Would you rather be plausible but dull, or implausible but fascinating? Economist Robin Hanson has made his choice. His new book The Age of Em: Work, Love and Life when Robots Rule the Earth, envisions consequences of advances in artificial intelligence. Hanson is speaking at Stevens on Wednesday, November 16, Babbio 122, 4 p.m. Below he answers a few questions. –John Horgan (A longer version of this Q&A was published on Horgan’s ScientificAmerican.com blog, “Cross-check.”)
Horgan: What’s the sound-bite version of The Age of Em? Is it a prediction or a thought experiment?
Hanson: “Em” is short for “brain emulation.” The idea is to port the software in a specific human brain to new computer hardware. Today if you have a program running on an old computer, a program you want to have available on a new computer, one approach is to watch the old program, guess how it works, and then try to write software on the new computer that works they way you think the old program works. But another approach is to write an emulator on the new computer, that makes this new computer look like the old computer to the old software. You can do this without understanding how the old software works.
To do this for human brains, we will need three techs, none of which is good enough yet, but which probably will be within roughly a century. We’ll need cheap computers, brain scans with enough spatial and chemical resolution, and signal-processing models for all the kinds of brain cells in a brain. The “age of em” is the era after ems are cheap enough to displace humans on almost all jobs, and before the economy changes yet again to something new, I know not what.
Horgan: Given that scientists can’t explain brains, why do you think engineers can “emulate” them?
Hanson: “Explain” isn’t all or nothing. We understand part but not all of a great many organ systems, such as muscle, bone, blood, and skin. We also understand a great deal about many systems that exchange signals with brains, such as eyes, ears, hands, and mouths. We have even created and fielded functional replacements for many of these systems. An “em” is an artificial system that replaces the signal-processing function of a brain. We can create an em by only understanding how each cell type processes signals–we don’t need to understand why that works at higher levels of organization.
Horgan: Our desires are rooted in biology. Where would the desires—if any–of artificial intelligences come from?
Hanson: When we write programs directly, we can explicitly encode their desires. But ems inherit their desires from the spaghetti code that evolution gave humans. So ems have mostly the same range of desires as humans, even when those desires are no longer functional.
Horgan: Do you yearn to be an em?
Hanson: Most ems will be copies descended from a few hundred humans that are most productive in the em world. I’m too old even now to have a chance of starting one of these successful clans. But still, I’d love to see their world, and have a better chance at immortality.
Horgan: What do you think about all the chatter about “reality” being a simulation?
Hanson: I doubt I’m living in a simulation, because I doubt the future is that interested in simulating us; we spend very little time today doing any sort of simulation of typical farming or forager-era folks, for example. But I’ll note that we mostly like such topics to stretch our thinking, not because we take them seriously. Horgan: My Stevens colleagues Lee Vinsel and Andrew Russell argue that innovation is overrated and maintenance of stuff we have underrated. Comment?
Hanson: It is certainly possible in some particular time and place for maintenance to be underrated and innovation overrated. I’d love to have betting markets on such questions, to leave them to those who know more on them than I. But still, the more that the future matters, the more that innovation matters relative to maintenance. Innovation accumulates over a long run, and pretty much all growth we’ve ever seen has come from innovation. In contrast, the benefits of maintenance decay more quickly with time. However, I will say that invention is very much overrated relative to all the other contributors to innovation, such as diffusion.