(Writing out this post has helped me answer the question for myself, but I still want to post it to see other thoughts).
I have been hesitant to get into AI safety research. Then I watched Robert Miles's video that walked through Stuart Russell's 10 reasons for not working on AI safety. The point of the video (and the point of Stuart Russell making the list) was to argue against all 10 reasons. The arguments against the 10 reasons convinced me to pay more attention and potentially pursue AI safety as a career path.
However, there is one "reason" that I don't think was covered. My concern is that "working on AI safety" might just mean "working on AI." The process of pursuing Safe AI might just advance the field enough to the point that it creates Dangerous AI. The safety researchers might discover something that gets twisted by bad faith actors/researchers/engineers.
My question is: are there any papers/videos/blogs that discuss this concern in more detail?
(My best counter-argument to my own concern is an unrefined analogy that I could probably improve: ignoring AI safety because "doing AI safety work might lead to something bad" is kind of like ignoring going to the hospital because something worse could technically happen to you on the car ride there.)
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.