MIRI stated goals are similar to those of mainstream AI research, and MIRI approach in particular includes as subgoals the goals of research fields such as model checking and automated theorem proving.
Research has both ultimate goals (“machines that think”) and short-term goals (“machines that can parse spoken English”). My impression is that the MIRI agenda is relevant to the ultimate goal of AI research, but has only limited overlap with the things people are really working on in the short term. I haven’t seen MIRI work that looked directly relevant to existing work on theorem proving or model checking. (I don’t know much about automated theorem proving, but do know a bit about model checking.)
Do you claim that MIRI is one or two decades ahead of mainstream researchers?
It’s not a matter of “ahead”. Any research area is typically a bunch of separate tracks that proceed separately and eventually merge together or have interconnections. It might be several decades before the MIRI/self modifying AI track merges with the main line of AI or CS research. That’s not necessarily a sign anything is wrong. It took decades of improvement before formal verification or theorem proving become part of the computer science toolkit. I would consider MIRI a success if it follows a similar trajectory.
If the answer is no, then how does MIRI (or MIRI donors) evaluate now whether these lines of work are valuable towards advancing their stated goals?
I can’t imagine any really credible assurance that “this basic research is definitely useful,” for any basic research. The ultimate goal “safe self modifying AI” is too remote to have any idea if we’re on the right track. But if MIRI, motivated by that goal, does neat stuff, I think it’s a safe bet that (A) the people doing the work are clueful, and (B) their work was at least potentially useful in dealing with AI risks. And potentially useful is the best assurance anybody can ever give.
I’m a computer systems guy, not a theorist or AI researcher, but my opinion of MIRI has gradually shifted from “slightly crankish” to “there are some interesting questions here and MIRI might be doing useful work on them that nobody else is currently doing.” My impression is a number of mainstream computer scientists have similar views.
Eliezer recently gave a talk at MIT. If the audience threw food at the stage, I would consider that evidence for MIRI being crankish. If knowledgeable CS types showed up and were receptive or interested, I would consider that a strong vote of confidence. Anybody able to comment?
Research has both ultimate goals (“machines that think”) and short-term goals (“machines that can parse spoken English”). My impression is that the MIRI agenda is relevant to the ultimate goal of AI research, but has only limited overlap with the things people are really working on in the short term. I haven’t seen MIRI work that looked directly relevant to existing work on theorem proving or model checking. (I don’t know much about automated theorem proving, but do know a bit about model checking.)
It’s not a matter of “ahead”. Any research area is typically a bunch of separate tracks that proceed separately and eventually merge together or have interconnections. It might be several decades before the MIRI/self modifying AI track merges with the main line of AI or CS research. That’s not necessarily a sign anything is wrong. It took decades of improvement before formal verification or theorem proving become part of the computer science toolkit. I would consider MIRI a success if it follows a similar trajectory.
I can’t imagine any really credible assurance that “this basic research is definitely useful,” for any basic research. The ultimate goal “safe self modifying AI” is too remote to have any idea if we’re on the right track. But if MIRI, motivated by that goal, does neat stuff, I think it’s a safe bet that (A) the people doing the work are clueful, and (B) their work was at least potentially useful in dealing with AI risks. And potentially useful is the best assurance anybody can ever give.
I’m a computer systems guy, not a theorist or AI researcher, but my opinion of MIRI has gradually shifted from “slightly crankish” to “there are some interesting questions here and MIRI might be doing useful work on them that nobody else is currently doing.” My impression is a number of mainstream computer scientists have similar views.
Eliezer recently gave a talk at MIT. If the audience threw food at the stage, I would consider that evidence for MIRI being crankish. If knowledgeable CS types showed up and were receptive or interested, I would consider that a strong vote of confidence. Anybody able to comment?