Political theorist, John Jay College/Harvard. Married to @diatkinson. Recent paper on human skills needed to control advanced AI: https://xitter.cf/t.co/guUWsbne0k

Joined March 2020
Tomorrow begins my "Governance of AI" class at Harvard. Super excited. Features work from all the usual suspects, including @GovAIOrg @forethought_org @EpochAIResearch @law_ai_ @TomDavidsonX @dwarkesh_sp @KelseyTuoc @deanwball @gwern @random_walker & more! Syllabus below.
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Joan Eleanor O'Bryan retweeted
Yes, I feel comfortable trusting Pangram to confirm my own intuitions. Here are the real problems: (1) Catching students cheating creates a bureaucratic nightmare for professors. (2) Catching students cheating is not the same as successfully teaching them.
If Pangram truly is as perfect as its academic defenders say it is, faculty could go back to offering out-of-class assignments, papers and take-home exams. But would you feel comfortable failing a student based on an AI's probabilistic judgment?
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Joan Eleanor O'Bryan retweeted
I would love it if some economists wrote a clear general-audience-accessible piece on how to think about 2pp (or growth) in units and abstractions, or even one just specifically aimed at AI researchers and computer scientists. I don't just mean something like "here is the long-run trend in GDP and the trend in child mortality and they correlate" or something one would see at a progress conference. That is good but not enough. What I mean is something that will help to deeply calibrate a sophisticated (quantitative yet non-economist) reasoner on why 2pp matters. In my experience as one of the extremely few computer scientists working on the economics of frontier AI, most computer scientists (who generally have no economic training) do not think 2pp over the next decade can coincide with much progress in society/improved welfare. Not to be unkind to my fellow computer scientists, but I honestly think the first-order reason is 2 is a small number, fairly close to 0. So if one believes that AI will improve society dramatically, then that suggests they need to reject "2pp" and, often, to throw out trust in economists with it altogether (baby with the bathwater). But I think a lot could be fixed if economists can help reconcile "2pp" and with "materially better". (And maybe this already exists and I am unaware.)
Replying to @Afinetheorem
PS - if we got an additional 1pp per year, or hey, maybe even 2pp of growth over next decade, it would be a boomtime the likes of which none of us in the West have seen in our lifetimes! Not a disappointment!
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Joan Eleanor O'Bryan retweeted
it's funny how even though this was just 6 months of trend extrapolation, part of me didn't believe anything would change
It was actually 6 months..
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Joan Eleanor O'Bryan retweeted
Women in the 1700s had way more babies in their late 30s and 40s than we do now, with zero fertility tech. They started in their 20s and just kept going. By 42, a woman was usually on baby #6, not baby #1. They also moved all day and ate real food. They spent most of their fertile years pregnant or nursing, which meant way less cycles for endometriosis and fibroids to build up. Your body learns to do this. Don't make it start cold at 40.
It is an incredible fact that women in the past had far more children at older ages than women do today, even without the benefit of modern technology. Assisted reproductive technology is supposed to extend the fertility window, and yet childbearing ends sooner now than it did in the past! 1/4 (Cambridge Population Group)
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Joan Eleanor O'Bryan retweeted
Getting real tired of the Surprised Pikachu routine this guy does. Wow, AI got so good at hacking that we can’t keep up? You “no longer think we’ll be able to patch all the bugs”?? Who could have predicted this??? Many people! For decades! Including Altman himself! He said he was “not optimistic that any of this will work” when it comes to security measures to contain superintelligent AI. He said that in 2015, just before founding OpenAI and then spending a decade straight driving this technology to the dangerous and unstable place that we’re in today.
OpenAI CEO Sam Altman: "I don't even know a dramatic enough word to use… models can find bugs that are outside of the normal threat model of what we think a hacker can do… hardware-level, insane stuff… I no longer think we're gonna be able to just patch all the bugs." It's over.
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Joan Eleanor O'Bryan retweeted
Me in a magic shower of instant hot water in my house with A/C, after a big breakfast with all my healthy kids, living a life that the vast majority of humanity across time would give their left foot for: "Dear God, life is hard, I could really use some more money"
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Joan Eleanor O'Bryan retweeted
Interesting article. At UCL, we still don't have access to Pangram to check student work, which seems crazy. 'I recently reviewed 1,191 doctoral dissertations from 2025 in the fields of educational leadership and administration. My research suggests that 35 percent of those dissertations were made up of more than a negligible amount — i.e., greater than 10 percent — of AI-generated text. Ten percent were more than 50 percent AI-generated... Before you protest — “AI-detectors are unreliable”; “they’re potentially biased against nonnative speakers”; “they can be tricked” — let me tell you that I used Pangram. It is not for nothing that Pangram has become the tool of choice for much of the internet, as a slew of peer-reviewed research has found that it achieves “near-zero” false-negative and false-positive rates, even against “adversarial” and “humanizing” AI software. I have used Pangram over the last year in my undergraduate, graduate, and doctoral courses and have found it (with additional safeguards and protocols) to be near-perfect in detecting students’ inappropriate use of AI in their writing. My ongoing study used 100 dissertations published before 2020 as a control; all came out as “100 percent Human” in Pangram.'
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Joan Eleanor O'Bryan retweeted
Damn, according to the office of disability one of my students has “brain rot,” which means I have to let them submit AI-generated work.
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Joan Eleanor O'Bryan retweeted
I've heard folks say post-AGI, a lot of human activity will be like going to the gym. There will be things you can do and places you can go to maintain the mental capacities you don't have to use as much anymore, like reason and creativity. This is presented as a positive vision.
Replying to @GregoryConti19
Video games are actually a leading example of where we will supposedly find meaning in a post-AGI world in Amodei's own vision.
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Joan Eleanor O'Bryan retweeted
Yep. Seems pretextual. Signal is pretty standard in AI industry in my experience and OpenAI autodeletes a lot of its own messages iirc. During the board crisis for example there was a lot of pro-sama organizing being done on signal.
It sounds like OpenAI fired the three safety researchers because they used disappearing messages. It sounds like they weren't told not to; they were just fired without warning after the fact. Seems bad.
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Joan Eleanor O'Bryan retweeted
I've recently been talking a lot about how we have to actively make sure humans are driving the legal process even over efficiency concerns or even getting the "best" outcome (which is driven by a flawed view of what law is, but that's a fight for another time). This extends up and down the range of disputes, including relatively low stakes ones, where juniors can learn to take on more consequential roles. We have enough people to do this, especially when we anticipate a glut of high agency, well educated people as AI takes over more white collar functions. What it requires is the will to implement it, deciding to pay for it, and designing how it works in practice. Not easy for sure, but I urge the people who say that this is pointless or AI is better at it anyway to extend their logic and tell us where they see humanity in their future. Of course Anthropic is doing a great job of recruiting the best and most creative legal thinkers as employees and advisors, and they and other AI companies see law as a big market sector, so I'm usually very pessimistic. Great to see that at least some people like @joaneleanor_ are working on broad approaches to this challenge.
I agree that if we want a human controlled future, we need to hire and train junior employees even at a cost to short term efficiency.
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Joan Eleanor O'Bryan retweeted
In fact, a human controlled future is worth a cost to long-term efficiency as well.
I agree that if we want a human controlled future, we need to hire and train junior employees even at a cost to short term efficiency.
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This will eventually need government backing, in all likelihood, though there are ways to create junior talent pipelines using philanthropic methods (prizes, games ecosystems, etc.). We've written about this, link below.
I agree that if we want a human controlled future, we need to hire and train junior employees even at a cost to short term efficiency.
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If you're looking for something to pitch to a grant-maker, there's some low hanging fruit here for protecting human autonomy. joanobryan.com/wp-content/up…
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Joan Eleanor O'Bryan retweeted
i’m at reagan national airport right now, and i noticed a lot of kids, adults, and airport staff wearing these “wings for all” shirts. looked it up and it’s v cool — it’s a program that gives folks w/ cognitive and physical disabilities a “dress rehearsal” day at the airport, so they can practice: - checking in, - going through TSA, and - finding a gate and boarding now i kinda think every industry needs some version of this? looks like WMATA offers a free program called Metro Ready for that purpose, glad to see it.
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Joan Eleanor O'Bryan retweeted
I think a lot of people who have become worried about AI risk in the last few months are still really sleeping on BlueDot as a place to get up to speed fast. Got this nice message a few days ago
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Joan Eleanor O'Bryan retweeted
As I've put it elsewhere, man was not made only to have hobbies.
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This should result in a submission ban. We need to ban slop. We need to do it soon. We can't tell students not to turn in slop if we allow our colleagues to do it.
I thought ppl were exaggerating about ICLR slop deluge but I legitimately had a paper in my ICLR batch containing meta commentary from the authoring LLM saying that the results in the paper do not match the paper's claims and are not statistically significant LMAO
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Joan Eleanor O'Bryan retweeted
Even before the slopocalypse, peer review and publishing in general in work on AI was broken. Everyone complains about it; here's to doing something about it instead. This journal will, I hope, become an invaluable source of trusted research on AI alignment, and give researchers working on this topic a thoughtful, constructive review process, a hopefully large audience, and opportunities for awards that can help them to build career capital. Proud to be making a start, please submit your papers, and volunteer to review.
The Alignment Journal publishes research on the scientific foundations of understanding, predicting, and steering artificial intelligent systems. As of today, submissions are open to everyone. What we do differently: - We pay reviewers, with bonuses for speed and insight. - Review discussion is confidential, but every accepted paper is published with a “review summary” to distill the insights generated. - Each paper is judged against our acceptance bar, not against other submissions. - Papers under review are listed publicly, and researchers can nominate themselves to review, so each paper can reach the reviewers who know the topic best. We seek work that builds theoretical or otherwise principled analyses of agency, robustness, incentives, interpretability, generalization, and long-term behavior, and whose significance survives the deletion of any particular model, dataset or benchmark. Empirical investigations of such ideas are welcome, and negative results are encouraged. We are especially interested in approaches that could apply to future superintelligent systems that interact and self-improve. You can submit your preprint in any format. Submissions are rolling and open now on the website. If you are instead interested in reviewing or serving as an action editor (basically: an area chair), create an account on our website. Links to submit, our scope and the reasoning behind the Journal are in the reply ⬇️
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Joan Eleanor O'Bryan retweeted
I strongly recommend everyone reads Nathan’s back and forth with Dario. Nathan works at Encode, an AI safety advocacy organisation. Nathan argues that Anthropic’s behavior does not align with its founding principles, and imposes unacceptable risk of death on all of humanity, including everyone you know and love. Dario leads Anthropic, a company racing to build AIs more powerful than all of humanity. He argues they’re behaving in line with their original strategy of “racing to the top”, ie pushing for frontier AI companies to build super powerful AI systems “safely” by being at the frontier and investing a lot into safety research. I believe Anthropic’s actions are mostly in line with Dario’s original “racing to the top” strategy - I just don’t think that strategy leads to a good outcome for humanity.
Dario — Thank you for taking the time to respond to my previous post. I think it's great when this kind of engagement happens in public rather than on company Slacks, and I hope to see more of it. I agree that Anthropic isn't best modeled as a profit-maximizer. Your post gave several compelling examples of Anthropic taking competitive hits for safety, and insofar as my previous post suggested otherwise, that's on me. But I don't think I made my main point as clearly as I could have, so let me try again. It comes down to four key claims: 1. Anthropic seems to be racing at breakneck speed to build recursively self-improving superintelligence (RSI). By its own lights, that could kill billions of people or literally destroy the world. 2. Risking destroying the world is very hard to justify. It is only conceivably acceptable if serious attempts to put RSI under robust societal governance are failing. 3. Far from meeting that burden, Anthropic, when push comes to shove, often works to keep governments from tying its hands. It seems to care much more about preventing government overreach than about reducing the risk that it and other AI companies will destroy the world. 4. Even if the AEGIS Act really was an honest mix-up, as you suggest, that is itself a serious problem. It suggests Anthropic isn't treating the governance of this technology with anything close to the gravity it deserves. In greater detail for those who want it: 1. Anthropic is racing to RSI, and by its own lights that is insanely risky. Launching RSI could literally destroy the world. That's according to you, your co-founders, and most of your safety staff and capabilities researchers, not to mention many AI researchers outside your walls. You are intentionally trying to create generally intelligent systems more capable than all humans that you claim in six to twelve months “could be capable” of taking over the entire internet before we have the ability to reliably monitor, control, or align them. “Succeeding” at RSI could kill or permanently disempower billions of people in the near future, including me and everyone I love. Yet Anthropic’s primary focus seems to be marshalling an immense amount of resources and talent in a race to get there first. 2. Risking destroying the world carries an enormous burden of justification. I believe the vast majority of people do not want Anthropic to do this (to the extent they know what it's doing). Imposing even a modest chance of catastrophe on billions of people who never consented requires an extraordinary justification. The central one Anthropic has offered: someone will build RSI regardless, so it's better for a safety-focused lab to be at the front of the pack, using that position to support strong AI governance. (Other reasons Anthropic has given, like modestly accelerating improvements in healthcare or economic growth, don’t seem remotely proportionate to the risks Anthropic is imposing by its own lights.) But that argument only works as a last resort. Racing to RSI is only conceivably okay if attempts to institute robust societal governance to manage that race are failing despite your best efforts. A lab that relies on this justification should be a strong, consistent supporter of efforts to enact governance that could bind it, including governance that could slow it and significantly constrain what it does. 3. Rather than supporting efforts at strong regulation, Anthropic has intervened to keep governments from tying its hands. Anthropic has sometimes helped: it played a very helpful role in passing transparency bills in Illinois and ongoing efforts in Massachusetts, and I'm sincerely appreciative. But transparency is far from enough for a technology that will be the world's most powerful superweapon at best, and an uncontrollable swarm of lethally superintelligent agents at worst. When it matters most, Anthropic has often pushed for weak regulation. The AEGIS Act is the most obvious example. No highly risky industry is regulated as anemically as AEGIS would regulate frontier AI: not nuclear, not banking, not aviation, not food safety, not the manufacture of explosives. In all of those industries, specialist regulators can address unsafe practices well before they cause harm. AEGIS would bar the federal government from intervening to block unsafe development or deployment of models until there is an "imminent risk" of catastrophic harm, and would require it to meet a demanding burden of proof in court. Worse, AEGIS would also prevent states from picking up the slack. This design makes perfect sense if you're a company trying to minimize the risk that the government can overly constrain you. It makes little sense if you want American democracy to govern frontier AI effectively. This isn't the first time. The initial version of California's SB 1047 would have let the Attorney General sue to stop developers like Anthropic from imposing unreasonable risks of catastrophic harm. It would also have created a regulatory agency to help set safety standards. Anthropic objected, and helped get both provisions removed before ultimately offering some support for the bill (which I also genuinely appreciate). I’m not saying that Anthropic should have supported 1047 in its initial form; that’s a complex issue and I realize there were questions about whether earlier versions of the bill were less politically feasible. Still, in Anthropic's own words, it helped weaken the bill because "[t]here is a substantial risk that the bill and state agencies will simply be wrong about what is actually effective in preventing catastrophic risk, leading to ineffective and/or burdensome compliance requirements." The same goes for New York's RAISE Act, whose initial version also would have let the Attorney General sue to stop unreasonable risks of catastrophic harm. Anthropic credits itself as a supporter of RAISE, but it did not support the bill while it was in the legislature, including when it nearly died. After the bill passed the legislature, Anthropic publicly critiqued it, saying "Any state proposals should be narrowly focused on transparency and not overly prescriptive." Why does Anthropic consistently take the risk of clumsy government action far more seriously than its own repeated warnings that companies like Anthropic will literally destroy the world by racing to RSI? 4. Even if AEGIS was an honest mix-up, that is itself a serious problem. Your response frames AEGIS as an early draft and a miscommunication. Perhaps you would have strengthened it and narrowed its preemption. (That wouldn't explain Anthropic's interventions to weaken SB 1047 or RAISE, but leave that aside.) Suppose that's exactly right. A federal framework for governing RSI is one of the highest-stakes documents your company will touch. Your post admits Anthropic "could have handled [these matters] better," but its tone ("This kind of thing happens a lot in large organizations") doesn't reflect the gravity of this issue. Anthropic talks about the need for “operational excellence” in critical areas, and I have a hard time believing that a similarly cavalier attitude would be tolerated while Anthropic was negotiating a key compute deal or preparing its next large pre-training run. In short The justification for racing rests on Anthropic fighting for strong governance, and Anthropic's record on regulation points the other way. Together with its breakneck racing, that fits a much darker picture of the company than the one that seems to prevail among your employees. I hope that Anthropic reflects on this picture, supports stronger regulation, exercises extraordinary caution when advocating for weak regulation, and doubles down on its founding purpose of helping the world safely navigate transformative AI together, instead of prioritizing Anthropic’s ability to win a race that imposes intolerable risks on everyone alive.
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