What is the most likely explanation for that? It seems that we can narrow it to two hypotheses: A) MIRI's insight is really relevant and important to AI design, but communication with the experts failed because > of some problem on MIRI's side, or on the experts' side (e.g. stubbornness, stupidity) or both (e.g. excessively different backgrounds). B) MIRI is mistaken about the value of their insight (possible psychological causes may include confirmation bias, Dunning–Kruger effect, groupthink, overconfident personalities, etc.).
I don't believe these options are exhaustive. "Relevant and valuable" are subjective and time-varying. The published work might be interesting and useful down the line, but not help the problems that AI researchers are working on right now.
It usually takes a few years for the research community to assimilate strange new ideas -- sometimes much more than a few years. This isn't due to a failure on anybody's part -- it's due to the fact that scientists pick problems where they have a reasonable prospect of success within a few years.
I would give MIRI at least a decade or two before evaluating whether their work had any mainstream traction.
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.
Do you claim that MIRI is one or two decades ahead of mainstream researchers?
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?
Previously: Why Neglect Big Topics.
Why was there no serious philosophical discussion of normative uncertainty until 1989, given that all the necessary ideas and tools were present at the time of Jeremy Bentham?
Why did no professional philosopher analyze I.J. Good’s important “intelligence explosion” thesis (from 19591) until 2010?
Why was reflectively consistent probabilistic metamathematics not described until 2013, given that the ideas it builds on go back at least to the 1940s?
Why did it take until 2003 for professional philosophers to begin updating causal decision theory for the age of causal Bayes nets, and until 2013 to formulate a reliabilist metatheory of rationality?
By analogy to financial market efficiency, I like to say that “theoretical discovery is fairly inefficient.” That is: there are often large, unnecessary delays in theoretical discovery.
This shouldn’t surprise us. For one thing, there aren’t necessarily large personal rewards for making theoretical progress. But it does mean that those who do care about certain kinds of theoretical progress shouldn’t necessarily think that progress will be hard. There is often low-hanging fruit to be plucked by investigators who know where to look.
Where should we look for low-hanging fruit? I’d guess that theoretical progress may be relatively easy where:
These guesses make sense of the abundant low-hanging fruit in much of MIRI’s theoretical research, with the glaring exception of decision theory. Our September decision theory workshop revealed plenty of low-hanging fruit, but why should that be? Decision theory is widely applied in multi-agent systems, and in philosophy it’s clear that visible progress in decision theory is one way to “make a name” for oneself and advance one’s career. Tons of quality-adjusted researcher hours have been devoted to the problem. Yes, new theoretical advances (e.g. causal Bayes nets and program equilibrium) open up promising new angles of attack, but they don’t seem necessary to much of the low-hanging fruit discovered thus far. And progress in decision theory is definitely not valuable only to those with unusual views. What gives?
Anyway, three questions:
1 Good (1959) is the earliest statement of the intelligence explosion: “Once a machine is designed that is good enough… it can be put to work designing an even better machine. At this point an ”explosion“ will clearly occur; all the problems of science and technology will be handed over to machines and it will no longer be necessary for people to work. Whether this will lead to a Utopia or to the extermination of the human race will depend on how the problem is handled by the machines. The important thing will be to give them the aim of serving human beings.” The term itself, “intelligence explosion,” originates with Good (1965). Technically, artist and philosopher Stefan Themerson wrote a "philosophical analysis" of Good's intelligence explosion thesis called Special Branch, published in 1972, but by "philosophical analysis" I have in mind a more analytic, argumentative kind of philosophical analysis than is found in Themerson's literary Special Branch. ↩