One open question in AI risk strategy is: Can we trust the world's elite decision-makers (hereafter "elites") to navigate the creation of human-level AI (and beyond) just fine, without the kinds of special efforts that e.g. Bostrom and Yudkowsky think are needed?
Some reasons for concern include:
Otherwise smart people say unreasonable things about AI safety.
Many people who believed AI was around the corner didn't take safety very seriously.
Elites have failed to navigate many important issues wisely (2008 financial crisis, climate change, Iraq War, etc.), for a variety of reasons.
AI may arrive rather suddenly, leaving little time for preparation.
But if you were trying to argue for hope, you might argue along these lines (presented for the sake of argument; I don't actually endorse this argument):
If AI is preceded by visible signals, elites are likely to take safety measures. Effective measures were taken to address asteroid risk. Large resources are devoted to mitigating climate change risks. Personal and tribal selfishness align with AI risk-reduction in a way they may not align on climate change. Availability of information is increasing over time.
AI is likely to be preceded by visible signals. Conceptual insights often take years of incremental tweaking. In vision, speech, games, compression, robotics, and other fields, performance curves are mostly smooth. "Human-level performance at X" benchmarks influence perceptions and should be more exhaustive and come more rapidly as AI approaches. Recursive self-improvement capabilities could be charted, and are likely to be AI-complete. If AI succeeds, it will likely succeed for reasons comprehensible by the AI researchers of the time.
Therefore, safety measures will likely be taken.
If safety measures are taken, then elites will navigate the creation of AI just fine. Corporate and government leaders can use simple heuristics (e.g. Nobel prizes) to access the upper end of expert opinion. AI designs with easily tailored tendency to act may be the easiest to build. The use of early AIs to solve AI safety problems creates an attractor for "safe, powerful AI." Arms races not insurmountable.
The basic structure of this 'argument for hope' is due to Carl Shulman, though he doesn't necessarily endorse the details. (Also, it's just a rough argument, and as stated is not deductively valid.)
Personally, I am not very comforted by this argument because:
Elites often fail to take effective action despite plenty of warning.
I think there's a >10% chance AI will not be preceded by visible signals.
I think the elites' safety measures will likely be insufficient.
Obviously, there's a lot more for me to spell out here, and some of it may be unclear. The reason I'm posting these thoughts in such a rough state is so that MIRI can get some help on our research into this question.
In particular, I'd like to know:
Which historical events are analogous to AI risk in some important ways? Possibilities include: nuclear weapons, climate change, recombinant DNA, nanotechnology, chloroflourocarbons, asteroids, cyberterrorism, Spanish flu, the 2008 financial crisis, and large wars.
What are some good resources (e.g. books) for investigating the relevance of these analogies to AI risk (for the purposes of illuminating elites' likely response to AI risk)?
What are some good studies on elites' decision-making abilities in general?
Has the increasing availability of information in the past century noticeably improved elite decision-making?
Several years ago, the theoretical physicist Geoffrey West decided to investigate whether Kleiber’s law applied to one of life’s largest creations: the superorganisms of human-built cities. Did the “metabolism” of urban life slow down as cities grew in size? Was there an underlying pattern to the growth and pace of life of metropolitan systems? Working out of the legendary Santa Fe Institute, where he served as president until 2009, West assembled an international team of researchers and advisers to collect data on dozens of cities around the world, measuring everything from crime to household electrical consumption, from new patents to gasoline sales. When they finally crunched the numbers, West and his team were delighted to discover that Kleiber’s negative quarter-power scaling governed the energy and transportation growth of city living. The number of gasoline stations, gasoline sales, road surface area, the length of electrical cables: all these factors follow the exact same power law that governs the speed with which energy is expended in biological organisms. If an elephant was just a scaled-up mouse, then, from an energy perspective, a city was just a scaled-up elephant.
But the most fascinating discovery in West’s research came from the data that didn’t turn out to obey Kleiber’s law. West and his team discovered another power law lurking in their immense database of urban statistics. Every datapoint that involved creativity and innovation — patents, R&D budgets, “supercreative” professions, inventors — also followed a quarter-power law, in a way that was every bit as predictable as Kleiber’s law. But there was one fundamental difference: the quarter-power law governing innovation was positive, not negative. A city that was ten times larger than its neighbor wasn’t ten times more innovative; it was seventeen times more innovative. A metropolis fifty times bigger than a town was 130 times more innovative.
One open question in AI risk strategy is: Can we trust the world's elite decision-makers (hereafter "elites") to navigate the creation of human-level AI (and beyond) just fine, without the kinds of special efforts that e.g. Bostrom and Yudkowsky think are needed?
Some reasons for concern include:
But if you were trying to argue for hope, you might argue along these lines (presented for the sake of argument; I don't actually endorse this argument):
The basic structure of this 'argument for hope' is due to Carl Shulman, though he doesn't necessarily endorse the details. (Also, it's just a rough argument, and as stated is not deductively valid.)
Personally, I am not very comforted by this argument because:
Obviously, there's a lot more for me to spell out here, and some of it may be unclear. The reason I'm posting these thoughts in such a rough state is so that MIRI can get some help on our research into this question.
In particular, I'd like to know: