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Why are April Fools jokes still on the front page? On April 1st, you expect to see April Fools' posts and know you have to be extra cautious when reading strange things online. However, April 1st was 13 days ago and there are still two posts that are April Fools posts on the front page. I think it should be clarified that they are April Fools jokes so people can differentiate EA weird stuff from EA weird stuff that's a joke more easily. Sure, if you check the details you'll see that things don't add up, but we all know most people just read the title or first few paragraphs.
The TV show Loot, in Season 2 Episode 1, introduces a SBF-type character named Noah Hope DeVore, who is a billionaire wonderkid who invents "analytic altruism", which uses an algorithm to determine "the most statistically optimal ways" of saving lives and naturally comes up with malaria nets. However, Noah is later arrested by the FBI for wire fraud and various other financial offenses.
Could it be more important to improve human values than to make sure AI is aligned? Consider the following (which is almost definitely oversimplified):   ALIGNED AI MISALIGNED AI HUMANITY GOOD VALUES UTOPIA EXTINCTION HUMANITY NEUTRAL VALUES NEUTRAL WORLD EXTINCTION HUMANITY BAD VALUES DYSTOPIA EXTINCTION For clarity, let’s assume dystopia is worse than extinction. This could be a scenario where factory farming expands to an incredibly large scale with the aid of AI, or a bad AI-powered regime takes over the world. Let's assume neutral world is equivalent to extinction. The above shows that aligning AI can be good, bad, or neutral. The value of alignment exactly depends on humanity’s values. Improving humanity’s values however is always good.  The only clear case where aligning AI beats improving humanity’s values is if there isn’t scope to improve our values further. An ambiguous case is whenever humanity has positive values in which case both improving values and aligning AI are good options and it isn’t immediately clear to me which wins. The key takeaway here is that improving values is robustly good whereas aligning AI isn’t - alignment is bad if we have negative values. I would guess that we currently have pretty bad values given how we treat non-human animals and alignment is therefore arguably undesirable. In this simple model, improving values would become the overwhelmingly important mission. Or perhaps ensuring that powerful AI doesn't end up in the hands of bad actors becomes overwhelmingly important (again, rather than alignment). This analysis doesn’t consider the moral value of AI itself. It also assumed that misaligned AI necessarily leads to extinction which may not be accurate (perhaps it can also lead to dystopian outcomes?). I doubt this is a novel argument, but what do y’all think?
Many organizations I respect are very risk-averse when hiring, and for good reasons. Making a bad hiring decision is extremely costly, as it means running another hiring round, paying for work that isn't useful, and diverting organisational time and resources towards trouble-shooting and away from other projects. This leads many organisations to scale very slowly. However, there may be an imbalance between false positives (bad hires) and false negatives (passing over great candidates). In hiring as in many other fields, reducing false positives often means raising false negatives. Many successful people have stories of being passed over early in their careers. The costs of a bad hire are obvious, while the costs of passing over a great hire are counterfactual and never observed. I wonder  whether, in my past hiring decisions, I've properly balanced the risk of rejecting a potentially great hire against the risk of making a bad hire. One reason to think we may be too risk-averse, in addition to the salience of the costs, is that the benefits of a great hire could grow to be very large, while the costs of a bad hire are somewhat bounded, as they can eventually be let go.
Given that effective altruism is "a project that aims to find the best ways to help others, and put them into practice"[1] it seems surprisingly rare to me that people actually do the hard work of: 1. (Systematically) exploring cause areas 2. Writing up their (working hypothesis of a) ranked or tiered list, with good reasoning transparency 3. Sharing their list and reasons publicly.[2] The lists I can think of that do this best are by 80,000 Hours, Open Philanthropy's, and CEARCH's list. Related things I appreciate, but aren't quite what I'm envisioning: * Tools and models like those by Rethink Priorities and Mercy For Animals, though they're less focused on explanation of specific prioritisation decisions. * Longlists of causes by Nuno Sempere and CEARCH, though these don't provide ratings, rankings, and reasoning. * Various posts pitching a single cause area and giving reasons to consider it a top priority without integrating it into an individual or organisation's broader prioritisation process. There are also some lists of cause area priorities from outside effective altruism / the importance, neglectedness, tractability framework, although these often lack any explicit methodology, e.g. the UN, World Economic Forum, or the Copenhagen Consensus. If you know of other public writeups and explanations of ranked lists, please share them in the comments![3] 1. ^ Of course, this is only one definition. But my impression is that many definitions share some focus on cause prioritisation, or first working out what doing the most good actually means. 2. ^ I'm a hypocrite of course, because my own thoughts on cause prioritisation are scattered across various docs, spreadsheets, long-forgotten corners of my brain... and not at all systematic or thorough. I think I roughly: - Came at effective altruism with a hypothesis of a top cause area based on arbitrary and contingent factors from my youth/adolescence (ending factory farming),  - Had that hypothesis worn down by various information and arguments I encountered and changed my views on the top causes - Didn't ever go back and do a systemic cause prioritisation exercise from first principles (e.g. evaluating cause candidates from a long-list that includes 'not-core-EA™-cause-areas' or based on criteria other than ITN). I suspect this is pretty common. I also worry people are deferring too much on what is perhaps the most fundamental question of the EA project. 3. ^ Rough and informal explanations welcome. I'd especially welcome any suggestions that come from a different methodology or set of worldviews & assumptions to 80k and Open Phil. I ask partly because I'd like to be able to share multiple different perspectives when I introduce people to cause prioritisation to avoid creating pressure to defer to a single list.

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  • become more fullfilled, resilient, and productive?
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  • embark on that journey together with other ambitiously altruistic
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Thank you for spreading the word! We hope to help lots of ambitious altruists this year.

Yarrow Bouchard posted a Quick Take 4h ago

Have Will MacAskill, Nick Beckstead, or Holden Karnofsky responded to the reporting by Time that they were warned about Sam Bankman-Fried's behaviour years before the FTX collapse?

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Joseph Lemien commented on ABishop's quick take 13h ago

I would like to estimate how effective free hugs are. Can anyone help me?

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Haha. Well, I guess I would first ask effective at what? Effective at giving people additional years of healthy & fulfilling life? Effective at creating new friendships? Effective at making people smile?

I haven't studied it at all, but my hypothesis that it is the kind of intervention that is  similar to "awareness building," but it doesn't have any call to action (such as a donation). So it is probably effective in giving people a nice experience for a few seconds, and maybe improving their mood for a period of time, but it probably doesn't have longer-lasting effects. From a cursory glance at Google Scholar, it looks like there hasn't been much research on free hugs.

Hmm, I'm a little confused. If I cook a meal for someone, it doesn't seem to mean much. But if no one is cooking for someone, it is a serious problem and we need to help. Of course, I'm not sure if we're suffering from that kind of "skinship hunger."

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You'll get a weekly email with the best posts from the past week. The Forum team selects the posts to feature based on personal preference and Forum popularity, and also adds some announcements and a classic post.

“I really needed to hear that”

His eyes were downcast, his normally jocular expression now solemn. I had really said something that had spoken to him, that had begun to assuage some hurt which had before remained unacknowledged.

It’s not your fault. Four words.

Later, I was...

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Thank you for your service.

On 17 February 2024, the mean length of the main text of the write-ups of Open Philanthropy’s largest grants in each of its 30 focus areas was only 2.50 paragraphs, whereas the mean amount was 14.2 M 2022-$[1]. For 23 of the 30 largest grants, it was just 1 paragraph...

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1
DPiepgrass
7h
What if, instead of releasing very long reports about decisions that were already made, there were a steady stream of small analyses on specific proposals, or even parts of proposals, to enlist others to aid error detection before each decision?
1
David T
9h
I think a dedicated area would minimise the negative impact on people that aren't interested whilst potentially adding value (to prospective applicants in understanding what did and didn't get accepted, and possibly also to grant assessors if there was occasional additional insight offered by commenters) I 'd expect there would be some details of some applications that wouldn't be appropriate to share on a public forum though

I 'd expect there would be some details of some applications that wouldn't be appropriate to share on a public forum though

Hopefully grantees can opt-in/out as appropriate! They don't need so share everything. 

Would love for orgs running large-scale hiring rounds (say 100+ applicants) to provide more feedback to their (rejected) applicants. Given that in most cases applicants are already being scored and ranked on their responses, maybe just tell them their scores, their overall...

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(I run hiring rounds with ~100-1000 applicants) agree with Jamie here. However, if someone was close to a cutoff, I do specifically include "encourage you to apply to future roles" in my rejection email. I also always respond when somebody asks for feedback proactively.

Is revealing scores useful to candidates for some other reason not covered by that? It seems to me the primary reason (since it sounds like you aren't asking for qualitative feedback to also be provided) would be to inform candidates as to whether applying for future similar roles is worth the effort.

I view our hiring process as a constant work in progress, and we look back at the application process of everyone after their time with us, potatoes and gems alike, and try figure out how we could have told ahead of time. Part of that is writing up notes. We use chatgpt to make the notes more sensitive and send them to the applicant. 

Caveat: We only do this for people who show some promise of future admission. 

Jamie, I've been contemplating writing up a couple of informal "case study"-type reports of different hiring practices. My intention/thought process would be to allow EA orgs to learn about how several different orgs do hiring, to highlight some best practices, and generally to allow/encourage organizations to improve their methods. How would you feel about writing up a summary or having a call with me to allow me to understand how you tried giving feedback and what specific aspects caused challenges?

Reducing the influence of malevolent actors seems useful for reducing existential risks (x-risks) and risks of astronomical suffering (s-risks). One promising strategy for doing this is to develop manipulation-proof measures of malevolence.

I think better measures would...

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Why are you pessimistic about eyetracking and body language? Although those might not be as helpful in experimental contexts, they're much less invasive per unit time, and people in high-risk environments can agree to have specific delineated periods of eyetracking and body language data collected while in the high-performance environments themselves such as working with actual models and code (ie not OOD environments like a testing room).

AFAIK analysts might find uses for this data later on, e.g. observing differences in patterns of change over time based... (read more)

I am thrilled to introduce EA in Arabic (الإحسان الفعال), a pioneering initiative aimed at bringing the principles of effective altruism to Arabic-speaking communities worldwide.
 

Summary

Spoken by more than 400 million people worldwide, Arabic plays a pivotal role...

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I am so happy to see this :D The translation and the website are amazing. Have you considered sharing the experiences of people from the MENA region who are open about EA ideas within their community? (It's something I am personally struggling with)

Peter Wildeford posted a Quick Take 14h ago

The TV show Loot, in Season 2 Episode 1, introduces a SBF-type character named Noah Hope DeVore, who is a billionaire wonderkid who invents "analytic altruism", which uses an algorithm to determine "the most statistically optimal ways" of saving lives and naturally comes up with malaria nets. However, Noah is later arrested by the FBI for wire fraud and various other financial offenses.

Continue reading