 70s, when I was a little kid by my uncle, the early computer developer and programmer, also got exposed by the same uncle to filmmaking, Super Eight filmmaking when I was a little kid went on to just kind of get involved in filmmaking, it, you know, and animation ended up teaching a lot of that as a young child, and then eventually, when I graduated high school, way back in the early 90s, I got into, let's see five different film schools, and I did them all, and not a single one was teaching how to use computers to make movies. They were literally cutting film and taping it together, which is cool, for sure. But I knew at that, even at that age, I knew that wasn't the future. The next stage of my career was about 20 years, actually 25 years as a media technology producer. I ended up going and teaching myself digital editing, because you could at that time, I basically was able to get, you know, the first version of Final Cut Pro at that time where, you know, I basically had a full multi million dollar production studio my backpack now we are right and learned editing. Ended up getting involved in media exhibits on storytelling kind of immersive and interactive. So got more and more into that whole world. And then the late 90s started working for about 10 years with fame futurist Ray Kurzweil on a number of different media technology projects, and that's where, kind of my media technology background, and then kind of the world of futures came together. And I

Matt Kirchner: 7:27

followed Kurzweil for decades, actually not, certainly not as closely as you did. But we're going to talk about the singularity in just a little bit. So we'll, I hear it's near exactly that too. Okay, we'll get into that, and actually nearer, according without question, we'll get into that in just a minute and talk about what the singular what the singularity is and why it's important, and why I've been fascinated with it. And you as well, you'll have to go back and listen. We had Eric Newman, who's the executive producer for Griselda Narcos. Oh yeah, yeah. I'm trying to remember his other big Oh painkiller with Matthew Broderick. And absolutely, it's just just absolutely fascinating. He was on, I'm gonna say, maybe three months ago or so. We'll look that up in the show notes for the audience, talking about the way that, you know, he kind of came of age, I think, right about the same time you did in the world of of media and film and how technology is absolutely transformed. That, in fact, he made the prediction that AI would write the next great American screenplay at some point in our lives, which I thought was a really fascinating thing for somebody with his pedigree to to be talking about so amazing how these technologies are changing everything you've had a front row seat to that all the way back to, you know, changes in film technology, working working alongside somebody like Ray Kurzweil, who's, you know, an absolute international thought leader on the technologies and the change that we're talking about today. What are some of the technologies you have your eyes on now? I mean, what should our audience be thinking about as we look to the next several years in terms of things that'll really transform the way we live, work and play? Sure, well,

Toshi Hoo: 8:51

as I mentioned, I started the Emerging Media Lab back in 2016 and prior to that, my career has been looking at kind of different emerging technologies, whether that the immersive dome shows. I mean, back in the day when just even having interactive media was a new thing, I got very heavily involved in that. But in 2016 the big story, and kind of the emerging technology that people reach in was virtual reality, augmented reality. So for the first six years of the lab, it was primarily focused on researching and prototyping and forecasting around what the impact of xr virtual reality and augmented reality would be on a variety of different sectors. Having been, you know, involved in exhibit design, I'm really keen on focusing on immersive experiences. And, you know, just so happens, virtual reality is an immersive experience, and it's really difficult for people to understand anything about it unless they try it right. And so a lot of what we created at Institute for the Future over those first six years was an experience lab, and we curated a wide range of all the kind of emerging XR hardware, from AR mixed glasses to virtual reality systems as well as. Interesting content. And then we also built a lot of our own prototypes for VR and AR to try to explore what's possible then. But yeah, the last two years, I mean, ever since the kind of release of chat GPT, something happened, right? There was this new chat bot, and we'd seen chat bots going far, as far back to 1950s AI, new idea, and there's been many attempts, and there's been things like Siri and Alexa, but there was a new chat bot that came out, chat, G, B, T, and it was just came out as a public research demo online and no promotion. It wasn't product, no advertising, and within a month, it had a million users, right? It's crazy. The reason was, is because it wasn't like any other chat bot anybody had experienced before, it had a level of cohesiveness and general knowledge that, by many accounts, kind of passed the proverbial Turing test. We don't talk about the Turing Test anymore, because we kind of essentially passed it back then. What was the turning test? Just so people know. So the Turing test. Alan Turing was one of the early innovators in computer science, he built the famous Enigma computer, analog computer for World War Two to break the codes of the Germans. But he imagined what all, basically all of the computing systems that we have today. And one of his thought experiments, he imagined this idea of a Turing test, or a test where you would have a text interaction with a computer, and you would have a text interaction with the human, and you would not be able to tell the difference. Got it. And so for many years, and particularly, you know, when I was working with Ray kurzwe, he talked a lot about, you know, when are we going to pass the Turing test? Because it was always very obvious, and there was, there is an organization that was running the Turing test for many years, and different AI developers were developing systems to try to pass it essentially, but really what we've seen now, and I think people, we've seen studies of this, but we also can just anecdotally, I think experientially, people are going and using chat, GPT, and that's what the amazing thing about, it produces extremely human like text, sure. So that was a turning point for our lab, and we realized this. We see AI as another medium, right? It's going to be a medium for human communication, collaboration, connection, and we've just been focusing on trying to digest kind of the big developments that have come out with this, try to sort the noise from the hype. And a lot of my role in Institute for the Future is as interpreter, so helping people understand what a technology is and its fundamentals. We've been talking about AI for a long time. Suddenly it's here. Generative AI is different than other forms of AI, and it's different in some really important, non intuitive ways. So a lot of my work is just trying to help people kind of wrap their mind around what this is, especially as it changes so quickly, right?

Matt Kirchner: 12:42

Give me an example of a non intuitive way that AI is is different.

Toshi Hoo: 12:47

Well, probably one of the most important is that generative AI is different from what I would call classification AI. So we've all been using classification AI in our daily lives, right? That's what's suggesting movies to us on Netflix, curating our social media feeds and things like that, and that's what we would think of as pattern recognition. And those algorithms are very powerful, and they've been somewhat useful, but they haven't been able to kind of have cohesive conversations and generate new ideas. Generative AI is much more pattern generation. So it looks at lots of other previous data, and what it does is it generates new patterns based on that data. And the surprising kind of discovery with especially chatgpt from OpenAI was that they were able to not just put forth cohesive information, but things that sound kind of intelligent. Now, the non intuitive part of it is that typically, most technology and most software is what we call deterministic, meaning it's consistent, right? You put in certain inputs and you get the same outputs. Generative. AI is non deterministic, meaning you can put in the same inputs and get different outputs each time. Imagine a calculator where you hit two plus two equals and you've got a different answer each time, and that's what gives it its creative ability, but it's also what makes it kind of unpredictable at times, unreliable, right? Hallucinations? Yeah, exactly. Hallucinations is one of the biggest issues. And so one of the things I like to point out is that people think of they hear AI, and they think precision answers right? And the challenge of generative AI is that it can give correct answers, but it's actually not designed to generate answers. What generative AI is designed to do is generate output that looks like an answer, and that's confusing, because lots of answers that look like answers are correct answers, right. Problem is, not only do some answers that outputs are not correct answers correct, you know, factually, you know ethically, sometimes historically correct, but the problem is they look exactly like a correct answer. Sure, and that's where we start to. Get into trouble.

Matt Kirchner: 15:01

If you look out 10 years, what will we be doing with AI and generative AI that we're not doing now, that would be like crazy.

Toshi Hoo: 15:10

Well, we're at the very, very, very, very, very beginning, right? Where, in fact, in many ways, most of us are still using the research demo that came out. It wasn't even a real product, right? Chatgpt. We're just having a little chat experience in a window, right? And most of those are kind of linear, somewhat ephemeral conversations, and they're most of them are text based. So what we're starting to see already is, first of all, the these large language models are not just about English, Spanish, French or Chinese, that language is that being applied to any way that humans communicate symbolically. So that can be now we're starting to see image generators, right? We're starting to see video generators, and not just generators, right? These models are being trained by on looking at images or video or songs or X rays or scientific data or molecular structures. So any form of data is now becoming kind of the training input into this. So these systems are not only able to do those individually, but they can do multi modal in combination. So you can have like a tech space or voice based conversation about some medical data that it's also ingested and then output a 3d animation. So that's one of the major changes that we're going to see over time, and as we kind of build out the more of the synthetic media side of generative AI, not just the text, but the ability to generate not only videos and images, but real time experiences like that's when we start to approach and this is where we start to intersect. With something like XR, you know, virtual and augmented reality, right? Which is what is going to be the interface for something like that, right? Sure. And so now we're able to essentially do things that are essentially equivalent to the holodeck, right? That's a forecast that we had from many years ago that's starting to become more and more feasible. One of the ways we kind of reframe XR and AI in the long term is to think about this as social, spatial, generative computing, meaning that, you know, in the same way the internet turned computing into a social experience, right? We just assume anything we're doing with a computer is going to have some connective part to it, right? It's going to be connected to the world in real time. So it becomes more conversational. These tools, you know, are going to become more and more that. And it's going to go beyond just data, information and media. Like right now, the chat bots we're experiencing are giving maybe answers and advice, like it might kind of give you an idea or something. The other big transformational aspect of this is when, when these systems start to have agency, and you might hear this term agent or agentic, and what they're talking about is the ability to do things in the world, not just talk about them. So that could be buy a plane ticket, that could be approve alone. It could be, you know, operate a robot to clean your kitchen. This is another big, kind of transformative aspect that we're starting to see the beginnings of as well. Now, I will say there's a lot of visions and a lot of hype around this idea of creating agents. Because the other idea is that you could not just credit agent to go and do one task, but that you could give it kind of a high level goal, like, can you make sure my house is clean and also decorated for the holidays, and not have to say, like, put up the lights and, you know, put my clothes away and all these things, but that it could break down complex series of tasks, decide what to do, and now it has agency and autonomy. This vision is what is kind of driving a lot of this idea of how transformative AI could be in our lives, where it's not just a chat bot on a screen, but it's creating whole different kinds of media experiences, as you mentioned earlier, going to transform how we create the media that we produce, and how we're going to create that, moving into more immersive kind of Hall deck simulation experiences. I mean, that's another aspect that we talk about quite a bit, is that. So that's the second time you use that term, holodeck. So I think I know what you mean, but help our audience understand what that means. Sure, sorry, that's a reference to a Star Trek thing than the next generation in the 90s. And the idea is that you could step into basically, kind of a room and that create holograms, or, you know, like a virtual reality immersive experience, right? That it's not just a simulation of what's going on, but it would be interactive. So you could say, please bring me to 17th century China. Okay, can recreate that and have characters in that space. Or you could say, you know, let's go inside of a COVID molecule and let's explore that at scale. So if we combine kind of the idea of XR, which is the ability to kind of go anywhere at any time, any scale, as many times as you want, with anybody, that's kind of the simulation side, right? When we look at the AI side of things, a term you might hear a lot is model, right? Okay, with large language models, sure, one of the ways we think about the kind of long term. Feature here is that we're building these capacities to model systems. Right with language models. We're modeling kind of how language works, how intelligence works, how human communication works, but we're starting to model even more and more complex systems, like how our bodies work, or how Alpha fold, which is a famous project looked at try to anticipate how proteins fold. How do we model how physical molecules interact? And now they're working on how drugs would interact with those. And this is this new capacity that, as we talk about kind of transformative not just how we use these tools, but how humans actually even think. I call it thinking through models, right? Traditionally, we think of like models, like a climate model, right? Scientists take, you know, really geeky scientists have the ability to go, take all this different kind of data, put it into a super, super computer that no one really has access to, and now kind of can theoretically anticipate what the weather is going to be tomorrow, or if we're going to have climate issues. You know, in the next five years, this capacity is about to become democratized to everybody, the ability to kind of model, meaning describe a system based on data, so that could be a past system, and then it kind of works in hand. In hand, the ability to model is the ability to take information, data, observations, and make a representation of that system. And that system could be a chemical system. It could be the 3d world that we live in. You know, holodeck kind of refers the idea of like that you would interact with a simulation, like in VR characters and Lydia environments, or three objects. But now extrapolate that to much wider forms of data, like, let's say traffic data in a city, or just urban development over time. You could model a city, you know, and then run simulations of either what has already been observed or what could happen in the future. And of course, that's what one of the things we're interested in is the institute is the ability to pre simulate scenarios from a

Matt Kirchner: 21:57

model. Awesome. Does all this mean that we're rapidly approaching the singularity. What do you think?

Toshi Hoo: 22:03

Well, it depends on how you define the singularity that Yeah. What's your definition? Yeah. So the original term, you know, Ray, kind of Ray Kurzweil, who I worked with for a bit, he coined that term in more popular vernacular. Before that, you know, it was really an astrophysics term that refers to an event horizon beyond which is very difficult for humans to understand, because the dynamics of that paradigm are so different than everything else we've ever experienced. And the classic example of that is a black hole, right? Because, yeah, matter, gravity, this thing pulls light in, in ways that are just not the way we think about how gravity works, or how mass, what is mass? Right? Right? When Ray kind of introduced it, this was kind of a similar idea. And he, you know, I think one of his biggest contributions to kind of helping people understand not just how to think about the future, but how transformative technology was going to be, was this idea of exponential change, you know, that's a little bit more of a common idea now, and even in like businesses we like, we expect, kind of like, you know, 100x you know, right? Yeah, chain transformation from technology. But right? We have to remember, back even just a couple decades ago, change was extremely incremental, and technology adoption was even really relatively slow. Wasn't until kind of the advent of the Internet, that you know, software could be shared immediately, that that really changed. But Ray really, kind of put forth this idea that technology, and this is based on kind of Moore's law, the idea that, you know, the founder of Intel said, Gordon Moore. Gordon Moore, we double our computing power every 18 months. And is something he observed and was able to kind of map out. And was was a truism for a long time, although there's some discussion if that we're kind of reaching our physical limits on chips, although there might be

Matt Kirchner: 23:52

ways, well, they keep saying that, but, you know, it's interesting, and we always tied it to as well, the exponential economy and the idea that products can double in price performance every 12 to 18 months, which I think, if I'm not mistaken, was a kind of a Kurzweil. I don't know if he that originated with him, but that whole idea of the exponential economy was something that kind of flowed out of the Gordon Moore idea that we can double our ability to process information, that there were the speed at which we can process information every 12 to 18 months, or, I think, Moore's case, maybe every two years. I mean, that whole concept just fascinates me. I've been fascinated by the whole concept of the exponential economy and how quickly things are moving, and maybe we're coming to the the end of that from a micro processing standpoint, I don't know, but it doesn't feel like we're slowing down at all in terms of innovation. And

Toshi Hoo: 24:33

to your point, Matt, this idea of exponential growth has been kind of translated into other schools of thought around economics, around kind of business and things like that is, of course, it's quite appealing to the business world. The idea of, like, exponential growth of profits, or, you know, capability, is very attractive. So that's really kind of what Ray was talking about in his New York Times best selling book, The singulators near that was released back in the 2000s I actually went on to co direct a film. Film, a documentary film based on that book with him a couple years later. So how closely Did

Matt Kirchner: 25:03

you work with him? I mean, you brought him up, and I knew that you guys have been connected. I followed his work for decades, and I think what it was, I think his original website was like Kurzweil ai.com or something. He actually had the foresight to put the letters AI right in the URL. And that was 20 years ago, right? Yeah, yeah.

Toshi Hoo: 25:20

So my history with Ray goes way back to the late 1970s back in Boston where I grew up. And Ray is from the Boston area as well. He was kind of from MIT, and my dad worked for his company back so as a young child, one of Ray's kind of biggest, earliest inventions was the reading machine for the blind. You know, he focused on pattern recognition at MIT, and he combined optical character recognition system, this was in the 1970s optical character recognition system with a speech synthesis system and then some software for pattern recognition to tie it all together. And created the world's first machine that could read a book out loud to a blind person. Amazing. And I, as a child, my dad had one of these sales records. It was, I remember, it was one of these, like printed records you could send out in a mailer that was square. It was kind of floppy and 45 I put it on there. I listened to the reading machine for the blind. I went to his office a couple times and got to play with it and have it read books and stuff. So that was my first and I was actually, you asked me how it kind of got in the futures world. That's actually, I wouldn't say I was working with Ray, but I was influenced by Ray from a younger idea that you could combine technologies and that by doing that, by making technology and media more accessible, you could radically change the world. It wasn't till around the late 90s, and I was living in the in the Boston area, and actually my friend was the web developer who made Kurzweil ai.net now it said.com It was dot, dot, okay, yep. At the time, I think he has.com he's probably got both. Ray went to SIGGRAPH, it's the annual computer graphics conference. This was in the kind of late 90s. He saw an early version of a digital Kermit, okay, digital puppet. This is really early before making digital characters. Was way before Toy Story and way before Pixar for sure, Henson crew had a digital puppet and Ray saw this, and as the mythology goes, he went home that night had a lucid dream in which his female virtual Alter Ego, Ramona, spoke to him and said, Ray, I want you to use virtual reality technology to bring me to life. And so Ray went to the office that day and told some folks in the office about this. My friend who knew I was doing interactive media technologies like kind of reached out and said, Ray has this idea. Our other friend, Noah rafford, who went on to become the lead futurist for did by government. By the way, I was a 3d expert, so Noah and I were brought in to build one of the world's first real time character animation systems for Ray to perform live on the TED stage. And wow, the year 2001 as a female virtual author, you go himself. So he's on stage with this motion capture suit, and then we translated that in real time to a digital essentially avatar, a puppet. And again, no one had heard the word avatar at CNN, right? It seems 23 years ago. Yeah, crazy. We believe was the world's first real time character animation performance ever done. So that was my first kind of big project with him. And then I went on to do a bunch of other smaller ones. But it wasn't until around 2005 to 2008 that I started working with him on the feature film, the documentary,

Matt Kirchner: 28:27

got it. So is he pretty down to earth guy? Like, I mean, you think about he's just so incredibly smart and so living in the future. Tell us about that.

Toshi Hoo: 28:35

Well, I wouldn't call Ray down to earth. He, you know, he's a visionary. I mean, he's a nice guy and he's friendly and he's playful and He's humorous, and his family is great, and he's actually his daughter. I just, actually, just saw Ray and his daughter at their book signing for his new book. The Singularity Is Near. Yeah, cool. But no, Ray was not a normal person account. He's operating, he's thinking kind of in a different sphere than most folks. He's incredibly smart and has been thinking about, kind of like these possibilities for literally, the last several decades. So he isn't necessarily kind of like thinking so much about the present. He's thinking about what the possibilities are. I would kind of characterize him as a bit on the utopian side. I think he's believes that, oh, more technology will always be better for humanity. I'm not sure I believe that. I think anybody who he's a technology theorist, I think anybody who is a technology practitioner knows that technology is always kind of broken right at number two, and technology, the more complex you get, the less predictable it gets. So so living at this time, right where we're in one way feeling like we're It feels like we're living in this technological future where we have virtual reality and artificial intelligence and we have all this technological power and potential. But it also feels incredibly kind of delicate and fracture, right? No

Matt Kirchner: 29:54

question. Yeah, it was. It's interesting. I was listening to Andrew Ng, who's, as you know, crazy entrepreneur. Or in the crazy, successful entrepreneur in the world of AI, he's an adjunct professor at Stanford. Watch a lot of his stuff on YouTube, and he was talking about the singularity, and the interviewer asked him the question of, are we close? And he said, You know, I don't know if we'll have it in the next 10 years. And, you know, for, I guess, for our audience benefit, when I think about it, it's like we get to the point where computers can can think and mimic humans in ways that are indiscernible, which is kind of the it's not exactly the perfect definition, but it's the way I think about it. Andrew's answer was, I don't know if we'll be there in 10 years, but I kind of hope we do. I kind of hope we I get to see it in my lifetime, was kind of what he said. And I'm not sure that everybody looks at it exactly the same way, you know? I think it'd be cool, but I also think it's a little scary. Is that is that kind of your thought?

Toshi Hoo: 30:42

I mean, the very definition of the singularity is a paradigm that we can't conceive of because it's going to be so different. So of course, that could be scary, right? I mean, could be wonderful too, yeah, by definition, right? And Ray has thought a lot about how it could be wonderful, but I think it's also easy to think about how it may not be, at very least, it might be a different and uncomfortable and hard to adapt to, right? I'm glad you defined the singularity. I mean, there's kind of two main ideas attached to the singularity. Number one is what you described, that this idea of, like, essentially human level or super human level intelligence. So the idea that, well, once we even kind of reach human level intelligence, the fact that it's continues to improve and self improve, potentially, right? That we read this kind of exponential curve, right, and that we kind of have take off, or lift off, as some people would call it, like that. It just goes so fast beyond what we can think of. The other kind of way that people think about the singularity often is this idea that sometimes referred to as transhumanism, which is that we're merging with our technology so, and that can be very literal, like Elon Musk's neural link, where we're, like, putting electrodes in our brain and having an interface. Or it could just be, I think it'd be argued that we're already somewhat transhuman with our phones, right? Like no questions this all day. It becomes kind of an extension of ourselves and our body, right, in our psychology and our social networks at this point. Yeah, when I get

Matt Kirchner: 32:03

that report every Sunday morning that shows my screen time, there's no question that that's actually happening to me,

Toshi Hoo: 32:09

exactly. And I think you asked about my history if, TF, it's interesting. And when I joined in 2016 I also look back to that as a time where there was a bit of a shift, I think, about the general public's perception of is technology bringing us to some sort of utopian world. Right until that point, it was like, oh, social media, it's so fun. We're all connected. And it was in those following years that we started really seeing examples, data and really analysis, saying, like, maybe technology, maybe the internet, is not great in all ways. It's spreading massive distant information. It's causing overthrows of democracy in some places, right? It's a mixed bag. And I think, you know, that's really part of what we try to do that city for the future, is to really kind of expand our range of the types of futures. We don't when we do forecasts. It's always important not just to consider our future, but a range of futures. And I think this is a little bit of where I diverge from rays. Ray has a very, kind of singular view of like, okay, we're this is where we're going, and that's exactly what's going to happen. And the reality, I think, is that the future is much more what I call multiversal meaning, not only are there multiple possibilities, but there's, we're all going to experience that future from a multiple perspectives, right? Sure, and those are all very different. So I think we need to have, I mean, I always really push for more of kind of a pluralistic view of like how we think about the future, and really try to dispel the myth of kind of the futurists and the ivory tower who tell you what's going to happen, and more that we all need to develop our capability, individually and as collectives, to the ability to kind of have cohesive and valuable conversations about the most importantly, the futures that could happen, and what are the preferable futures we're actually trying to create. Well,

Matt Kirchner: 33:46

and one of the things you referenced earlier was the idea that you're not necessarily trying to predict the future, that nobody can predict the future. I read a book probably 20 years ago and sat through a series of lectures on this idea of what they called scenario planning. And the whole idea was that the goal isn't to figure out exactly what's going to happen and get there before everybody else or make sure you're prepared for that version of the future. Is to say, okay, these are the four or five things that are most likely to happen. And if I start to see the world going in one direction or another, and you could think about that as broadly as all of technology, or as narrowly as maybe things that would affect an individual business, then I've got a plan for where to go. And it sounds like your philosophy is almost the same thing. Little

Toshi Hoo: 34:28

bit. I would take it even further to say that, you know, I mean, we do create forecasts at the institute that is sure, our bread and butter forecast scenarios. So forecasts are descriptions of the future. We like to say they're plausible but provocative statements about the future that help us make better decisions today. Right? It's not enough just to say something of the future. It's got to be able to be something that we can facilitate and use today, and then scenarios are more stories about those futures. So how do we imagine what it would be like to inhabit those as an individual? Or operate within those future, future forecasts as an organization, it's through thinking through not just the forecast. You're never going to come to an iftf event and just read a forecast and be like, Okay, I got I know what's going to happen now, right? The point of the actual kind of product that I like to say is not just even the things that could happen, but most importantly, as you run through your own scenarios around you as an individual or you as an organization, that you learn about your organization, you start to see yourself and your organization in ways you couldn't see before. And it's I even caution people from this term future proofing, because also that assumes, like, Okay, I know probably what's going to happen. I think if you assume that you know what's going to happen, you're going to miss what's actually happening. Yeah, that's a really good point. We are in a world that's increasingly volatile and unpredictable and chaotic. It's comforting to think, Okay, I know what's going to happen, or I'm future proofed, and people love that, but the comfort is actually lulling us into not pay attention to what's happening. Now, in our practice, I kind of alluded earlier, when we run a forecast, we won what's called the Four alternative scenario forecasts, which means you don't just run a forecast, you play that forecast out. So for example, if my forecast is in five years, we are going to have more virtual humans than real humans. And then you play that scenario out in four different kinds of archetypes. This is a framework created by Jim data, who is one of the grandfathers of Strategic Foresight at University of Hawaii. And those are growth scenario, collapse scenario, a constraint scenario and a transform scenario. And it's through running those different kinds of scenarios on the assumptions that your forecast has, that you start to understand the dynamics of what could happen. So if this happens, that might happen, and that's going to help you better be prepared and be what we call future ready, not future proof, but increase your future readiness, so that you're able to kind of re contextualize your own model of who you are, and that with the options you have in these new operational environments, which is,

Matt Kirchner: 37:04

I mean, it's just fascinating to think about that and to think, what were the four, by the way, it was transformative, collapse, growth and constraint. Yeah, so that's an interesting way to look at the world, without a doubt, all the incredible work that you're doing, at iftf, I've got to believe you've got, like, one great success story of, we have this nonprofit where there's a reason that we exist that's obviously beyond just generating cash flow and generating, you know, economic results. It's we're doing this great work. You have a story that might resonate in terms of where you really help change a life or change a market space, or do something that you felt really good about. I could give you a bunch of different examples

Toshi Hoo: 37:44

about kind of the work that we've done with big companies or government agencies. One of the challenges is, when you're doing 10 year forecasts, you don't often takes a while how to hear back from people if those are, you know, helpful or useful, but we do.

Matt Kirchner: 37:57

That's the benefit too, is that if you're wrong, nobody remembers by the time 10 years goes by, exactly

Toshi Hoo: 38:02

I could talk about projects, and I'm happy to but to be honest, in my work, the times where I feel most successful with what I'm doing is after I give a keynote, for example, giving a talk about generative AI. And when I come to somebody and they tell me, thank you, you explain that to me in a way that I could finally understand. It awesome to me. The future is less going to be created by like, one great entrepreneur that's going to be the one that changes the world, and more about the kind of collective understanding and literacies that we're building across all of our different layers of society and different types of folks. Absolutely. Yeah, I'm happy to talk about project as well, but in terms of, like, building fitness, that's a perfect

Matt Kirchner: 38:40

example. I think it was in my life's book. And I know you interviewed, Ethan Malik at one point, where he talks about that being one of the great gifts is the ability to if and if it's not him, it's somebody else that I read recently, but it talks about the ability to take really complex concepts and boil them down into something that the average person, or somebody who isn't a subject matter expert in that area, can understand and comprehend and understand the impact. And I would say you definitely have that gift having seen you speak myself. So that's a great example of how the work that you're doing is helping to change lives. I want to give you one more opportunity to talk about something that changed the life, and that's your own life. One of the questions we love to ask every one of our guests here on The TechEd Podcast Toshi, is to ask someone to go back in time. You know, you go back in time to that 15 year old version of yourself. You know, your dad's working for Ray Kurzweil, which had to be just an incredible experience to grow up in a home like that, before you had all the success in film, before all you had all the success in media, and then the incredible technology stuff that you're doing these days, if you could go back and give that young man one piece of advice, Toshi, what would that be?

Toshi Hoo: 39:44

That's a great question. As a futurist, I'm often thinking about the future and not right about the past. You know, if I were to go back to my 15 year old self, I would say, be your natural, curious self. It's going to take you places you could never imagine. You'll go absolutely and it did you. Know, I actually like to say that my main product that I produce for the world is is wonder, yeah, meaning motivated curiosity. And I think that's the most transformative thing you can do. And it's and it's not just kind of like a playful, you know, fun feeling. It's more helping people imagine that maybe the world is even larger than they imagined. No question, it is, leads into asking questions and growth. And I think that's really how the world is really transformed. So that's how I got to where I'm at. So if I were to say my 15 year old self, I'd say, just keep being curious. Don't try to guess where you're gonna go. That's right,

Matt Kirchner: 40:36

never really, yeah, no, and that's so fascinating. And I've been on this actually, this kick about curiosity this year, and it's been influenced by guests we've had on the podcast. So I'll give you just three quick examples. Mike Bigley, who is the superintendent of a school district in western Wisconsin, just created a whole emerging technologies lab for his students and all kinds of really cool applied AI experiences for those students when he's looking for educators to be part of leading change like that. He said the number one personality trait he looks for is curiosity. Then we had Todd wanick, who's the CEO of Ashley Furniture, good friend of ours, largest furniture manufacturer in the world, of course. And we asked Todd, when you look for people to lead your AI transformation? I said, What do you look for? And he said, Curiosity was the first thing that he'd look for. And then we had Barbara humpton, who's the CEO of Siemens, huge company, of course, Siemens, USA, $20 billion in revenue, 45,000 employees. Give or take. One of the things that Barbara humpton said is, if you have curiosity and initiative, the world is yours, which I thought was really, really interesting way of looking at the world in the fact that here you are with all the cool experiences that you've had. Nobody knows what their career journey is going to look like. You've had an incredible career, no doubt more to come. But for you to say, Hey, I would remind my 15 year old self to be curious is just one more data point on this whole journey of curiosity that I've been on here over the course of 2024

Toshi Hoo: 42:00

a lot of people come up to me right now and say, What should I tell my 10 year old child? Now I actually think the future belongs to the curious people. Right? We're in a period of time where so much is being disrupted, and that's scary, but it's also an incredible time for new things to happen, and it's the curious ones that are going to really create and explore those The future

Matt Kirchner: 42:19

belongs to the curious people. I can't thank the curious Toshi, who enough for joining us here on The TechEd Podcast. It's been a phenomenal conversation. We reference some things I know our audience is going to want to check out. You will find those and all of our show notes at TechEd podcast.com/who that is. TechEd podcast.com/h O, O, need to remind our audience as well to check us out on social media. As you know, we are on LinkedIn, we're on Facebook, we are on Instagram, we are on x, we are everywhere you would ever want to look for your social media. So while you're there, reach out say hello. We would love to hear from you, and we would love to see you again next week on The TechEd Podcast, thanks so much for being with us. You.