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?
One question is whether AI is like CFCs, or like CO2, or like hacking.
With CFCs, the solution was simple: ban CFCs. The cost was relatively low, and the benefit relatively high.
With CO2, the solution is equally simple: cap and trade. It's just not politically palatable, because the problem is slower-moving, and the cost would be much, much greater (perhaps great enough to really mess up the world economy). So, we're left with the second-best solution: do nothing. People will die, but the economy will keep growing, which might balance that out, because a larger economy can feed more people and produce better technology.
With hacking, we know it's a problem and we are highly motivated to solve it, but we just don't know how. You can take every recommendation that Bruce Schneier makes, and still get hacked. The US military gets hacked. The Australian intelligence agency gets hacked. Swiss banks get hacked. And it doesn't seem to be getting better, even though we keep trying.
Banning AI research (once it becomes clear that RSI is possible) would have the same problem as banning CO2. And it might also have the same problems as hacking: how do you stop people from writing code?