Peter Drotos 🔸
Bio
Participation7
Working on computer chips driven by a childhood passion and donating the majority of my income. Recently transitioned to work on Compute Governance full-time.
Was seeking a community of people trying to optimize their impact and made the above decisions after engaging with EA core ideas.
Posts 3
Comments40
I think location constraints (either visa or personal) should be an important factor for career choice. 80k recommends moving to a hub in general, but I think the importance varies across career paths. As a starting point, I'd try to factor such constraints into my exploration priority list. I.e., if I'm roughly equally excited about two paths overall and one fits my location constraints much better, then explore that path first.
I would definitely advise against doing a medical degree, just to then become an engineer in the US. I think it's not realistic to keep your motivation level sufficiently high.
However, it seems it's difficult to make impact to reducing AI risks outside of the USA/UK. All of the frontier AI companies and EA organzations(like CLR, MIRI) are mostly in the USA(or the UK), and it's hard to get a remote job opportunity.
Frontier companies are highly competitive; they can afford not to bother with remote working. For EA/AIS, I think most entry roles are similarly highly competitive, and for some roles, it's simply mandatory to be close to Tech/Policy hubs. But there are also some remote-first organizations, mostly ones that require scarce experienced profiles.
I think it's important to distinguish between the following two theories of change categories:
- Doing important work that not enough people want to do
- Doing important work differently from how others would do it
For #1, if the nature of the work itself does not require in-person presence, and there are no remote options, then maybe the current supply/demand gap is not as big as you originally thought, so the expected counterfactual impact might also be much lower. For #2, there is no such gap by definition, and filtering applicants for in-person presence is very likely.
Maybe we need to flip this around. Instead of tracking how much funding was allocated to a certain cause area, we should be tracking the expected marginal opportunity in each and comparing those. I.e., what was the expected result of a marginal $1M donated to each cause area on average in, say, a given year?
This does not incentivize for making the allocations secret since the decisions are made based on the current state of the "market" irrespective of any previous allocations.
Going back to the 100 fund managers example, I think I'd much prefer them to individually recognize that people preferring the alternative allocation are just as competent in the decision as they are (in an ideal case), and as a result, apply the uncertainty to their own preference (making it 75-25 instead of 100-0/50-50) rather than relying on an external mechanism.
I think Patient philanthropy and Career capital are valid reasons (not sure about backfire risks).
I'd also highlight that the claim "funding is not the main bottleneck" does not imply that more funding is useless.
And importantly, I think another key part of the 80k advice is to find something you are really good at. So I think the career path priority list should be treated as a starting point that you should first adjust to your own strengths and interests, and then explore through experiments. Start with cheap tests and don't dismiss a great opportunity that is a few items below in the priority list.
If you are considering being a dentist (over alternative EtG paths), then you may already have signals that suggest you'd do well as a dentist. If that's the case, then I think you should also consider Biorisk as a career path. (Starting with reading about it / talking to people who think it's an important problem, if you have not done this already).
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I think it's fair to say that entry into AI/ML is difficult. I just checked recently if 80k themselves acknowledge this, and they do!
Cons
- Due to a shortage of managers, it’s difficult to get jobs and might take you some time to build the required career capital and expertise
- ...
Also adding Rethink Priorities' pilot of personalized donation advice (signup form here) that I found in their 2025 Results, 2026 Plans and Funding Needs document (shared also on their website and in an EA forum post).
I've had a call with them this week, and they are working on establishing support for cause-neutral individual donors. I'd recommend reaching out to them if you are interested.
I’d push back on this. Maybe the career choice (decision to do the job at the given market rate instead of doing something else) of N employees on the market allows achieving the current total production at $2X total cost instead of, say $3X, if it was fully up to the market. (The decisions shifting the supply curve upwards so the market can buy more production at a given price)
In that case, the total funding required is $X less, so on average $X/N for each impact focused employee. For comparison, if the market consists of, say, another N impact agnostic employees (2N employees total), then the individual market rate salary was also $X/N. (Average funding need reduction comparable to the market salary.)
Now, the above numbers are obviously arbitrary, but I think this illustrates the effect that I (we?) hope to have from direct work.