If everyone who wants to make sure GAI is safe abstains from working on it, that guarantees that one of the following will happen:
GAI is invented by people who were not thinking about its safety.
GAI is never invented at all.
In order for the second possibility to be true, there must be something fundamental to GAI that safety researchers could discover but the thousands of other researchers with billions of dollars in funding will never discover on their own.
I’d like to add that I think there are ways in which safety work gets done without people working on ‘AI safety’. This isn’t in conflict with what you said, but it does mean that people who want to work on safety could not go on to work on it but there are still people doing the jobs of AI safety researchers.
It seems plausible to me that a person could end up working on AI and economic incentives push them to work on a topic related to safety (e.g. google want to build TAI → they want to understand what is going on in their deep neural nets better → they get some ai researcher to work on interpretability → [AI becomes a bit interpretable and possibly more safe]). I guess that in this case, the people may not be thinking about safety but if they are doing the jobs of the people that would then I don’t think it really matters.
I do think that people should work on AI safety on net, but this seems like a reasonable counterargument.
This answer clarified in my mind what I was poorly trying to grasp at with my analogy. Thank you. I think the answer to my original question is a certain “no” at this point.
Yeah, I haven’t thought about this question previously and am not very familiar with AI safety research/debates (even though I occasionally skim stuff), but one objection that came to my mind when reading the original post/question was “If you aren’t working on it, does that actually mean there will be one whole less person working on it?” Of course, I suppose it’s possible that AI safety is somewhat weird/niche enough (in comparison to e.g., nursing, teaching) where the person-replacement ratio is moderate or low and/or the relative marginal returns of an additional worker are still fairly high, e.g., your individual choice to get a job in AI safety may have the expected average effect of increasing the total amount of people working on the project by, say, 0.75. I don’t have the field knowledge to answer that question, and it’s only one of many factors to consider, but if it is the case that the replaceability ratio is relatively high (e.g., your net average effect is <0.25) then that immediately has a big reduction on the potential for “I am increasing the number of people working on AI which increases the likelihood of bad AI occurring.”
That being said, I’m confident there are much better counterarguments that draw on more knowledge of how working on AI safety can reduce the risk you are talking about without also contributing to this blob concept of “more people working on AI” which you worry could increase the likelihood of AGI, which increases the likelihood of bad AGI.
If everyone who wants to make sure GAI is safe abstains from working on it, that guarantees that one of the following will happen:
GAI is invented by people who were not thinking about its safety.
GAI is never invented at all.
In order for the second possibility to be true, there must be something fundamental to GAI that safety researchers could discover but the thousands of other researchers with billions of dollars in funding will never discover on their own.
I’d like to add that I think there are ways in which safety work gets done without people working on ‘AI safety’. This isn’t in conflict with what you said, but it does mean that people who want to work on safety could not go on to work on it but there are still people doing the jobs of AI safety researchers.
It seems plausible to me that a person could end up working on AI and economic incentives push them to work on a topic related to safety (e.g. google want to build TAI → they want to understand what is going on in their deep neural nets better → they get some ai researcher to work on interpretability → [AI becomes a bit interpretable and possibly more safe]). I guess that in this case, the people may not be thinking about safety but if they are doing the jobs of the people that would then I don’t think it really matters.
I do think that people should work on AI safety on net, but this seems like a reasonable counterargument.
This answer clarified in my mind what I was poorly trying to grasp at with my analogy. Thank you. I think the answer to my original question is a certain “no” at this point.
Yeah, I haven’t thought about this question previously and am not very familiar with AI safety research/debates (even though I occasionally skim stuff), but one objection that came to my mind when reading the original post/question was “If you aren’t working on it, does that actually mean there will be one whole less person working on it?” Of course, I suppose it’s possible that AI safety is somewhat weird/niche enough (in comparison to e.g., nursing, teaching) where the person-replacement ratio is moderate or low and/or the relative marginal returns of an additional worker are still fairly high, e.g., your individual choice to get a job in AI safety may have the expected average effect of increasing the total amount of people working on the project by, say, 0.75. I don’t have the field knowledge to answer that question, and it’s only one of many factors to consider, but if it is the case that the replaceability ratio is relatively high (e.g., your net average effect is <0.25) then that immediately has a big reduction on the potential for “I am increasing the number of people working on AI which increases the likelihood of bad AI occurring.”
That being said, I’m confident there are much better counterarguments that draw on more knowledge of how working on AI safety can reduce the risk you are talking about without also contributing to this blob concept of “more people working on AI” which you worry could increase the likelihood of AGI, which increases the likelihood of bad AGI.