I think it’s useful to ground these results by looking at another setting in which cultural and institutional norms put ambitious, intellectually selected young people into a similar context, which I think can be reasonable characterized as high-stakes, status-competitive, weak-boundary work environments.
Here are some comparisons GPT found to people in early-career academia:
Survey here
Early academia
Difficulty switching off from work
68%
78% ranked difficulty maintaining work–life balance among their top five concerns. 49% reported a long-hours culture at their university, explicitly including sometimes working through the night.[1]
Imposter syndrome
60%
42% experienced frequent imposter thoughts. More than 26% experiencing serious/intense imposter thoughts.[2]
39.3% reported anxiety-disorder symptoms.[4] A different study found 17% had clinically significant symptoms of anxiety.[5]
Hopelessness or depression
29%
26.5% depressive-disorder symptoms.[4] A different study found 24% had clinically significant symptoms of depression.[5]
Loneliness or isolation
32%
24% severely or very severely lonely (note this was collected during COVID).[6]
Considered cutting back or leaving
45%
51% considered leaving because of work-related mental health concerns.[4]
It seems worthwhile to me to question the premise that AI safety/x-risk work is unusually psychologically harmful. I’m not in the field, but I think there is a somewhat romantic story available here: that these problems arise because people are grappling with x-risk, carrying a moral burden, and working on something unusually consequential. That story is surely partly true, but it’s also flattering. Ingroup dynamics give us some reason to suspect that attributing distress to the exceptional significance of the work may be a motivated explanation, when a less glamorous one is that AI safety has reproduced a familiar high-pressure knowledge-work environment: long hours, poor boundaries, status competition, perfectionism, career uncertainty, people who are willing to sacrifice other parts of their lives to succeed.
The practical downside of viewing the problem as exceptional is that solutions become less available, need to be built bespoke. But if a large part of the variance is coming from more ordinary occupational dynamics, then a much larger institution (academia) has spent a long time running into the same failure modes and trying to intervene. There may be a helpful update here that upweights boring and well-established interventions.
I think it’s useful to ground these results by looking at another setting in which cultural and institutional norms put ambitious, intellectually selected young people into a similar context, which I think can be reasonable characterized as high-stakes, status-competitive, weak-boundary work environments.
Here are some comparisons GPT found to people in early-career academia:
It seems worthwhile to me to question the premise that AI safety/x-risk work is unusually psychologically harmful. I’m not in the field, but I think there is a somewhat romantic story available here: that these problems arise because people are grappling with x-risk, carrying a moral burden, and working on something unusually consequential. That story is surely partly true, but it’s also flattering. Ingroup dynamics give us some reason to suspect that attributing distress to the exceptional significance of the work may be a motivated explanation, when a less glamorous one is that AI safety has reproduced a familiar high-pressure knowledge-work environment: long hours, poor boundaries, status competition, perfectionism, career uncertainty, people who are willing to sacrifice other parts of their lives to succeed.
The practical downside of viewing the problem as exceptional is that solutions become less available, need to be built bespoke. But if a large part of the variance is coming from more ordinary occupational dynamics, then a much larger institution (academia) has spent a long time running into the same failure modes and trying to intervene. There may be a helpful update here that upweights boring and well-established interventions.
Nature's 2019 global survey of 6,320 PhD students
A study of 302 Australian PhD students. Also in there, Imposter thoughts predicted symptoms of depression, anxiety and suicidality.
A study of 62 master's and doctoral psychology students at a Canadian university.
Nature's international survey of 7,600 postdocs.
A meta-analysis of nine studies, 15,626 PhD students.
A study of 222 doctoral researchers in the Berlin area.