AI (artificial intelligence) poses a challenge to human work, threatening to usurp many human jobs in coming years. But a related question that’s too often ignored and needs to be addressed is whether this challenge will come from AI in fact being able to match and exceed human capabilities in the environments in which humans currently exercise those capabilities, or whether it will come from AI also manipulating our environments so that machines thrive where otherwise they could not.
AI never operates in a vaccuum. Rather, any instance of AI operates in an environment. We often think that AI will leave an environment untouched and simply supersede human capability as it operates in that environment. But what if the success of AI depends not so much on being able to rival human capabilities as in “changing the game” so that AI has an easier job of it. The mathematician George Polya used to quip that if you can’t solve a problem, find an easier problem and solve it. Might AI in the end not so much supersede humans as rather impoverish the environments in which humans find themselves so that machines can thrive at their expense?
To see what’s at stake with this line of concern over AI, consider the prospect of automated vehicles. Automated vehicles, we are told, are poised to take over all of human driving. Once the machine learning for the automation of driving matures just a bit more, we are assured that human drivers will be out of a job — the machines will drive so much better than us that it would in fact be unethical for humans to continue to drive. And, of course, as an unfortunate side effect, humans whose jobs depend on driving will all be put out of work (truck drivers, taxi drivers, etc.).
Now the actual progress of automated vehicles has not reflected this rosy picture (rosy if you’re an AI advocate, dismal if you’re out of a job). Recent fatalities with automated vehicles have undercut this picture to the public at large. But the deeper conceptual problem with the automation of driving is that there appear just too many contingencies on the road, contingencies that human drivers can handle without difficulty but for which machines require specialized training. [Read more…] about Virtual Railroads and West Virginia Back Roads: AI’s Temptation to Theft Over Honest Toil