As someone who hires people (I am hiring right now, see bottom of the post), I often get emails asking whether someone should apply for a role I've listed.
If you're considering contacting a hiring manager to ask if you're a good fit for the role, you should just apply.
Why?
Notable exceptions, where you should email:
To be clear, the urge to send an email to check if you should apply is totally normal (I have done it before), and anyone who has done this has nothing to worry about. However, I would strongly recommend applying despite your reservations. You can just do things!
Also, if you want to apply to become Access to Medicines Initiative's Head of Monitoring, Evaluation, and Data, JOB DESCRIPTION AND APPLICATION HERE: https://docs.google.com/document/d/1nqOz2a5bTQs5W361G5gpJ3brLEf6xuG0
After the initial experiment period, we've decided to keep the featured page.
One of the key graphs in making this decision is below:

Now that the featured page is likely to stick around long term, I'd like to start collecting ideas for V2[1]. Do you use the page? Do you pointedly not use the page? I'd love to get any and all feedback, in the comments here, or via this form.
Please share small things like aesthetic tweaks as well as larger issues such as a disagreement on the kind of posts that get featured, or how featuring is done. Happy to answer questions too.
I.e., the current version is a prototype, and I'm ready to do a full redesign if necessary. Because of some protracted OOO I might have to take soon - V2 might land near the end of September, or even early October.
You should judge others on a curve, and probably yourself as well.
Judging others on a curve means that folks see reward for doing more than what is typical. This is just good reinforcement-learning theory, since it is easy to get both feedback on rewarded & not-rewarded actions.
I started writing this thinking that you should NOT judge yourself on a curve, in contrast. IE, you know much more about your own circumstances, and so pretending you are average throws away info. For example, if I only gave 5% of my income to charity, that would be above average for the US. But my opportunities are amazing, and so 5% would in reality show low effort.
But actually, I was just using the wrong comparison group! I shouldn't compare myself to a big group of other people. I have a near perfect comparison group in my past self. If I did a better job this week than last week at work, that's a great sign! If my one-rep max for benchpress has gone down over the last month, that's a bad sign!
This all feels obvious in retrospect.
[central europe] We are organising the largest AI-safety march (at least in central europe) to date at Prague, starting at 15:00 on 31st August. We have got parlimentary support as well as very supportive police, allowing us to take the preffered route. We want as many people to come - fell free to spread information about the event outside EA as much as possible, especially if you have friends living near Prague who may come. If you want closer info/visual materials or help us with organisation, you can get in contact with czech PauseAI on whatsapp.
Luma event link
Thank you for writing this, Tom and Rocky. I think this is an important caution, and I appreciate the way you are framing it.
As someone directly involved in a welfare-tech-style intervention, I actually agree with much of your core argument. I also strongly believe that good tech interventions can be extremely impactful, partly for some of the reasons you outline: they can sometimes bypass certain barriers that exist for other welfare work, and they can make it possible to help very large numbers of animals relatively quickly. But I also agree that, when looked at from the outside, they can be falsely perceived as silver bullets, so I want to share three insights from SWP about electrical stunning for shrimp.
I’ve also posted a more direct response to “Animal Welfare Has an Evidence Problem,” which you refer to in the post, to clarify some of these points.
First, at SWP, our work on shrimp stunning has been much more complex than simply deploying stunners at scale. The Humane Slaughter Initiative does involve getting electrical stunning equipment used on farms, but in practice, we are doing much more than that: coordinating and funding welfare research and R&D, collecting field data, working with scientists, developing and refining slaughter protocols, iterating on the technology with existing equipment providers, negotiating with industry, engaging corporate stakeholders, building and maintaining producer relationships, training staff, educating farmers… Much of this work is not visible from the surface, but it’s central to making the intervention possible. The tech matters, but it does not operate in a vacuum.
Second, on shrimp stunning specifically, I think you captured something important. SWP entered this space aware that there were uncertainties, and we’ve been proactively trying to reduce them. Some of that work is public, but much of it happens through industry collaborations, field implementation, and producer relationships, which are often necessarily behind closed doors or covered by NDAs. That can make the work less visible from the outside, even though it is central to what we are doing.
This is one reason I think treating our intervention too simplistically, as merely putting stunners on farms, can lead to exactly the kind of disillusionment and backlash you describe.
Third, I feel some of the issues you describe are not limited to tech interventions. Many ambitious attempts to change existing systems seem to have an early phase where progress looks relatively fast, followed by a harder phase where problems become more complex, uncertainty can increase, coordination costs become bigger, and resistance from affected stakeholders becomes stronger. That does not necessarily mean the intervention – tech or otherwise – was a mistake; it can be a natural progression of an ambitious project.
Thanks again for writing this! It’s an important reminder that welfare tech can be genuinely promising and, in some cases, extremely impactful, but it should not be treated as a silver bullet.
I think that this diagnosis is basically on target; it points to something that seems relatively under-resourced, despite some focus by think tanks, and something that the major AIxBio safety groups are not as focused on. I also agree that we don't know if AGI will subsume this, and that it's plausible but uncertain if other bottlenecks matter more, but that's an uncertainty we can't resolve without simply waiting for the outcomes, and so this seems very high value in expectation.
I'm less certain about the object level questions, and don't have strong intuitions - so I think that conditional on not hearing from someone more informed about this that there are additional questions or concerns, or literature you should look at, the best way to figure out whether this is needed, and what the risk is, is to start the work - good luck, and I'd be happy to chat about this more!
Hi Amanda, I have a few points of clarification regarding the evidence on shrimp stunning and Shrimp Welfare Project’s Humane Slaughter Initiative.
We acknowledge it is true that academic peer-reviewed evidence is limited (although we’re excited to report that the Stirling study is no longer a pre-print and has been published in Aquaculture). That being said, our intervention is informed by more evidence than just the peer-reviewed literature. We (and, sometimes, the industry) have access to more evidence than what’s published or able to be communicated publicly.
It may be useful to clarify what we mean by “research” and “evidence-building” in this context. Beyond peer-reviewed studies, evidence-building for humane slaughter means reducing uncertainty across several linked questions, including: whether electrical stunning can quickly render shrimp insensible under controlled conditions; whether it works reliably during commercial harvests; what parameters, protocols, and equipment designs improve outcomes; whether producers are using stunners as intended; and how monitoring systems can make that implementation more verifiable over time.
In practice, that means the evidence base is built from multiple sources: lab studies, field observations, stunner data, producer feedback, behavioral indicators, equipment iteration, implementation protocols, and MEL systems. This is not a linear process where all the research happens first and implementation only begins later. Field implementation is part of the learning which often reveals the constraints, failure modes, and practical questions that the next round of research needs to answer.
Recently, The Center for Responsible Seafood (TCRS) published a summary of a study conducted by the University of Stirling[1]. In a field visit in April 2026, researchers compared electrical stunning and ice slurry on an Indian farm. An excerpt reads:
“In summary, to meet ethical and welfare concerns, shrimp benefit from rapid stunning immediately after harvest. Electric stunning provides a rapid and effective stun as shown by the lack of response to subsequent cold exposure, but the process triggers a strong muscle contraction and elevated blood lactate. Cold shock does not deliver an immediate stun.
The report found that, with ice slurry alone (referred to as cold shock or CS), “shrimp are highly likely to maintain neural sensibility during the CS stunning process,” and those animals “did incur an initial ca. 30 sec tail flip response (since they are not insensible).”
“Therefore,” the researchers wrote, “best practice would suggest that ES needs to be followed by CS (ES+CS protocol).”
For those unfamiliar with TCRS, it’s quite an industry-aligned organisation, so their study coming to this conclusion is noteworthy.
Through our Humane Slaughter Initiative, Shrimp Welfare Project’s team members have seen dozens of harvests using stunners, and we have collected thousands of photos and videos that have informed our intervention (e.g., which parameters work best in certain contexts, how the use of a pump/harvester could minimize time shrimps spent out of water, etc.). We can’t share most of that content publicly because our industry partners (and therefore, we) operate in a competitive market environment where confidentiality, trade secrets, and proprietary information are very important. We understand that many folks in the EA community would appreciate greater transparency, and we’re always trying to facilitate a productive exchange of knowledge about our work – hopefully, this comment will accomplish some of that.
To respond to some of your specific points:
In 2021, Tesco and Hilton Seafood published a report on their use of a modified Optimar stunner in Vietnam. … This gives some reassurance for this particular machine, although I know from talking to people in the field that this machine was a modified version of the commercially available one.
Shrimp Welfare Project has visited that farm and observed the stunner in operation, and it is an early (yet almost-standard) Optimar model. It's a fish stunner that had its electrified "fingers" (which, when they touch animals on an electrified conveyor, complete the electric current and produce the stunning shock) lowered to reach much smaller animals, rather than a completely bespoke modification that could have fundamentally changed the stunner's parameters or operation.
We've worked with Optimar to implement improvements over the years (we’re currently on version ~6), so the shrimp-specific finger-lowering adjustment is no longer a post-manufacturing modification, but a feature of the commercially-available standard model. Perhaps this is the source of the confusion?
Regardless, the important takeaway here is that the 2020 case study used a stunner that is representative of the kind of stunners we support via our HSI program at present, and it concluded that electrical stunning at the recommended parameters was able to “deliver >97% stunning efficacy,” and followed by “immediate immersion in ice slurry achieving 100%” efficacy.
Going into your next point about sample sizes, I wanted to note that this case study used 50kg samples per voltage tested. Since shrimps were 25-30g each at harvest, that’s ~1,700-2,000 animals per 50kg sample, though the report doesn’t state this explicitly. There were also 100 shrimps checked for stunning effectiveness at start-up.
[re: Weineck et al.] The study uses a very small sample size (N = 6 for each intervention) which makes me uncomfortable recommending any action based on it. … [re: Stirling study] This study is also small (N = 4-6 per intervention) which again leads me to have limited confidence in conclusions.
Many of the studies that involve animal testing like this use small sample sizes. In speaking with scientists who specialize in invertebrate biology, it’s understandable why these studies would be designed with small sample sizes. If the desired effect size is large for the variables tested (as is often the case here) and the standard deviation among individuals is only moderate (as is expected to be the case here), this is not necessarily a limitation. It’s statistically appropriate, and even often ethically mandated – by institutional standards and/or the Three R Principles of animal research. This is only to say: we should not have a knee-jerk response to sample size.
That said, we recognize that the actual findings are not a clean on/off, but rather a subtle, dose-dependent difference between responders and non-responders. Our confidence would increase if there were more animals tested to generate more data to support precise parameters for effective stunning. At the same time, the direction of the findings is still informative, especially as they converge with other evidence, including the TCRS study and our own field data.
Based on this data, it is unclear if electric shock followed by ice slurry provides any benefit over ice slurry alone, provided the animals are kept in ice slurry until they are fully dead. (It is unclear how long that would take, though.) … A sufficiently strong electrical shock with proper ice slurry (which is hard to implement in practice) does not provide much improvement over proper ice slurry alone.
I don’t think the Stirling paper supports this.
At 2.5–5 °C (which would be a high-performing slurry temperature by current commercial standards) cold shock was slow and unreliable as a route to neurological insensibility. Using the paper’s threshold of Ptot <10% of baseline brain activity, only 4 out of 5 shrimp reached this threshold, and this occurred after 28 minutes. One animal did not appear to reach the Ptot <10% threshold within the 30-minute observation period.
At −2.5 °C, all shrimp reached Ptot <10% within 4 minutes. However, achieving and maintaining a −2.5 °C slurry consistently during commercial harvests, especially in tropical climates and under high biomass loading, is likely to be extremely difficult. We are exploring this avenue, including deepchill-type technology, but at present we are only moderately optimistic about its practical feasibility. At the moment, maintaining these kinds of temperatures is far from “proper ice slurry,” and more appropriately understood as a rare exception in real-world production settings.
The best-supported approach in the paper is electrical stunning (ES) followed by cold shock (CS). In the effective ES + CS group, all animals that did not tail flip after cold exposure reached Ptot <10% after 3 minutes of cold shock. There’s limited research on the relationship between tail flipping and neural insensibility / loss of consciousness[2], so our confidence in this correlation would increase with more data. But it’s important to reiterate that, based on the best available knowledge from the Stirling lab (which they clearly state in the paper), absence of tail flipping after cold exposure is aligned with neurological insensibility[3].
Here is a video that shows shrimp in ice slurry – the first group has been electrically stunned, and the second group has not. The second clip shows a nearly ideal ice slurry in a production setting, with a temperature around 1 degree C. What you see in that video is consistent with what we’ve seen at shrimp farms around the world: that even when in a highly controlled ice slurry, shrimps flip their tails for multiple minutes.
Insufficient electrical stunning with proper ice slurry may be worse than ice slurry alone.
This would be true for basically all stunning methods, across land and aquatic animals. If a percussive stunning bolt is insufficiently administered to a cow’s head, then the slaughter process would be more painful than if a stunning method hadn’t been poorly attempted.
Electrical stunning without proper ice slurry slaughter poses real potential for causing harm.
A few things here:
Additionally, this line of reasoning would seem to contradict your argument in your post, that:
“Many shrimp harvests do not use ice slurry, or do not use it properly (not cold enough, not long enough, etc.).”
There’s a tension here worth flagging: on the one hand, your comparison of electrical stunning vs. ice slurry assumes an idealized version of “proper” ice slurry – cold enough, maintained long enough, carefully managed. But when it comes to what electrical stunning would look like in real-world harvest conditions, your concern raised is precisely that ice slurry is often not implemented properly. If poorly implemented ice slurry undermines the case for electrical stunning, then the same realism has to apply when ice slurry itself is proposed as the alternative. Either way, the fair comparison is between the two methods as they would actually be implemented – and in our view, that comparison favors electrical stunning followed by ice slurry as the kill method.
The science is clear that any stunning method can be reversible if it’s not followed by an adequate kill step. This is true for both electrical stunning as well as ice slurry that’s used for stunning. In the Humane Slaughter Initiative, our protocol calls for ice slurry as the kill step; importantly, we’re not using ice slurry as a stunning method, but rather a method to prevent the shrimps from recovering after the electric shock. We guide farm staff on how to do this ice slurry properly, including monitoring the temperature and replenishing the ice, etc. In our field experience, this process usually involves putting shrimps through the stunner, then directly into an ice bath for several minutes (as in this video and this video), and then into transport crates where they are packed with ice. In this slaughter method, the ice slurry prevents the shrimps from re-warming and recovering, rather than being the step that also stuns them.
Doing a well-implemented ice slurry for stunning is much harder to do effectively in practice than an ice slurry for prevention of recovery/slaughter after electrical stunning. So, although these practices share the same name, their different purposes and application create a major distinction. We are more confident in ice slurry as a slaughter and recovery prevention method after electrical stunning, than ice slurry as a stunning method itself.
Overall, the evidence base for shrimp stunning is still developing and Shrimp Welfare Project acknowledges this and is actively working to develop it further, both through our own fieldwork and by coordinating with researchers, manufacturers, producers, and other industry actors. Given the scale of the problem, we do not think the right response is to wait for full certainty, as it would mean accepting a harmful status quo for billions of animals while the evidence accumulates. The direction of the evidence, our field experience, and the practical realities of commercial harvests so far all point the same way: electrical stunning is faster, more consistent, and more monitorable than industry-typical ice slurry stunning.
More importantly, it is somewhat illusory to think that all the necessary research and R&D can happen first, in isolation, and only then be translated into the field. In industry-facing work, implementation is often what makes the most useful research possible. Without producer buy-in, farm access, commissioning data, firsthand observations of real harvests, and tests in farm conditions, we would be left with a largely theoretical understanding of the problem. We would not know which constraints actually matter, which failure modes appear in practice, or what kinds of equipment, protocols, and monitoring systems can realistically work.
This is especially true in an industry that is often cautious about disclosure around its know-how. Building trust with producers and the wider industry is not incidental to the intervention; it is part of what makes practical progress possible. That is why we think collaborating with the industry is the most effective path: build trust, implement carefully, learn from the field, improve the technology, and strengthen the evidence base as we go. The field implementation work is what creates the conditions for practical, relevant R&D to happen.
Humane slaughter for shrimp is emerging as a higher-welfare standard, and the science on effective stunning is not fully settled. As I’ve outlined, there are things that would increase our confidence levels. But the available evidence indicates that well-implemented electrical stunning beats what is happening on most farms today. And it’s my view that responsible implementation now, alongside continued research, R&D, and monitoring, is one of the strongest bets we can make for reducing suffering at scale.
This is an example of the fact that we have access to more data than that which is publicly available. In this case, the research summary is published online, but we also have access to the full scientific report (although we’re not at liberty to post or share it). There have been many instances like this over the years.
Behavioral indicators are tricky because they’re not always a reliable indicator of unconsciousness. It’s like proving a negative: you can often infer consciousness from the presence of certain behaviors, but you cannot reliably infer unconsciousness from a lack of those behaviors alone. However, Stirling’s team measured behavioral indicators and investigated which of them correlated with EEG results, to determine which might be reliable.
Generally, when shrimps are electrically stunned, there’s one big tail flip when shrimps go through the stunner (likely a reflexive response), followed by immobility. The Stirling study found that this correlates with shrimps having one big EEG spike and then a drop, likely indicating a seizure analog followed by absence of brain activity (a loss of consciousness).
I have recently been (re)reading Effective Altruism in the Garden of Ends, which is a great post on this forum about what you need to be a hardcore EA. And I'm on the agenda planning group for the (UK) Quaker Earthcare gathering this year, which is all about designing a gathering format to help people get Spirit-led on their climate doom. I've started thinking about what all this might imply about better EA community.
For context, I was first involved in EA in 2018, would describe mysel...
I agree that Quakerism is an interesting, beautiful tradition that may plausibly co-enrich EA. I’ve sat in meetings for worship many times.
I’ll admit, however, that I was a little bothered that this post describes, without asterisk or caveats, Quakers as a “Christian sect.” This is quite a contested position within Quakerism itself, despite its inarguably Christian roots, and Nontheist (i.e. secular or atheist) Quakerism is well attested and not rare (indeed, one source says up to 30% of British Quakers do not identify as theist.)
My experience in Quaker spaces is that people will point to the fact that, for example, that other 70% is theist to sometimes make a similar point - but of course, ‘theist’ is not the same as ‘Christian’ and a plurality is not an absolute definition. Presenting this contested definition as universal feels, to put it directly, misleading, and to me it seems to mar the spirit of the post, primarily because as far as I’m aware nontheist Quakerism is one of the few secular spiritual traditions and I don’t think it should be elided in this way, especially to an audience that may not be familiar with the fact that it is not an unusual Quaker stance in the UK or US.
Michael Nielsen has a beautiful new essay on moral imagination: the ability humans have to 'develop and transmit new notions of good action, indeed, even new kinds of good'.
As examples, he gives:
Thanks Toby!
I couldn’t agree more that these are some important moral imagination innovations, and yet there is a lot of room for improvement among EAs.
I hadn’t heard your “positive ethics“, but I have relatedly thought we need something like “opportunity cost ethics”, which perhaps takes this even one step further, that we ought to continue searching for actions that optimize moral expected value until the point of diminishing returns, where the loss of value from delaying action exceeds the marginal expected value from seeking more information (although you do hit upon a bit of an optimal stopping problem with this, nonetheless I think you can’t sweep the serious importance of this search under the rug.)
Essentially, the world is crazy enough that we should expect crazy opportunities for doing good, and it is of utmost moral value to continue searching as long we are still discovering facts that dramatically improve our prospects for doing good.
I also appreciate your work on moral uncertainty quite deeply, I think this helped me appreciate how important it is to have some kind of comprehensive reflection process for the long-term future, to make sure we get the right moral values before spreading to space. While I independently discovered many of these same moral innovations, e.g. longtermism, I did not fully appreciate this and it has significantly changed my priorities.. Unfortunately I feel like a lot of people (even within EA) still don’t fully appreciate the importance of moral uncertainty.
This competition entry has been selected for publication by the Forum team.
Here’s Anthony DiGiovanni’s unawareness argument, quoted from his summary post (footnotes omitted):
Let’s say that we c-prefer A over B if the reason we prefer A is an impartial altruistic comparison of the actions’ possibl...
Thanks! Great points.
On 1:
I think it's reasonable to say that nowhere-optimal actions can be permissible if we don't have the dominating action in mind, but let me try push back a bit. Imagine that you're in a decision situation, thinking about what's permissible. You know that you have two options, A and B, and that neither of A and B dominates the other. However, you also remember thinking about this same decision situation in the past, where you recognized that you also have a third option C. You remember that C dominates B and that it doesn't dominate A. Unfortunately, you just can't remember what option C is. In this sort of case, I have the intuition that it'd be impermissible to choose B. If that's right, then actions can be rendered impermissible by virtue of being dominated by options that we don't have in mind.
On 3:
One thing to note here is that, although I use mixed actions to rule out nowhere-optimal actions, I don't advocate choosing mixed actions. The decision rule says you should choose somewhere-uniquely-optimal actions, and (as you say) it's impossible for a mixed action to be somewhere-uniquely-optimal. I think that helps a bit with the decision-theoretic-fishiness / dynamic inconsistency / paying to avoid information problems. See also my reply to Jesse's third point.
On 4:
Yes, it's true that more actions tend to become somewhere-uniquely-optimal when there are more probability functions in our representor. I still think that the decision rule makes lots of actions impermissible though. In particular, I think the 'flanking variants' test will rule out lots of actions. See also my reply to Jim Buhler on finding somewhere-uniquely-optimal actions.
On 5:
That's true. The preciser maximizes EV with respect to the probability function. The impreciser just has to maximize EV with respect to some probability function. But, as you say, those can be very different, so maybe it was an overstatement to say that we're almost back where we began.
Yeah, that seems like a pretty good way to go. I think creating too much imprecision might be a concern, and that there's also a concern about motivation. As I understand it, rectangularising in this case means adding probability functions to your representor on which, e.g., Pr(X | Heads)<0.01. But that seems incompatible with characterizing your representor as the set of probability functions you could settle on after ideal reflection on your current evidence, because (we can stipulate that X is such that) ideal reflection won't lead you to believe that X and Heads are so tightly anti-correlated. And given that, it seems maybe hard to justify including probability functions on which Pr(X | Heads)<0.01 in your representor (and thereby letting those probability functions affect what's permissible/impermissible for you).
This week is Cluelessness Critiques Week on the EA Forum.
We'll be publishing eligible entries[1] to the Cluelessness Critiques Essay Competition on the Foru...
Thanks Vasco, this is helpful.
I would be interested in a version of this contest attempting to answer something like "If you believe Vasco that donations to SWP are better than torture, should you also believe that AI alignment is better than misalignment?"
I think that is what Richard Chappell is referring to when he mentions "radical skeptics" here. But I would be interested in a version of his post which defends the claim that EAs are reasonably justified in making the trade-offs we currently make (even if a radical skeptic would not be convinced of this defense).
Reflections from the Effective Giving & Careers team.
Earlier this year we ran our first open call for the effective careers side of our work — a request for proposals from organizations that help people move into high-impact careers. W...
This personal post is not part of the competition, as my intent is not to produce an original constructive response to cluelessness. However, Toby Tremlett encouraged me to share it insofar as it contributes to this week's conversation.
TL; DR: I work in animal welfare and am clueless....
Under your own views, any portfolio of interventions can easily increase or decrease animal suffering?
I agree. This is why I find myself having to "justify" a decision procedure that just considers a few select (albeit uncertain) effects rather than say "I'm maximizing expected value".
I think my decision procedure can make interventions that decrease our uncertainty very appealing. I currently work on animal welfare desk research, and am strongly considering getting into some form of primary research in the future. Caveats:
A preliminary estimate, and a request for better ones.
Summary
I believe the standard literature estimates for the number of DALYs attributable to a case of stunting are too low, largely because they don’t account for the long term effects. This means that childhood nutritional interventions that reduce the prevalence of stunting may be substantially more cost-effective than previously believed.
Epistemic status
Exploratory and back-o...
I am developing a program which I call AI Safety Hub Free Agency, a program to seed new AI safety hubs by sending highly agentic and motivated individuals (Free Agents) with proven experience in organizational founding to cities that are lacking in AI safety communities, connecting them with local talent who act as president of the new organization, and giving them the proper funding to create and fund a new organization. Free Agents w...
For example, I'm a medical student in Taiwan. However, I'm confident that going to USA medical school would probably significantly increase my career donations(because the annual salary in Taiwan doctor is:$170k, while it's $400k in USA, even the tuition of USA med school is $400k more than Taiwan, the career earning is definitely higher). Also, even if I study medicine in Taiwan, it's better for me to become a private clinic owner, which needs a significant amount of money. If I...
Interesting suggestion! I think the example you outline makes sense. I'd guess part of why you don't see this kind of thing in EA might include:
Anyway, just some quick thoughts, very open to counter takes and thank you for suggesting this idea! I do think there is a good place for some smart finance type stuff in EA for sure, such as loans for social enterprises to kick off, or other clever things like advance market commitments.
No, funders can get even more money for effective philanthropy by investing in AI.
EA groups have been and continue to be overpowered.
Running an EA group is among the most impactful things you can do when you are at University.
The other day my previous co-organizer sent me a list of 15 (!) people who were in our EA group who are doing exciting and important GCR work.
In the interest of getting this quick take out, I am not reaching out to everyone to see if I can list their name/quote them but I want to stress the “exciting and important” aspect of this. Some of these people are perhaps within the top 10 people affecting American AI policy from a GCR lens. And they only graduated within the last 5 years - many of whom started in very impactful roles in less than two years(!). People are advising on 100s of millions of dollars, in political office, and founding exciting new orgs in the ecosystem (like, actually awesome orgs!).
And that is only GCR work - a previous member of our group is now CEO of one of the largest EA-affiliated global health orgs and another, a researcher at GiveWell.
When I was a group organizer, I was often stressing about whether I was having an impact and I often hear organizers stressing about whether the payoff will be quick enough. It is true that my group’s outcomes are not the median and that sometimes it does just take many years to pay off - but there definitely are existence proofs of massive impact on a pretty quick timeframe.
I have been involved in EA groups since 2017. Almost a decade now!
And in the meantime I’ve seen so many exciting impact stories coming out from groups all over the world.If you are interested in more of my takes on groups you can check out some of my past talks: Hyping them up and Sharing potential pitfalls
If you are interested in running a group there are many resources available to you!