How do I tell whether a small group doing secret research will be better or worse at saving the world than the global science/military complex? Does anyone have strong arguments either way?
I haven't heard of any justification for why it might only take "nine people and a brain in a box in a basement". I think some people are too convinced of the AIXI approximation route and therefore believe that it is just a math problem that only takes some thinking and one or two deep insights.
Every success in AI so far relied on a huge team. IBM Watson, Siri, Big Dog or the various self-driving cars:
1)
With Siri, Apple is using the results of over 40 years of research funded by DARPA via SRI International's Artificial Intelligence Center through the Personalized Assistant that Learns Program and Cognitive Agent that Learns and Organizes Program CALO.
When a question is put to Watson, more than 100 algorithms analyze the question in different ways, and find many different plausible answers–all at the same time. Yet another set of algorithms ranks the answers and gives them a score. For each possible answer, Watson finds evidence that may support or refute that answer. So for each of hundreds of possible answers it finds hundreds of bits of evidence and then with hundreds of algorithms scores the degree to which the evidence supports the answer. The answer with the best evidence assessment will earn the most confidence. The highest-ranking answer becomes the answer. However, during a Jeopardy! game, if the highest-ranking possible answer isn’t rated high enough to give Watson enough confidence, Watson decides not to buzz in and risk losing money if it’s wrong. The Watson computer does all of this in about three seconds.
It takes a company like IBM to design such a narrow AI. More than 100 algorithms. Could it have been done without a lot of computational and intellectual resources?
The basement approach seems ridiculous given the above.
IBM Watson started in a rather small team (2-3 people); IBM started dumping resources on them once they saw serious potential.
Stuart Armstrong paraphrasing a typical AI researcher
I forgot to mention in my last post why "AI risk" might be a bad phrase even to denote the problem of UFAI. It brings to mind analogies like physics catastrophes or astronomical disasters, and lets AI researchers think that their work is ok as long as they have little chance of immediately destroying Earth. But the real problem we face is how to build or become a superintelligence that shares our values, and given that this seems very difficult, any progress that doesn't contribute to the solution but brings forward the date by which we must solve it (or be stuck with something very suboptimal even if it doesn't kill us), is bad. The word "risk" connotes a small chance of something bad suddenly happening, but slow steady progress towards losing the future is just as worrisome.
The usual way of stating the problem also invites lots of debate that are largely beside the point (as far as determining how serious the problem is), like whether intelligence explosion is possible, or whether a superintelligence can have arbitrary goals, or how sure we are that a non-Friendly superintelligence will destroy human civilization. If someone wants to question the importance of facing this problem, they really instead need to argue that a superintelligence isn't possible (not even a modest one), or that the future will turn out to be close to the best possible just by everyone pushing forward their own research without any concern for the big picture, or perhaps that we really don't care very much about the far future and distant strangers and should pursue AI progress just for the immediate benefits.
(This is an expanded version of a previous comment.)