Algo_Law

Karma: 336

BSc (Hons) Computer Science with Artificial Intelligence

Master of Laws (LLM) Space Law

PhD Candidate (Law) - Title: “AI and Machine Learning Nascent Visual Biometrics in Police Intelligence and Criminal Evidence – Impacts on Reliability and Fairness”

I currently work in the criminal justice system of England & Wales, as well as researching my PhD. My academic history in AI and in Law have resulted in an avid interest in all things AI Law (esp criminal law and human rights law) and its value to Longtermist principles. If you ever want to chat about the topic at all, please feel free to pop me a message:)

Algo_Law 7 Oct 2022 15:08 UTC
11 points
0 ∶ 0
in reply to: IanDavidMoss’s comment on: Warning Shots Probably Wouldn’t Change The Picture Much
“I think the second view is basically correct for policy in general, although I don’t have a strong view yet of how it applies to AI governance specifically. One thing that’s become clear to me as I’ve gotten more involved in institution-focused work and research is that large governments and other similarly impactful organizations are huge, sprawling social organisms, such that I think EAs simultaneously underestimate and overestimate the amount of influence that’s possible in those settings.”
This is a problem I’ve spoken often about, and I’m currently writing an essay on for this forum based on some research I co-authored.
People wildly underestimate how hard it is to not only pass governance, but make sure it is abided to, and to balance the various stakeholders that are required. The AI Governance field has a massive sociological, socio-legal, and even ops-experience gap that means a lot of very good policy and governance ideas die in their infancy because no-one who wrote them have any idea how to enact them feasibly. My PhD is on the governance end of this and I do a bunch of work within government AI policy, and I see a lot of very good governance pitches go splat against the complex, ever-shifting beast that is the human organisation purely because the researchers never thought to consult a sociologist, or incorporate any socio-legal research methods.

Algo_Law 7 Oct 2022 14:59 UTC
1 point
0 ∶ 2
on: What does it mean for an AGI to be ‘safe’?
Good post, thank you.

”or other such nonsense that advocates never taking on risks even when the benefits clearly dominate”

An important point to note here—the people who suffer the risks and the people who reap the benefits are very rarely the same group. Deciding to use an unsafe AI system (whether presently or in the far future) using a risks/benefits analysis goes wrong so often because one man’s risk is another’s benefit.

Example: The risk of lung damage from traditional coal mining compared to the industrial value of the coal is a very different risk/reward analysis for the miner and the mine owner. Same with AI.

Algo_Law 27 Sep 2022 18:28 UTC
1 point
1 ∶ 0
on: Giving opportunity: $50 ‘thank you’ notes
This would be an interesting approach to generate charitable donations. I would caution though that this seems to me (a non-USA person, so take this with a grain of salt) to skirt a little close to some laws surrounding this so I’d definitely check that out first. One man’s charitable fundraising could be another man’s false representation!

Still though, interesting thought :)

Algo_Law 27 Sep 2022 18:20 UTC
5 points
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on: The Onion Test for Integrity
This is helpful. My entire career revolves around “conceal, but don’t mislead” and even I’m still learning where lines are. Thank you for this post.

Algo_Law 10 Sep 2022 8:59 UTC
26 points
13 ∶ 0
on: Cause Exploration Prizes: Announcing our prizes
This was a great event which I followed very closely indeed. It generated so much interesting exploration of different areas and I learned so much about the world I live in.

I just want to add that the idea of having ‘good-faith’ submission prizes was a fantastic addition, and really helped level the playing field for people who otherwise might not have been able to contribute. I heard from a couple of people that they may not have been able to submit without them. I’d love to see more of these in similar contests in future.

Algo_Law 13 Aug 2022 10:36 UTC
3 points
0 ∶ 0
on: Any Legal Consultancies for Early EA Orgs?
I understand there are some people in the early stages of exploring this, though I’m sorry for the life of me I can’t remember who. The Law and Longtermism slack channel which is run by the Legal Priorities Project and may be a good starting point, as I understand some people have found people for this there before.

Algo_Law 8 Aug 2022 12:27 UTC
1 point
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in reply to: Karthik Tadepalli’s comment on: Why does no one care about AI?
You raise some fair points, but some others I would disagree with. I would say that just because there isn’t a popular argument that AGI risk affects underpriviliged people the most, doesn’t make it not true. I can’t think of a transformative technology in human history that didn’t impact people more the lower down the social strata you go, and AI thus far has not only followed this trend but greatly exaccerbated it. Current AI harms are overwhelmingly targetted towards these groups. I can’t think of any reason why much more powerful AI such as AGI would for whatever reason buck this trend. Obviously if we only focused on existential risk this may not be the case, but even a marginally misaligned AGI would exaggerate current AI harms, particularly in suffering ethics cases.

Algo_Law 8 Aug 2022 9:48 UTC
3 points
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in reply to: Gil’s comment on: Most Ivy-smart students aren’t at Ivy-tier schools
Good points. An important point to bear in mind though is that once again well-roundedness, volunteer work, hobbies etc are all related to factors apart from motivation/ability. Generally, people from wealthier backgrounds have much more of these on their resume than people from poorer backgrounds because they could afford to take part in the hobbies, could afford to work for free, etc. Lots of supposedly ‘academic filtering’ is actually just socioeconomic filtering with extra steps.

Algo_Law 8 Aug 2022 9:43 UTC
1 point
0 ∶ 0
on: Why does no one care about AI?
Great post! I’m gonna throw out two spicy takes.

Firstly, I don’t think it’s so much that people don’t care about AI Safety, I think it’s largely who cares about a threat is highly related to who it affects. Natural disasters etc affect everyone relatively (though not exactly) equally, whereas AI harms overwhelmingly affect the underpriviliged and vulnerable. People who are vastly underrepresented in both EA and in wider STEM/academia, who are less able to collate and utilise resources, who are less able to raise alarms. As a result, AI Safety is a field where many of the current and future threats are hidden from view.

Secondly, AGI Safety as a field tends to isolate itself from other areas of AI Safety as if the two aren’t massively related, and goes off on kind of a majorly theoretical angle as a result. As a consequence, AGI/ASI Safety folk are seen as something of living in a fantasy world of their own making compared to lots of other areas of AI risk by both the public and people within AI. I don’t personally agree with this, but it’s something I hear a lot in AI research.

Algo_Law 6 Aug 2022 8:24 UTC
11 points
0 ∶ 0
on: 4 Ways to Give Feedback to Job or Grant Applicants
This would be very helpful. It’s often confusing for the applicant as they have no idea what to change/work on. For me, I’ve been rejected by every EA fellowship I’ve ever applied for (woop woop, highscore) but I don’t know how to improve. Twice orgs have legit emailed me out the blue saying they like my blog/forum content and asking me to apply and then rejected me. I have no idea what stage I failed at. Was my application poorly written? Were my research suggestions poor? Is it a CV issue? Am I over or under qualified? Who knows. Certainly not me. So I’m sat here, still shooting off applications, with no idea which part is letting me down. I sometimes get “your application was really strong but unfortunately...” in the rejection email, but I’m never sure whether that’s being nice or actual feedback.

They say it’s expensive or time consuming to give feedback, and that’s a fair comment, but compared to the possible upside I think it’s a sound investment. I’ve collaborated with a bunch of really talented EAs who gave up applying to fellowships because of this. Deadlines are often extended because they want more applications, but maybe they’d get more applications if their attrition rates were lowered by giving people (especially early careers people) an idea of what areas they need to work on.

You can ask third parties to review your applications, but really only the orgs themselves know why something was rejected.

Algo_Law 6 Aug 2022 8:17 UTC
2 points
0 ∶ 0
on: $20K in Bounties for AI Safety Public Materials
The audience section is a wide scope which is useful, but just to confirm—would doing an explainer for AI Safety topics/issues affecting other areas with those as the audience count?

Eg. Producing content on AI Safety risks in economics for economists? Or producing content on AI Safety topics in medicine for doctors?

Algo_Law 1 Aug 2022 8:38 UTC
11 points
0 ∶ 0
in reply to: JoelMcGuire’s comment on: Announcing: the Prague Fall Season
I think you’re right in your third paragraph. I lead a small group far outside of a ‘hub’ and I’d find this really useful as being immersed in a fully EA environment for some time. It wouldn’t so much being a case of pulling me FT to Prague, but more a chance to spend time in an EA environment that is different from my home one. That’s largely what was behind my own application, anyway.

Algo_Law 24 Jul 2022 5:54 UTC
1 point
0 ∶ 0
in reply to: Cullen 🔸’s comment on: Law-Following AI 3: Lawless AI Agents Undermine Stabilizing Agreements
No problem RE timescale of reply! Thank you for such a detailed and thoughtful one :)

Algo_Law 22 Jul 2022 21:42 UTC
2 points
0 ∶ 0
on: Social scientists interested in AI safety should consider doing direct technical AI safety research, (possibly meta-research), or governance, support roles, or community building instead
I really enjoyed this post, thank you for writing it. I’m commenting from an AI law and policy centric view, so this comment is mainly aimed at that angle.

I agree with much of your post, but I want to highlight that there is a need for social scientists in some areas of AI Safety research. I have worked on a few projects for the UK government around AI Safety, helping to build legal, regulatory, and mitigation strategies in the AI Safety field. This is often part of an interdisciplinary team. A few of us are usually sociologists which, with me having a mixed CompSci and Law background, was initially a big change. They were massively useful. I think the importance of understanding human society and how it functions is often woefully underestimated in the AI Safety field. It may or may not have a place in the purely hard-line technical AI Safety area, (I’d be the wrong person to ask), but in terms of governance and policy specialisms such as sociology and economics are very important. If anything, there’s a bit of a lack of people with those expertise area with adequate knowledge of AI. So if there is someone who is, for example, a sociology PhD with a big interest in AI, there are definitely opportunities available.

The hard part is finding them. One of the weird niggles of AI Policy/Governance is that it’s heavily network-based in that you have to build and maintain relationships as a core resource. This means someone starting out without someone there to guide/help can face a real challenge. Another of the downsides is that sometimes (quite rarely) the work/research/projects is secret or NDA, so people don’t always get to talk about the work they did in as much detail when applying for fellowships, jobs etc.

This is why I think orgs which run fellowships in this area are important—they’re a jumpstart on the network element and can help better guide people to new specialisms.

Edit reason: typo

Algo_Law 22 Jul 2022 21:13 UTC
16 points
0 ∶ 0
on: On Elitism in EA
Preface: There is every possibility that I have misinterpreted or misread the post. Please do let me know if this is the case and I will rescind this comment.

This is an interesting post, thank you for making it. It must have taken a lot of effort, and it’s always a bold move putting culture and community related thought pieces out there because they’re often not ‘safe’ topics. Though I enjoyed many of your past posts, I don’t agree with this one for a couple of reasons.

Firstly, I think the term ‘elitism’ is used too broadly in some areas. Eg. sometimes you mean it to mean cutting out people from different backgrounds, and sometimes a much broader sense. I think it would be helpful to define more clearly what you mean by it. I know you both say “Elitism in EA usually manifests as a strong preference for hiring and funding people from top universities, companies, and other institutions where social power, competence, and wealth tend to concentrate.” but that doesn’t appear to track consistently through the post.

Secondly, some points are contradictory. Eg you state:
“In these cases, elitism is beneficial because specialized competence and leadership are key to being successful in senior roles (e.g. CEOs, senior AI engineers, research leads) and these are traits highly correlated with elite environments.”
But you also state:
Elite selection (e.g. at top universities) will often select for people who have a baseline of financial stability.
This links to my first point in that it’s not clear whether you’re talking about ‘elite environments’ as people who are the best in their field being brought together, or people from supposedly ‘elite’ institutions/organisations. These quotes are from different sections, however, so perhaps I have divorced them from context here.

I see quite frequently in EA discourse that ‘elite’ universities are equated with the best talent. For a community based on rejecting assumptions, it’s quite a leap to make. I’m not saying people from those universities aren’t great (because they are), but there’s an important point to consider.

If we take two of the most ‘elite’ universities in the UK, Oxford and Cambridge, and take but a cursory look around their website we find the following:
Cambridge University
“Taught students undertaking taught Masters courses (for example, the MPhil by Advanced Study) are normally expected not to work during term-time. Students should consult their Faculty and Department for further details regarding vacation dates when they may be able to work.”
and also
Research students undertaking a course of more than 12 months or the MPhil by Research may undertake paid work up to a maximum of ten hours per week with the approval of both their Supervisor and College Tutor. The work undertaken should be either academic-related, related to a student’s professional or career development, outreach work undertaken on behalf of the University or related to covid-19.
Oxford University
Study at Oxford is very demanding. We would strongly advise against you relying on income from employment to fund your studies as this may have an adverse effect on your ability to complete your course to your full potential.
and also
An undergraduate degree at the University of Oxford is a full-time course. During term-time you will have very little time to take on a part-time job in addition to your studies and other activities. There are some opportunities to do a limited amount of paid work within colleges, but you should not rely on this in your budgeting

If you then Google the most expensive cities in the UK, you’ll notice some familiar names. Oxford often sits at the #1 spot, in fact.

A trend appears here—and it’s not unnoticed. Research by Cherwell found that the national average for students working part-time was 57%, with 90% of those working as many as 20 hours per week. In Oxford? Only 20% of students are employed and the majority work less than five hours per week.
So how are these funded? There are a variety of scholarships available, but some quick sums on a calculator show these don’t quite add up. Oxford is one of the UK’s most expensive cities, and even on the maximum student loan amount you’re still £2000 - £5000 short each academic year. Cherwell found that to make this up, a student would need to work 850 hours a year—which amounts to full-time for 22 weeks. Essentially, to not only excel but even participate at these universities you need savings—often from family or sponsors. I will say this, because it’s important: many students from low income families do go to these universities and manage to make it work. So if you’re reading this and this is you, don’t be mad. I’m not saying it’s impossible—I’m saying it’s an influence in creating a trend where wealth matters as much as or more than ability.

So for these reasons I would challenge this assumption that elite universities are collections of the best and brightest in the country. They’re a collection of intelligent people who also have the financial ability to go. I would go as far as to say, and I am expecting significant pushback on this, that if anything this is less valuable to draw from as on average these people will have faced fewer obstacles and gained less life experience than equally able peers from different socioeconomic brackets. You mention earlier traits like ‘leadership’ and ‘agency’, and would argue that these are traits more commonly found in those who bootstrap rather than who come from ample opportunity.

It’s entirely possible you didn’t intend ‘elite environments’ to mean this, but perhaps that could do with being cleared up. At any rate, I’ve long posed that drawing from certain universities doesn’t guarantee access to the best talent and that this elitist view robs EA of lots of potentially highly impactful talent. A look at recent history’s most transformative technologies and people doesn’t reinforce the idea that there’s a correlation between university eliteness and capacity for impact.

Again, I reiterate because people can jump to conclusions, I’m not saying elite universities don’t select from highly able people. Because they do. They have higher numbers of more able people there than anywhere else because they can select from a greater pool. I’m saying that they are not made up of the most able people.

So as far as elitism goes, by selecting for the people based on socioeconomic factors, we not only suffer from a lack of intellectual range of thought (as you rightly state in your post), but elitism becomes a self-fulfilling spiral.

Finally, though I appreciated some elements of your post, I honestly struggle to think of any genuine examples where elitism is in any way helpful either for research purposes or within EA. I would very strongly push back against that assumption. One particular part:

”financial stability is an important prerequisite to getting more involved”

I’m not sure how this could be true, unless you’re referencing socioeconomic barriers within EA—in which case removing them would be a tiny fraction of the cost than losing the amount of talent it does. A $100,000+ salary could be useful for earning to give, but in terms of actually interacting with EA and contributing to cause areas, pretty much every most impactful EA I personally know is on well under half of that.

These are just my takes, and there’s every chance people will heartily disagree with me. But that’s what makes our ideas better :) Perhaps a different word might be better—that doesn’t carry the connotations of elitism? Just an idea!

Algo_Law 21 Jul 2022 17:22 UTC
5 points
0 ∶ 0
on: If you’re unhappy, consider leaving
I’ve purposely built my engagement with EA in line with the principles you wrote:
1. Social—have non-EA friends. Ideally have some be local. Talk about other stuff with them, mostly.
2. Financial—do not rely on EA funding sources for income that you couldn’t do without. Don’t apply for EA jobs.
3. Emotional—do not have a unidimensional sense of self-worth that boils down to “how am I scoring on a vague, amorphous impact scale as envisioned in EA terms
In this way I think I’m fairly permanently ‘out’ of EA. But I think I get the best of both worlds like this. I have a foot in enough to make impact and to be generally considered an EA, but if I was unceremoniously booted out of EA tomorrow it wouldn’t be catastrophic. Or even significantly affect my life that much.

¹¹⁄₁₀ would recommend

Algo_Law 18 Jul 2022 16:07 UTC
6 points
0 ∶ 0
on: Fellowship alternative: Reading the EA Forum (with discussion questions)
Finally. An EA fellowship that cannot reject me. Victory is mine!

Joking side, I really like a lot of the questions here. It’s also worth bearing in mind a lot of the categories can overlap with each other which is another big bonus I see. Ideally, would these discussions take place on a single megathread, or across multiple smaller ones? Perhaps stickied topics in each tag?

Algo_Law 18 Jul 2022 15:58 UTC
1 point
0 ∶ 0
on: On the Journey Towards Action
Yeah, I’m going to agree with JeffreyK here and say that you could definitely pursue philosophy as an interdiscipline. Tbh, PhD is a philosophy degree in every area. My law PhD is technically a philosophy degree. I’m doing a lot of philosophy in it despite not having a prior interest in that area, because it’s required for new knowledge.

If you have an interest area such as law, tech, animal rights, etc, you can always combine that with philosophy. That way you get to be a philosopher whilst also doing something you enjoy doing.

Also, be aware that EA (for its myriad of amazing qualities) has this weird propensity for hero worship. We tend to pick one individual and put them on a pedestal, whilst also forgetting the large teams it took to get them there. It’s not a uniquely EA flaw, it’s a hero thing. The event organisers, PR agents, marketers, consultants, ops folk, etc were all vital for their success, but don’t make it to the bio section. You can make a big impact in EA without mirroring someone else’s career path, even by contributing to wherever you feel most interest.

Algo_Law 18 Jul 2022 15:48 UTC
10 points
0 ∶ 0
on: Law School: Why and When? – Considerations for Members of the EA Community
This is a fantastic and much-needed post with loads of consideration. Really great to see, especially with a small but growing legal and legal-adjacent community in EA.

I did a similar route to this but in the UK, so in the spirit of adding context for those who aren’t US-based, I’m going to cover some points in this comment. It’s not agreeing or disagreeing with anything you said in your post, but providing a little bit of info from a different area for anyone from there :)

I did my undergrad in AI, formally the BSc (Hons) Computer Science with Artificial Intelligence. Because of engaging a lot with EA at the tail end of that degree, and due to 80,000 hours publications, I applied for an LLM at Northumbria Law School. A lot of law schools here in the UK are starting to encourage interdisciplinary applicants to fill new skill gaps in emerging areas.

I applied and was accepted for Space Law (LLM), and graduated in 2021. I found it a bit difficult, but law in itself wasn’t that hard and to be honest the biggest change to get used to was going from STEM writing and research styles to legal styles. I really enjoyed it, and would recommend it to others. So if you’re UK-based with a non-law background, there are a lot of places that cater to that.

This is the course I did which I would recommend both as a uni and for the teaching staff who were hugely supportive and really passionate. They included an ‘Advanced Legal Research’ module to get the STEM folks up to speed. I’d say for my cohort it was around 70% of the course were lawyers, 20% computer scientists/engineers, and 10% other. Most people adapted to law well. So if you’re interested in going into an area specialism, it’s a good place to start. This course also did modules on AI law, which I took and would recommend. Very interesting.

The exams were all long essays (which generally we could pick the topic for, lots of freedom), with a final research project (again, you decide). I then went on to do my PhD in law at the same law school, where I’m looking at AI in policing and as evidence. So even as a non-law background person you can still advance.

Downsides are that due to the non-law background, you’re not technically a lawyer. You’ll still be highly sought after by companies looking for information, and because it’s a niche area there’s lots of opportunity for early careers impact, but you’ll need to do a conversion course to be able to give actual legal advice. (Except as an expert witness or general counsel, but expert witness work can be few and far between, with general counsel work preferring lawyers over non-lawyers).

Luckily the UK just introduced the SQE, a new way for non-law folk to qualify as solicitors. There are considerable financial barriers unfortunately, as the exams are horrendously expensive for literally no reason (one is like £2500 to take a multiple choice online exam) so there are real class barriers. You can also take the bar course to be a barrister, but I have less familiarity with that.

For fees, you can get funded quite easily by SFE I found, but can’t speak for those outside of England. As normal in the UK, your loan repayments are only taken as a small % of what you earn over a certain threshold, so you can’t really go broke by going to law school. It’s not a ‘real’ loan, like all educational loans.

So yeah, this post was a great read and it’s cool to see that law school is becoming more explored as a career path. Honestly I kind of fell into it, but found a niche I enjoy with lots of good impact potential so maybe I just got lucky. I’d recommend to anyone interested in studying law not to let yourself get put off by law’s reputation as a fierce and considerably difficult area. I actually found law to be way less toxic than computer science, and around the same in difficulty.

If anyone based in UK wants to ask me more about my experiences, my inbox is open. I only applied for the LLM because I knew a non-law person who did it before me and got to grill them. Or I wouldn’t have likely applied. So I’m happy to pass that baton on :)

Algo_Law 18 Jul 2022 15:23 UTC
10 points
0 ∶ 0
on: A Survey of the Potential Long-term Impacts of AI
This is a really great, high-quality look at this area. Thank you all so much for writing it, especially in such an easy to read way that doesn’t sacrifice any detail.

One bit I really like about this is it addresses a major blind spot in AI safety:

”AGI is not necessary for AI to have long-term impacts. Many long-term impacts we consider could happen with “merely” comprehensive AI services, or plausibly also with non-comprehensive AI services (e.g. Sections 3.2 and 5.2).”
I feel that Section 4 is an area that the current AI Safety research really neglects, which is odd because in my opinion it is the area of AI Safety that is perhaps most vital—both for preventing suffering and for preventing long-term risk.

I’ve been doing a lot of research in this area within Criminal Justice, and we recently published a report for the UK Cabinet Office and the Centre for Data Ethics and Innovation on their trials of a new Algorithmic Transparency Standard which is somewhat down this avenue of investigation. The standard’s aim was to try and mitigate some of these risks, and the work was evaluating how it would interact in real-world situations. You can read it here if you’re interested: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4155549

For my PhD research I am looking at how AI is used within criminal justice, both as intelligence and as evidence. This area has a really big impact on AI Safety and yet very few people (especially EA-aligned) are working on it, so it was really refreshing to see you cover issues such as facial recognition in your post. The issues around how the technology is developed, sold, and used have a load of parallels with the wider AI Safety debate, in addition to being directly related from an authoritarian risk stance.

I really enjoyed your coverage in Section 6.2, and have considered for some time writing up an in-depth primer to many of the issues in this area. There’s a lot of factors at play that are impacting the (very rapid) rollout of automation and AI in policing and crime, and the dynamic between developers and purchasers is particularly crucial to the wider AI Safety field. Lots of AI Safety’s biggest fears about AI in a century’s time are already becoming a reality at small scale, but the nature of criminal justice is that it often occurs behind closed doors, to people who can’t publicise what has happened to them, and is often not interpretable to those not involved in the criminal justice system. When an AI sends someone to prison based on its say-so, that doesn’t end up in a research paper. The person just disappears into the void. Hence many researchers are unaware that it’s happening. I’m fairly convinced that this is an important cause area for exploration, so if anyone else wants to work on projects like this feel free to drop me a message.

Circling back to the research paper above, an important quote stood out to me:

”‘Most algorithms that have been designed in policing aren’t tested for bias. They’re not designed with any transparency. Mostly the people who built them don’t know what they do, let alone anybody else”—Interview Subject C5

This has strong parallels to what you were saying about how AI, particularly when it comes to power and society, doesn’t have to be AGI to be harmful. We spend a lot of time worrying about super-labs creating superintelligence, but merely thoughtlessly made software in the wrong place with a lot of power under the code’s “fingertips” means that despite only being a fancy decision tree, it can still cause a lot of harm very quickly.

Your point in the conclusion is also really important:

”Power and inequality: there are a lot of pathways through which AI seems likely to increase power concentration and inequality, though there is little analysis of the potential long-term impacts of these pathways. Nonetheless, AI precipitating more extreme power concentration and inequality than exists today seems a real possibility on current trends.”

I think a lot of the reason there is little analysis in this area is that:

1. There is, for reasons I am unsure of, often a great dislike of anything that remotely smells like ‘social justice’ in EA. No-one is ever clear about their reasoning, but I’ve heard a lot that people greatly fear EA becoming ‘infiltrated by SJWs’ or whatever. When in reality, social justice is a major part of Longtermism.

2. Most EA people tend to be from the kind of backgrounds where this power inequality won’t affect. This means that AI can be causing lots of harm, but to the kinds of people who are underrepresented in EA. It’s why increasing the range of people we attract to the community is vital. It’s not EDI box-ticking, it’s a matter of intellectual diversity. I know CEA are making some progress on this, but I’d like to see more formal effort put into this because I think it has significant knock-on impact for the type of AI (and other) research to do with this area we see.

All in all, great read and I can’t wait to see more surveys from you all.