Haoxing Du

Epistemic status: Feeling frustrated, and therefore somewhat uncharitable. I’m very frustrated with calls for people to “drop everything and pivot into AI safety” like this one. (See also this, this, this, this for recent calls for more people to go into AI safety; though my frustration was triggered by the Celeste's post.) There are far more talented people trying to get into AI safety than there are jobs for them.[1] MLAB 2, which I did in 2022, was already competitive to get into, at about 5% acceptance rate (admitted about 40 out of 800 applicants). Things are much, much more competitive now. There is a whole pipeline of AI safety fellowships (and guides for applying to them). It is rumored that one recent cohort of the Anthropic Fellows program had over 10,000 applicants. (Anecdotally, I applied to the Anthropic Fellows program in early 2026, after working at Redwood, METR, and an ML startup, and I didn’t get in!) And, uh, just take a look at the AI safety jobs? The bottom of the salary range for METR’s current “Member of Technical Staff, Embedded Assessments” job posting is $402k. This is higher than the median total comp for Research Scientists ($310k) and Machine Learning Engineers ($282k). Plus these jobs are high status too. These are really good jobs and nobody needs to be convinced to want them. I think it’s Actually Bad to keep saying AI safety is talent-constrained. I think it really harms people to tell them they should drop what they’re doing to switch to AI safety when there isn’t a path for the vast majority of the people who do to thrive. These are good, talented people who just want to help, and they could be doing lots of other good things instead of putting themselves through the meatgrinder of applying to AI safety jobs. Finally, I worry that believing that the field is talent-constrained is holding us back as a field. If we believed that we just needed to wait for the right talent to come along, then we can stop looking elsewhere and fix