Hi, I'm an 18 year old going into college in a week. I am studying Computer engineering and mathematics. Since I have a technical interest and AGI has a much higher probability ending humanity this century(1/10, I think) than other causes (that I would rather work on, like Biorisks is 1/10,000), would the utility positive thing to do be to force myself to get an ML alignment focused PhD and become a researcher?
I am at a mid-tier university. I think I could force myself to do AI alignment since I have a little interest, but not as much as the average EA. I wouldn't find as much engagement in it, but I also have an interest in starting a for-profit company, which couldn't happen with AGI alignment (most likely). I would rather work on a hardware/software combo for virus detection (Biorisks), climate change, products for 3rd world, other current problems, or other problems that will be found in the future.
Is it certain enough that AI alignment is so much more important that I should forgo what I think I will be good at/like to pursue it?
Edit: made some people confused that I had a false dichotomy between "pursuing my passion" and doing EA alignment. Removed that comment.
Why do you think you'd need to "force yourself?" More specifically, have you tested your fit for any sort of AI alignment research?
If not, I would start there! e.g., I have no CS background, am not STEM-y (was a Public Policy major), and told myself I wasn't the right kind of person to work on technical research ... But I felt like AI safety was important enough that I should give it a proper shot, so I spent some time coming up with ELK proposals, starting the AGISF curriculum, and thinking about open questions in the field. I ended up, surprisingly, feeling like I wasn't the most terrible fit for theoretical research!
If you're interested in testing your fit, here are some resources
I could possibly connect you to people who would be interested in testing their fit too, if that's of interest. In my experience, it's useful to have like-minded people supporting you!
Finally, +1 to what Kirsten is saying - my approach to career planning is very much, "treat it like a science experiment," which means that you should be exploring a lot of different hypotheses about what the most impactful (including personal fit etc.) path looks like for you.
edit: Here are also some scattered thoughts about other factors that you've mentioned: