Fact checking Moravec's paradox

I have launched a YouTube channel in which I analyze AI developments from a normal technology perspective. This essay is based on my most recent video in which I did a deep dive into Moravec’s paradox, the endlessly repeated aphorism that tasks that are hard for humans are easy for AI and vice versa.

Here’s what I found:

• Moravec’s paradox never been empirically tested. (It’s often repeated as a fact by many AI researchers, including pioneers I know and respect, but that doesn’t mean I’ll take their claims at face value!)

• It is really a statement about what the AI community finds it worthwhile to work on. It doesn’t have any predictive power about which problems are going to be easy or hard for AI.

• It comes with an evolutionary explanation that I find highly dubious. (AI researchers have a history of making stuff up about human brains without any relevant background in neuroscience or evolutionary biology.)

• Moravec’s-paradox-style thinking has led to both alarmism (about imminent superintelligent reasoning) and false comfort (in areas like robotics).

• To adapt to AI advances, we don’t need to predict capability breakthroughs. Since diffusion of new capabilities takes a long time, that gives us plenty of time to react — time that we often squander, and then panic!

Watch the full argument here or read it below.

Every week brings new claims about AI advances. How do we know what’s coming next? Could AI predict crime? Write award-winning novels? Hack into critical infrastructure? Will we finally have robots in our home that will fold our clothes and load our dishwashers?

What will AI advances mean for your job? What will it mean for the social fabric? It’s hard to deal with all this uncertainty. If only we had a way to predict which new AI capabilities will be developed soon and which ones will remain hard for the foreseeable future.

Historically, AI researchers’ predictions about progress in AI abilities have been pretty bad. We don’t really have principles that describe which kinds of tasks are easy for AI and which ones are hard.

Well, we have one — Moravec’s paradox. It refers to the observation that it’s easy to train computers to do things that people find hard, like math and logic, and hard to train them to do things that we find easy, like seeing the world or walking.

It comes ...