I've already mentioned driving forces, and so let's just think about what are potential driving forces and I'll give a couple examples, and we'll talk about what we can do with driving forces. So one driving force is climate change. It's happening, it's a fact, you know, you can debate certain things and you can predict different things about like how fast it's happening, how many parts of CO2 per million, how many degrees Celsius the average global temperatures are changing, all of these exist on a spectrum, but we know that there's some directionality in terms of a heating world. So that's a kind of driving force where it's a matter of degree. We know that there's some sort of vector in one direction, and it could be fast, it could be slow. We don't know the sort of specific milestones in the future of when certain ice caps will melt, and all of those things, but there's a certain directionality that we know. There's other driving forces that where we're not sure if something's going...
to happen and it's more like a binary of like who's going to win the next election, and it's more of a one or another. There's always going to be one winner of the horse race or whatever you're thinking about. And so... It's more interesting for us sometimes to think about a mashup of these driving forces of sometimes doing something where you know a general direction, but you just don't know the scale or the size of that direction, and then could also have something that's more like binary of this candidate A wins, candidate B wins. You know, this bill passes, that bill doesn't pass, and then you can do the what ifs. Sort of like that Gwyneth Paltrow movie, Sliding Doors, where it's like you get on the train or you don't get on the train, and then what are the what ifs of what happens. So you can think about things in a binary like that. Other driving forces could be things that we've mentioned already, automation, artificial intelligence, humans becoming more and more cyborg-like. What does it mean when more and more humans are enhanced, augmented in some way? And so you can also think about this as a spectrum in terms of the speed of RND, or the speed of diffusion, if we're interested in, I don't know, cyborgs specifically. Alright, there's a weak signal of... There's a few human beings on earth right now who are certified cyborgs. There's this guy Neil Harbisson who's a British Catalan guy who runs the Cyborg Foundation, and he was born with a very extreme form of color-blindness and so he can't see color at all, he sees everything in black and white, but he has a background as a musician, so he has a well-tuned ear. He has a cyborg implant that's plugged into his skull that has an antenna with a camera, and he can point it at things and people and it's connected to his brain, it vibrates at different frequencies based on the colors that the camera, that the sensor is picking up, and he's taught himself, he's trained his brain to interpret those different signals, these different vibrations as color even though he's never physically seen color. So he's extending himself. So that's a weak signal, that's not like a mainstream thing, but it is possible. So you can also think about what happens when there's a million cyborgs, a billion cyborgs on earth, what are the implications of that? Are people going to be jealous of that? How do we regulate cyborgs? What happens there? So there's all sorts of things you can do with these driving forces and weak signals and things like that. I talked about how the future is not a singular thing. We're not trying to predict the future. So one thing you can do with driving forces is choose a couple of them that are interesting to you. So maybe for your industry, for your team, you're interested in the mashup of... Between climate change and automation. So you could just create this Cartesian axis, one axis is around the speed of climate change, the other axis is on the speed of AI development, or development of cyborgs. Whatever you're interested in. So once you have this Cartesian axis, it's a matter of degree and you have four different possibilities, so you have fast climate change, fast AI development, fast climate change, slow AI development, slow climate change, fast AI development, and then slow and slow. So you get the point here in this visual picture of these four scenarios. From there you can build out a world around that scenario. So what I do for my degree students when we have more time for this is we'll build out these scenarios, we'll choose the driving forces that are most interesting to people, we'll go wide with the driving forces, and then we'll narrow down, we'll do voting, we'll do consensus, come to two driving forces that we want to focus on at any one time. If you have too many driving forces at once, you've got too many dependent variables and it's just a lot to deal with, so it's helpful to just segment like a couple of the things that are the priority. So it could be about market forces versus natural forces, or a couple different driving forces and trends, then we mash them up, create this four-part Cartesian axis, and then we come up with scenarios around that, we come up with stories based on that. So I won't ask you to do this now, but you can think about your 10 years from now stories that I just ask you guys to do cold or inspired by each other, inspired by my story. But you could see how you could write four different future scenarios now of you 10 years in the future based on this grid that we've created. You do the one where there's fast climate change and fast AI, you do one with the slow climate change, slow AI, for each of those four, and you can see how those future realities, those future possibilities would be different, because you've chosen these two driving forces and then four different possibilities. So this is just one way to identify and choose different things that you want to explore in your future scenarios.