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Reposting from LessWrong, for people who might be less active there:[1]
TL;DR
- FrontierMath was funded by OpenAI[2]
- This was not publicly disclosed until December 20th, the date of OpenAI's o3 announcement, including in earlier versions of the arXiv paper where this was eventually made public.
- There was allegedly no active communication about this funding to the mathematicians contributing to the project before December 20th, due to the NDAs Epoch signed, but also no communication after the 20th, once the NDAs had expired.
- OP claims that "I have heard second-hand that OpenAI does have access to exercises and answers and that they use them for validation. I am not aware of an agreement between Epoch AI and OpenAI that prohibits using this dataset for training if they wanted to, and have slight evidence against such an agreement existing."
- Seems to have confirmed the OpenAI funding + NDA restrictions
- Claims OpenAI has "access to a large fraction of FrontierMath problems and solutions, with the exception of a unseen-by-OpenAI hold-out set that enables us to independently verify model capabilities."
- They also have "a verbal agreement that these materials will not be used in model training."
Edit (19/01): Elliot (the project lead) points out that the holdout set does not yet exist (emphasis added):
As for where the o3 score on FM stands: yes I believe OAI has been accurate with their reporting on it, but Epoch can't vouch for it until we independently evaluate the model using the holdout set we are developing.[3]
Edit (24/01):
Tamay tweets an apology (possibly including the timeline drafted by Elliot). It's pretty succinct so I won't summarise it here! Blog post version for people without twitter. Perhaps the most relevant point:
OpenAI commissioned Epoch AI to produce 300 advanced math problems for AI evaluation that form the core of the FrontierMath benchmark. As is typical of commissioned work, OpenAI retains ownership of these questions and has access to the problems and solutions.
Nat from OpenAI with an update from their side:
- We did not use FrontierMath data to guide the development of o1 or o3, at all.
- We didn't train on any FM derived data, any inspired data, or any data targeting FrontierMath in particular
- I'm extremely confident, because we only downloaded frontiermath for our evals *long* after the training data was frozen, and only looked at o3 FrontierMath results after the final announcement checkpoint was already picked .
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Some quick uncertainties I had:
- What does this mean for OpenAI's 25% score on the benchmark?
- What steps did Epoch take or consider taking to improve transparency between the time they were offered the NDA and the time of signing the NDA?
- What is Epoch's level of confidence that OpenAI will keep to their verbal agreement to not use these materials in model training, both in some technically true sense, and in a broader interpretation of an agreement? (see e.g. bottom paragraph of Ozzi's comment).
- In light of the confirmation that OpenAI not only has access to the problems and solutions but has ownership of them, what steps did Epoch consider before signing the relevant agreement to get something stronger than a verbal agreement that this won't be used in training, now or in the future?
- ^
Epistemic status: quickly summarised + liberally copy pasted with ~0 additional fact checking given Tamay's replies in the comment section
- ^
arXiv v5 (Dec 20th version) "We gratefully acknowledge OpenAI for their support in creating the benchmark."
- ^
See clarification in case you interpreted Tamay's comments (e.g. that OpenAI "do not have access to a separate holdout set that serves as an additional safeguard for independent verification") to mean that the holdout set already exists
Note that the hold-out set doesn't exist yet. https://x.com/ElliotGlazer/status/1880812021966602665
What does this mean for OpenAI's 25% score on the benchmark?
Note that only some of FrontierMath's problems are actually frontier, while others are relatively easier (i.e. IMO level, and Deepmind was already one point from gold on IMO level problems) https://x.com/ElliotGlazer/status/1870235655714025817
Some very quick thoughts from EY's TIME piece from the perspective of someone ~outside of the AI safety work. I have no technical background and don't follow the field closely, so likely to be missing some context and nuance; happy to hear pushback!
Shut down all the large training runs. Put a ceiling on how much computing power anyone is allowed to use in training an AI system, and move it downward over the coming years to compensate for more efficient training algorithms. No exceptions for governments and militaries. Make immediate multinational agreements to prevent the prohibited activities from moving elsewhere. Track all GPUs sold. If intelligence says that a country outside the agreement is building a GPU cluster, be less scared of a shooting conflict between nations than of the moratorium being violated; be willing to destroy a rogue datacenter by airstrike.
Frame nothing as a conflict between national interests, have it clear that anyone talking of arms races is a fool. That we all live or die as one, in this, is not a policy but a fact of nature. Make it explicit in international diplomacy that preventing AI extinction scenarios is considered a priority above preventing a full nuclear exchange, and that allied nuclear countries are willing to run some risk of nuclear exchange if that’s what it takes to reduce the risk of large AI training runs.
- My immediate reaction when reading this was something like "wow, is this representative of AI safety folks? Are they willing to go to any lengths to stop AI development?". I've heard anecdotes of people outside of all this stuff saying this piece reads like a terrorist organisation, for example, which I think is a stronger term than I'd describe, but I think suggestions like this does unfortunately play into potential comparisons to ecofascists.
- As someone seen publicly to be a thought leader and widely regarded as a founder of the field, there are some risks to this kind of messaging. It's hard to evaluate how this trades off, but I definitely know communities and groups that would be pretty put off by this, and it's unclear how much value the sentences around willingness to escalate nuclear war are actually adding.
- It's an empirical Q about how to tradeoff between risks from nuclear war and risks from AI, but the claim of "preventing AI extinction is a priority above a nuclear exchange" is ~trivially true; the reverse is also true: "preventing extinction from nuclear war is a priority above preventing AI training runs". Given the difficulty of illustrating and defending a position that the risks of AI training runs is substantially higher than that of a nuclear exchange to the general public, I would have erred on the side of caution when saying things that are as politically charged as advocating for nuclear escalation (or at least something can be interpreted as such).
- I wonder which superpower EY trusts to properly identify a hypothetical "rogue datacentre" that's worthy of a military strike for the good of humanity, or whether this will just end up with parallels to other failed excursions abroad 'for the greater good' or to advance individual national interests.
- If nuclear weapons are a reasonable comparison, we might expect limitations to end up with a few competing global powers to have access to AI developments, and countries that do not. It seems plausible that criticism around these treaties being used to maintain the status quo in the nuclear nonproliferation / disarmament debate may be applicable here too.
- Unlike nuclear weapons (though nuclear power may weaken this somewhat), developments in AI has the potential to help immensely with development and economic growth.
- Thus the conversation may eventually bump something that looks like:
- Richer countries / first movers that have obtained significant benefits of AI take steps to prevent other countries from catching up.[1]
- Rich countries using the excuse of preventing AI extinction as a guise to further national interests
- Development opportunities from AI for LMICs are similarly hindered, or only allowed in a way that is approved by the first movers in AI.
- Given the above, and that conversations around and tangential to AI risk already receive some pushback from the Global South community for distracting and taking resources away from existing commitments to UN Development Goals, my sense is that folks working in AI governance / policy would likely strongly benefit from scoping out how these developments are affecting Global South stakeholders, and how to get their buy-in for such measures.
(disclaimer: one thing this gestures at is something like - "global health / development efforts can be instrumentally useful towards achieving longtermist goals"[2], which is something I'm clearly interested in as someone working in global health. While it seems rather unlikely that doing so is the best way of achieving longtermist goals on the margin[3], it doesn't exclude some aspect of this in being part of a necessary condition for important wins like an international treaty, if that's what is currently being advocated for. It is also worth mentioning because I think this is likely to be a gap / weakness in existing EA approaches).
Curated and popular this week
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Around 1 month ago, I wrote a similar Forum post on the Easterlin Paradox. I decided to take it down because: 1) after useful comments, the method looked a little half-baked; 2) I got in touch with two academics – Profs. Caspar Kaiser and Andrew Oswald – and we are now working on a paper together using a related method.
That blog post actually came to the opposite conclusion, but, as mentioned, I don't think the method was fully thought through.
I'm a little more confident about this work. It essentially summarises my Undergraduate dissertation. You can read a full version here. I'm hoping to publish this somewhere, over the Summer. So all feedback is welcome.
TLDR
* Life satisfaction (LS) appears flat over time, despite massive economic growth — the “Easterlin Paradox.”
* Some argue that happiness is rising, but we’re reporting it more conservatively — a phenomenon called rescaling.
* I test this hypothesis using a large (panel) dataset by asking a simple question: has the emotional impact of life events — e.g., unemployment, new relationships — weakened over time? If happiness scales have stretched, life events should “move the needle” less now than in the past.
* That’s exactly what I find: on average, the effect of the average life event on reported happiness has fallen by around 40%.
* This result is surprisingly robust to various model specifications. It suggests rescaling is a real phenomenon, and that (under 2 strong assumptions), underlying happiness may be 60% higher than reported happiness.
* There are some interesting EA-relevant implications for the merits of material abundance, and the limits to subjective wellbeing data.
1. Background: A Happiness Paradox
Here is a claim that I suspect most EAs would agree with: humans today live longer, richer, and healthier lives than any point in history. Yet we seem no happier for it. Self-reported life satisfaction (LS), usually measured on a 0–10 scale, has remained remarkably flat over the last f
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We’ve redesigned effectivealtruism.org to improve understanding and perception of effective altruism, and make it easier to take action.
View the new site →
I led the redesign and will be writing in the first person here, but many others contributed research, feedback, writing, editing, and development. I’d love to hear what you think, here is a feedback form.
Redesign goals
This redesign is part of CEA’s broader efforts to improve how effective altruism is understood and perceived. I focused on goals aligned with CEA’s branding and growth strategy:
1. Improve understanding of what effective altruism is
Make the core ideas easier to grasp by simplifying language, addressing common misconceptions, and showcasing more real-world examples of people and projects.
2. Improve the perception of effective altruism
I worked from a set of brand associations defined by the group working on the EA brand project[1]. These are words we want people to associate with effective altruism more strongly—like compassionate, competent, and action-oriented.
3. Increase impactful actions
Make it easier for visitors to take meaningful next steps, like signing up for the newsletter or intro course, exploring career opportunities, or donating.
We focused especially on three key audiences:
* To-be direct workers: young people and professionals who might explore impactful career paths
* Opinion shapers and people in power: journalists, policymakers, and senior professionals in relevant fields
* Donors: from large funders to smaller individual givers and peer foundations
Before and after
The changes across the site are aimed at making it clearer, more skimmable, and easier to navigate. Here are some side-by-side comparisons:
Landing page
Some of the changes:
* Replaced the economic growth graph with a short video highlighting different cause areas and effective altruism in action
* Updated tagline to "Find the best ways to help others" based on testing by Rethink
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Summary
I’m excited to announce a “Digital Sentience Consortium” hosted by Longview Philanthropy, in collaboration with The Navigation Fund and Macroscopic Ventures, to support research and applied projects focused on the potential consciousness, sentience, moral status, and experiences of artificial intelligence systems. The opportunities include research fellowships, career transition fellowships, and a broad request for proposals for applied work on these topics.
For years, I’ve thought this area was seriously overlooked. It now has growing interest. Twenty-two out of 123 pages of Claude 4’s model card are about its potential moral patienthood. Scientific experts increasingly say that near-term AI sentience is a real possibility; even the skeptical neuroscientist Anil Seth says, “it is unwise to dismiss the possibility altogether.” We’re hoping to bring new people and projects into the field to increase the chance that society deals with the possibility of digital sentience reasonably, and with concern for all involved.
* Apply to Research Fellowship
* Apply to Career Transition Fellowship
* Apply to Request for Proposals
Motivation & Focus
For about as long as I’ve been reading about transformative AI, I’ve wondered whether society would face critical decisions involving AI sentience. Until recently, I thought there was not much to be done here besides perhaps more philosophy of mind and perhaps some ethics—and I was not sure these approaches would make much progress.
Now, I think there are live areas where people can contribute:
* Technically informed research on which AI systems are sentient, like this paper applying existing theories of consciousness to a few AI architectures.
* Innovative approaches to investigate sentience, potentially in a way that avoids having to take a stand on a particular theory of consciousness, like work on AI introspection.
* Political philosophy and policy research on the proper role of AI in society.
* Work to ed