I think this is easier to see if we move away from the AI Safety space. Would it be appropriate for 80,000 Hours job board advertise an Environmental Manager job from British Petroleum?
That doesn’t seem obviously absurd to me, at least.
I dislike when conversations about that are really about one topic get muddied by discussion about an analogy. For the sake of clarity, I’ll use italics relate statements when talking about the AI safety jobs at capabilities companies.
Interesting perspective. At least one other person also had a problem with that statement, so it is probably worth me expanding.
Assume, for the sake of the argument, that the Environmental Manager’s job is to assist with clean-ups after disasters, monitoring for excessive emissions and preventing environmental damage. In a vacuum these are all wonderful, somewhat-EA aligned tasks. Similarly the safety focused role, in a vacuum, is mitigating concrete harms from prosaic systems and, in the future, may be directly mitigating existential risk.
However, when we zoom out and look at these jobs in the context of the larger organisations goals, things are less obviously clear. The good you do helps fuel a machine whose overall goals are harmful.
The good that you do is profitable for the company that hires you. This isn’t always a bad thing, but by allowing BP to operate in a more environmentally friendly manner you improve BP’s public relations and help to soften or reduce regulation BP faces. Making contemporary AI systems safer, reducing harm in the short term, potentially reduces the regulatory hurdles that these companies face. It is harder to push restrictive legislation governing the operation of AI capabilities companies if they have good PR.
More explicitly, the short-term, environmental management that you do on may hide more long-term, disastrous damage. Programs to protect workers and locals from toxic chemical exposure around an exploration site help keep the overall business viable. While the techniques you develop shield the local environment from direct harm, you are not shielding the globe from the harmful impact of pollution. Alignment and safety research at capabilities companies focuses on today’s models, which are not generally intelligent. You are forced to assume that the techniques you develop will extend to systems that are generally intelligent, deployed in the real world and capable of being an existential threat. Meanwhile the techniques used to align contemporary systems absolutely improve their economic viability and indirectly mean more money is funnelled towards AGI research.
Yep. I agree with all of that. Which is to say that that there are considerations in both directions, and it isn’t obvious which ones dominate, in both the AI and petroleum case. My overall guess is that in both cases it isn’t a good policy to recommend roles like these, but don’t think that either case is particularly more of a slam dunk than the other. So referencing the oil case doesn’t make the AI one particularly more clear to me.
That doesn’t seem obviously absurd to me, at least.
I dislike when conversations about that are really about one topic get muddied by discussion about an analogy. For the sake of clarity, I’ll use italics relate statements when talking about the AI safety jobs at capabilities companies.
Interesting perspective. At least one other person also had a problem with that statement, so it is probably worth me expanding.
Assume, for the sake of the argument, that the Environmental Manager’s job is to assist with clean-ups after disasters, monitoring for excessive emissions and preventing environmental damage. In a vacuum these are all wonderful, somewhat-EA aligned tasks.
Similarly the safety focused role, in a vacuum, is mitigating concrete harms from prosaic systems and, in the future, may be directly mitigating existential risk.
However, when we zoom out and look at these jobs in the context of the larger organisations goals, things are less obviously clear. The good you do helps fuel a machine whose overall goals are harmful.
The good that you do is profitable for the company that hires you. This isn’t always a bad thing, but by allowing BP to operate in a more environmentally friendly manner you improve BP’s public relations and help to soften or reduce regulation BP faces.
Making contemporary AI systems safer, reducing harm in the short term, potentially reduces the regulatory hurdles that these companies face. It is harder to push restrictive legislation governing the operation of AI capabilities companies if they have good PR.
More explicitly, the short-term, environmental management that you do on may hide more long-term, disastrous damage. Programs to protect workers and locals from toxic chemical exposure around an exploration site help keep the overall business viable. While the techniques you develop shield the local environment from direct harm, you are not shielding the globe from the harmful impact of pollution.
Alignment and safety research at capabilities companies focuses on today’s models, which are not generally intelligent. You are forced to assume that the techniques you develop will extend to systems that are generally intelligent, deployed in the real world and capable of being an existential threat.
Meanwhile the techniques used to align contemporary systems absolutely improve their economic viability and indirectly mean more money is funnelled towards AGI research.
Yep. I agree with all of that. Which is to say that that there are considerations in both directions, and it isn’t obvious which ones dominate, in both the AI and petroleum case. My overall guess is that in both cases it isn’t a good policy to recommend roles like these, but don’t think that either case is particularly more of a slam dunk than the other. So referencing the oil case doesn’t make the AI one particularly more clear to me.