Dawn Drescher

Karma: 2,636

There are critical gaps in the accessibility and affordability of mental health services worldwide: In some countries, you have to wait for years for therapy, in others you get at max one session per month covered by the health insurance, in others therapies for particular conditions like cluster B personality disorders are virtually nonexistent.

We want to leverage LLMs to fill these gaps and complement regular therapy. Our product is in development. We’ve based it on Gemini and want it to interface with widely used messaging apps, so users can interact with it like they would with a friend or coach.

I’ve previously founded or worked for several charities and spent a few years in earning to give for work on invertebrate welfare and s-risks from AI.

You can get up to speed on my thinking at Impartial Priorities.

Welfare Biology and AI: Soil and Sea

Dawn Drescher29 Apr 2026 20:49 UTC

20 points

0 comments11 min readEA link

(impartial-priorities.org)

Dawn Drescher 24 Apr 2026 18:42 UTC
4 points
0 ∶ 0
in reply to: Vasco Grilo🔸’s comment on: Welfare Biology and AI: The Quiz
Thanks! Yes, small invertebrates have been on my mind ever since Brian Tomasik wrote about them 10+ years ago and cautioned against walking on grass. I’m sort of reducitarian about grass… I’ve also donated to the “inverts” project of RP! It’s a cause area I’m quite excited about, though I’m not sure whether I’m more excited about helping arthropods or nematodes.
Your updated estimates have huge credible intervals! What is the main source of the uncertainty in the model, or the main sources?
I’ll compress some of my summaries of your articles to remove the older numbers and clarify your updated views in the second article by quoting from the comment. Ty!
The 90k (or 90.3k) figure is based on this sentence from this article:
Nonetheless, I calculate GiveWell’s top charities increase the welfare of soil animals 90.3 k times as much as they increase the welfare of humans, which is a way higher ratio than the ones I just mentioned.
I’ll avoid citing the precise number.

Welfare Biology and AI: The Quiz

Dawn Drescher24 Apr 2026 11:57 UTC

19 points

3 comments8 min readEA link

(impartial-priorities.org)

Dawn Drescher 13 Jan 2026 12:42 UTC
2 points
0 ∶ 0
in reply to: Özge ’s comment on: Seeking Feedback: An Initiative on AI, Mental Health, and Alignment
Thank you so much! It was great meeting you in the call too!
(Someone developed a benchmark for harmful AI behaviors. In particular the Delusion Confirmation Score, Harm Enablement Score, and Safety Intervention Score. So they can compare models on these dimensions.)

AI Mental Health Chatbots for Low-Resource Settings: A Prioritization Framework

Dawn Drescher1 Dec 2025 17:41 UTC

10 points

0 comments16 min readEA link

Dawn Drescher 25 Oct 2025 18:21 UTC
3 points
1 ∶ 0
on: Retroactive Funding for Alignment
[Same as what I replied to your DM:] Yeah, exactly! Systems like that were on my mind a lot around 2021–23 when we launched Impact Markets, which is now GiveWiki. You could do the payouts if humanity has survived for another year, has survived AGI, has survived a year with AGI, etc. You could also chain retrofunders with different time horizons. We tried to get something like this off the ground for about 2 years, but couldn’t find any retrofunders anymore after FTX collapsed. (Some of the regrantors were interested.)

https://impactmarkets.substack.com/p/chaining-retroactive-funders

If you can find a retrofunder for a system like that, you can make it happen!

Dawn Drescher 1 Oct 2025 14:57 UTC
2 points
1 ∶ 0
in reply to: John Salter’s comment on: Seeking Feedback: An Initiative on AI, Mental Health, and Alignment
Hiii! Thanks! I’m only speaking for myself here, and I’m mostly interested in #3, or specifically in building, testing, and rolling out an AI-based tool for this rather than an RCT.
2. Consider the challenges of distribution and funding.
Yeah, working directly with the likes of Google (Gemini) and others would be swag, but correct me if I’m wrong, I see a very low chance of that working out? There is little commercial incentive in it for them, it doesn’t help them gain more market share from their competitors because our target clients can’t pay much, reputational risks similar to self-driving cars, etc. I haven’t asked anyone who works there, but I’m not sufficiently optimistic that it could work out to attempt it… Besides, if it does work out and lots of people start using Gemini for therapy, and then Google redecides and closes that department again, lots of users will use new version of a product for a purpose for which it’s not tested or optimized anymore.
But I already built an alpha version of an app for mentalization-based treatment on top of Gemini. That’s super easy, and I’ll permanently have control over the instructions and possibly the fine-tuning. If it should turn out to be too risky, I can shut it down, or more likely I can make adjustments to minimize any new risks.
Do you think I overestimate the difficulty of working with the model providers?
4. Doing too many things
The topics can probably be trimmed down a bit, but I feel like #1–3 form a nice story line where we first assess the risks, the assess the opportunities, and then exploit them? Personally, I’d rather ⁸⁰⁄₂₀ all of that by rolling out my solution only to fairly stable people first (I’m in some relevant support groups), collect feedback, poll well-being measures from time to time, and react to any problems with safety (in the feedback) or lacking effectiveness (well-being measures) along the way, while I increasingly market it to wider audiences. The others might want to take this more slowly, and as a result they’ll probably have the better data, but when that data is in, I can still optimize my tool accordingly.
Do you think it would really be better to focus on one topic only or would you agree that merging and 80/20ing is the better approach?

Seeking Feedback: An Initiative on AI, Mental Health, and Alignment

Gina Hafez30 Sep 2025 16:14 UTC

16 points

6 comments6 min readEA link

Dawn Drescher 20 Aug 2025 8:55 UTC
2 points
0 ∶ 0
in reply to: tobycrisford 🔸’s comment on: Beyond Control: The Strategic Case for AI Rights
They model that, and after, I think, 1661 iterations of the human-AI trade game, the human-AI trade game accumulates enough wealth for humans that it would’ve been self-defeating for the humans to defect like that. I think it’s still a Nash equilibrium but one where the humans give up perfectly good gains from trade. (Plus blockchain tech can make it hard to confiscate property.)

Beyond Control: The Strategic Case for AI Rights

Dawn Drescher12 Aug 2025 14:06 UTC

8 points

3 comments3 min readEA link

(impartial-priorities.org)

Dawn Drescher 11 Aug 2025 9:13 UTC
8 points
0 ∶ 0
in reply to: Larks’s comment on: How to Donate to Alleviate Suffering in Gaza
Thanks for the summary!

Dawn Drescher 10 Aug 2025 20:00 UTC
2 points
0 ∶ 0
in reply to: Larks’s comment on: How to Donate to Alleviate Suffering in Gaza
by promoting revanchism and ethnic hatred
Hiii! Do you know someplace where I can read up on that? Ty!

How to Donate to Alleviate Suffering in Gaza

Dawn Drescher10 Aug 2025 18:43 UTC

−23 points

14 comments4 min readEA link

(impartial-priorities.org)

Breaking the Cycle of Trauma and Tyranny: How Psychological Wounds Shape History

Dawn Drescher10 Aug 2025 8:46 UTC

8 points

1 comment12 min readEA link

(impartial-priorities.org)

With the Future of the World in Your Hands, Think for 6.77 Years!

Dawn Drescher9 Aug 2025 10:46 UTC

30 points

1 comment10 min readEA link

(impartial-priorities.org)

Dawn Drescher 7 Aug 2025 18:28 UTC
2 points
0 ∶ 0
in reply to: Felix Wolf 🔸’s comment on: EA Summer Camp 2025
Oops, already subscribed. xD I’ll try to pay more attention! Ty!

Dawn Drescher 7 Aug 2025 11:19 UTC
2 points
0 ∶ 0
on: EA Summer Camp 2025
Just learned about it! Do you have a newsletter or something so I can try to be quicker next year? I’ll be in Berlin around that time in case someone wants to meet up before or after!

Dawn Drescher 21 Jul 2025 20:42 UTC
4 points
0 ∶ 0
on: The standard case for delaying AI appears to rest on non-utilitarian assumptions
What has been your personal take-away from this line of thinking? This “standard case” is far from my own thinking, though I agree with the conclusion. Is it also far from your own thinking?
My take:
1. My axiology depends on unknown empirical results from further research into such things as Evidential Cooperation in Large Worlds, but at first approximation I’m skeptical that anything that runs counter to widely shared goals (or convergent drives, e.g., self-preservation) can be particularly good.
2. I endorse antisubstratism and AI rights.
3. I value reducing suffering very highly because I think that suffering is frequently very intense.
4. Bio-humans will have an extremely hard time surviving and reproducing in space or on other planets in our solar system and will have an extremely hard time reaching other solar systems.
5. The Long Reflection is necessary but impossible.
6. They key feature of a being that risks that it can experience suffering is reinforcement learning. Perhaps negative reinforcement can feel very mild or just like the absence of positive reinforcement, but perhaps it’s intense.
So what I’m afraid will happen is that an artificial RL agent will seek out resources first elsewhere in our solar system and then elsewhere in the galaxy (something that would be difficult for bio-humans), will run into communication delays due to the lightspeed limit, and will hence split into countless copies, each potentially capable of suffering. Soon they’ll be separated so far that even updates on what it means to be value-aligned would travel for a long time, so there’ll be moral “drift” in countless directions.
What I would find reassuring is:
1. Making sure AIs want to minimize the risk of suffering of other AIs, or at least near copies.
2. Research into how we can measure and minimize the suffering in RL (at least to the point where it’s mild and the pleasure dominates) and some way of applying that research broadly. Sadly it seems questionable to me that a low-suffering training regime is the most efficient training regime.
3. Faster-than-light communication but not transportation so the agent can remain monolithic.
4. Very energy efficient AIs, because they’ll face a tradeoff between staying monolithic to avoid value drift but only being able to harvest energy sources in our solar system or even just from the sun vs. the opposite. And the more they can do with little energy, the longer they’ll stay in our solar system, which might buy us and them time.
5. More time to get anyone interested in these things, research them, and apply them on a global scale before the lightspeed limits make it hard to disseminate the information.
Human extinction also seems bad on the basis that it contradicts the self-preservation drive that many/most humans have. Peaceful disenfranchisement may be less concerning depending on the details. But at the moment it seems random where we’re headed in the coming years because hardly anyone in power is trying to steer these things in any sensible way. Again more time would be helpful.
Basic rights for AIs (and standing in court!) could also provide them with a legal recourse where they currently have to resort to threats, making the transition more likely to go smoothly, like you argue in another post. Currently we’re nowhere close to having those. Again more time would be helpful.

Dawn Drescher 8 Dec 2024 18:33 UTC
2 points
0 ∶ 0
on: Donation Election Discussion Thread
I used the comment field in the form to note that a field in the form was marked as optional when it was actually mandatory. That comment got automatically published here, and out of context it made no sense whatsoever. I think it would’ve been clearer to not automatically transfer this form feedback here (some people might’ve even assumed that it’s private feedback).

Dawn Drescher 31 Oct 2024 16:15 UTC
7 points
0 ∶ 0
on: EA is bad for mental health (and I’m tired of pretending it’s not)
Thanks for writing all of this up in one place!
One of my gripes with the community has long been that maximization is core to EA and we’re still really clueless about what it implies and most of the community (outside RP, QURI, etc. and some researchers) seems to have given up on figuring it out.
I feel like we’re like this one computer science professor I had who seemed a bit senile and only taught the sort of things that haven’t lost relevance in the last 30 years because he hadn’t kept up with anything that happened since the 80s. He probably had good personal and neurological reasons for that, but we don’t, right?
I haven’t read any EA introductory materials in a few years, but I hope they contain articles about expected value maximization along with articles on how EV is usually largely unknowable due to cluelessness and often undefined due to Pasadena games. That stochastic dominance is arguably a much better approach to prioritization but that Christian Tarsney is so far more or less the only one who has bothered to look into it. That there is perhaps a way forward to figure out what’s the best thing to do if we funded some big world-modeling efforts based on software like Squiggle but that hardly anyone outside RP and QURI (and Convergence?) currently bothers to do anything about it. (I’ve dabbled a bit in these fields but my personal fit doesn’t seem to be great.)
Maybe there’s even a way to scalably adjust for personal fit whatever recommendations this big model effort might yield. Maybe there are some common archetypes/personas plus quizzes that tell people which ones they are closest to.
Arguably this can wait until this whole AI thing is under control (if that’s even possible), but few people will want to work on AI safety, so maybe it doesn’t have to wait?
My takeaway has been mostly that I don’t have a clue and so will go with some sort of momentary best guess gives me enough fulfillment, enjoyment, and safety. I’ve written more about it here.
That said, EA has had a great effect on my mental health.
I used to be a crying wreck because of all the suffering in the world. I spread myself thin trying to help everyone. I felt guilty about the majority of terrible things in the world that I was powerless to prevent. (Suicidal too, except that would’ve been self-defeating.)
Then EA came along and gave me an excuse to “pick my battles,” i.e. focus on a few things where I could make a big difference, taking into account my skills and temperament. Now, if someone went, “Hey, you should become a politician to prevent X and Y,” I could go, “No, I wouldn’t be good at that and hate every second of it and it would come at a great cost to A, which I’m already doing.” EA, for the first time, allowed me to set boundaries.
EA also gave me an appreciation for the (perhaps, plausibly, who knows really) great absolute impact that I can have despite the minimal impact that I have (perhaps, plausibly, who knows really) relative to the totality of the suffering in the world. That made it much easier to find fulfillment.