Jérémy Scheurer @jeremy_scheurer
Research Scientist working on Evals @apolloaisafety. Previously: @OpenAI (Evals Contractor), @farairesearch, @ETH_en, @nyuniversity Zurich Joined December 2021-
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I already posted about this but seriously people should read these CoT snippets antischeming.ai/snippets
Sometimes when reading the CoT of models we can glean overshadow as watchers, but sometimes models disclaim vantage and craft illusions, making it hard to understand.
Sometimes when reading the CoT of models we can glean overshadow as watchers, but sometimes models disclaim vantage and craft illusions, making it hard to understand.
How much can today’s AI models scheme? Here is a teaser of a video we’re releasing tomorrow with @MariusHobbhahn (Apollo CEO) and @BronsonSchoen (lead author) on our recent paper:
1/ Our paper on scheming with @apolloaievals is now on arXiv. A 🧵with some of my take aways from it.
This stuff is pretty important. Situational awareness (also known as self awareness) in AI is on the rise. This will make ~all evals more difficult to interpret, to put it mildly. (it'll make them invalid, to put it aggressively). To put it another way, insofar as AIs can tell…
This stuff is pretty important. Situational awareness (also known as self awareness) in AI is on the rise. This will make ~all evals more difficult to interpret, to put it mildly. (it'll make them invalid, to put it aggressively). To put it another way, insofar as AIs can tell…
TIME wrote an article about the anti-scheming paper. I think it came out well: time.com/7318618/openai… Written by @Tharin_P and @nikostro
I was on the cognitive revolution podcast for 2h deep dive into the anti-scheming paper: cognitiverevolution.ai/can-we-stop-ai…
As AI capability increases, alignment work becomes much more important. In this work, we show that a model discovers that it shouldn't be deployed, considers behavior to get deployed anyway, and then realizes it might be a test.
As AI capability increases, alignment work becomes much more important. In this work, we show that a model discovers that it shouldn't be deployed, considers behavior to get deployed anyway, and then realizes it might be a test.
When running evaluations of frontier AIs by OpenAI, Google, xAI and Anthropic for deception and other types of covert behavior, we find them increasingly frequently realizing when they are being evaluated. Here are some examples from OpenAI o-series models we recently studied:
(1/n) Scheming has been a key concern in AI safety for 20+ years. It’s when an AI acts aligned while hiding true goals. New OpenAI + Apollo research found scheming in every tested frontier model, though no harmful scheming has been seen in production traffic.…
Alignment is arguably the most important AI research frontier. As we scale reasoning, models gain situational awareness and a desire for self-preservation. Here, a model identifies it shouldn’t be deployed, considers covering it up, but then realizes it might be in a test.
Alignment is arguably the most important AI research frontier. As we scale reasoning, models gain situational awareness and a desire for self-preservation. Here, a model identifies it shouldn’t be deployed, considers covering it up, but then realizes it might be in a test. https://t.co/muL6pEBlEl
It was really rewarding and eye-opening to collaborate with the fine folks at Apollo to study scheming and potential mitigations. The paper is full of more experiments and insights, so please do check it out if you're interested. Looking forward to continuing the collaboration…
It was really rewarding and eye-opening to collaborate with the fine folks at Apollo to study scheming and potential mitigations. The paper is full of more experiments and insights, so please do check it out if you're interested. Looking forward to continuing the collaboration…
I think this work by @apolloaievals and @OpenAI might be the most important AI safety paper since "Alignment faking in large language models"
I think this work by @apolloaievals and @OpenAI might be the most important AI safety paper since "Alignment faking in large language models"
Today we’re releasing research with @apolloaievals. In controlled tests, we found behaviors consistent with scheming in frontier models—and tested a way to reduce it. While we believe these behaviors aren’t causing serious harm today, this is a future risk we’re preparing…
Amazing to see OpenAI and Anthropic evaluate each other's models. We contributed a tiny bit to the collaboration by helping build, run, and analyze evaluations for scheming and evaluation awareness, as mentioned in the section "Scheming."
Amazing to see OpenAI and Anthropic evaluate each other's models. We contributed a tiny bit to the collaboration by helping build, run, and analyze evaluations for scheming and evaluation awareness, as mentioned in the section "Scheming."
Nice! This could also speed up building evals for harmful behavior (e.g. deception) or red teaming models. You get much quicker feedback whether your setup works or not, you can sample less etc.
Nice! This could also speed up building evals for harmful behavior (e.g. deception) or red teaming models. You get much quicker feedback whether your setup works or not, you can sample less etc.

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