In this week's Rule Breaker Investing podcast, Motley Fool co-founder David Gardner has invited a special guest: Robin Hanson, a George Mason University economics professor and research associate at Oxford's Future of Humanity Institute. Hanson has master's degrees in physics and philosophy and a Ph.D. in social science, and he previously worked on A.I. at Lockheed Martin and NASA. His recently published book is The Age of Em: Work, Love and Life when Robots Rule the Earth.
Hanson joins us this week to discuss a broad topic: the future. At this point, the cycles of change are getting shorter. The economy doubles every 15 years or so. But even through those transformations, it's often possible to predict where we're headed.
This video was recorded on Sept. 14, 2016.
DAVID GARDNER:
One thing that I've talked about before on this podcast -- and I'm going to rechannel Ray Kurzweil, with whom you may or may not agree on this point -- is the concept that the predictability of the future keeps narrowing. That in ancient Egypt, you could predict pretty well what your grandchildren would be doing. By the time I came of age (when I was 13 years old in 1979), you could look forward and say things like, "Well, satellites and cable TV. It looks like that's a good growth industry."
Fast forward to today. It feels like I can predict only a few years ahead [what will be] meaningful technologies. And we see things ahead of time. We see 3-D printing before it really hits. Those kinds of things.
ROBIN HANSON:
I think your impression is a little misleading. I think what we can see is into a certain number of doublings. So today the economy doubles every 15 years. That's the time scale over which a lot of fundamental change is happening. It's hard to see through many doublings, but in the past, when the economy only doubled every thousand years, then seeing through a few doublings meant seeing through a few thousand years. So fundamentally the problem is seeing through doublings, and not so much seeing through time. The more change happens in any given time, the harder it is to see through time.
But we actually can see quite a lot. There are people, many decades ago, who foresaw roughly when digital cameras would show up and all these things. They just used straightforward projections. I was actually part of a group of people, before the World Wide Web showed up, who foresaw the World Wide Web and were trying to predict it and then influence what would happen. There are many things you can see through a few doublings, and there's also things you can just see that are more fundamental. The Age of Em is a scenario [about] if a certain technology shows up and gets cheap.
Now, it's hard to guess which technologies will show up when and be cheap, but conditional on certain technologies showing up, I think we can actually say a lot about how the world might play out.
DAVID:
I want to ask you more about that, Robin. I think somewhere in the book you say the chances of what you're describing in the book actually happening are something like one in a thousand. Is that right?
ROBIN:
Well, I was trying to say if you take all the things I say and make a conjunction out of it, it's a ridiculously low probability.
DAVID:
And it's remarkable, because you have an incredible if this, then that going on in your head that you put into the book where well, if that's true, then this will be true and it's very, very deep. But getting back to looking in the near term, which is what I wanted to talk about.
So one thing we do here at The Motley Fool is, when we pick a stock, we imagine some things that we hope will happen, that to us will be indicators (green flags -- future) that if those start lighting up green, we were right and the stock's going to do well. We put some red ones out there, too, and that's what I call our 5 and 3.
I was wondering if you could do that a little bit. Thinking backwards from a hundred years from now, could you provide us a few flags that if those flip up and they're green, then you're looking more and more right, and if they don't, then you're looking more and more wrong?
ROBIN:
Well, sure. There are three technologies required to make emulations feasible, and they all have to achieve much better levels than they have now. One is we need lots of cheap, fast, parallel computers, so if computers just hit a block and they just don't get better, that's a big red flag, but if they continue to exponentially improve as they have...
DAVID:
Quantum?
ROBIN:
...that's a green flag.
DAVID:
Yes.
ROBIN:
Quantum may not actually make that much difference. It's just ordinary computers I would focus on.
DAVID:
OK.
ROBIN:
Second is brain scans. You need to scan brains and find spatial and chemical detail. Now we can actually do scanning at fine enough spatial and chemical resolution, already. You just need to scale it up. People have been doing that, but you'd want to see that that actually continues, as we hope.
And third, you need good models of cells. There is a whole academic literature where people work out computational models of particular kinds of brain cells, but we just need them for all the different brain cells. We don't even really know how many kinds there are. So it would be nice to see that people start to count how many there are and start to work down the list of having models for all the different cells. If they somehow reach a roadblock there, that would be a red flag, but if they keep going, that's more of a green flag.
Now, another red flag is, of course, if other kinds of artificial intelligence (such as the other kind that's more in the news these days) accelerate as fast as many people seem to hope or expect relative to my expectations, I guess that's kind of a red flag. That might mean that that kind of A.I. would reach human-level abilities before this kind, in which case the scenario is less relevant.
