In your field, my perception is that there's this sort of bifurcation between these optimists and maybe you call them realists or pessimists. I think most people in AI would agree that we're pretty far from what we might call human level AI, but disagree on what that actually is. And also disagree on what should the field be aiming towards? Should it be aiming towards some general AGI, artificial general intelligence, or should it be focusing more on the kinds of narrow AI we have now?
Computer Scientist and author Melanie Mitchell of Portland State University and the Santa Fe Institute talks about her book Artificial Intelligence with EconTalk host Russ Roberts. Mitchell explains where we are today in the world of artificial intelligence (AI) and where we might be going. Despite the hype and excitement surrounding AI, Mitchell argues that much of what is called "learning" and "intelligence" when done by machines is not analogous to human capabilities. The capabilities of machines are highly limited to explicit, narrow tasks with little transfer to similar but different challenges. Along the way, Mitchell explains some of the techniques used in AI and how progress has been made in many areas.