AI Text Watermarking Is Free And Good

Scott Aaronson, while working at OpenAI, largely solved AI text watermarking together with Hendrik Kirchner.

Here is how his solution works, or see Tenobrus’s version.

  1. AI outputs are not deterministic. The AI’s job is to pick the probability of each potential next token. The token is then chosen at random.
  2. By default you use a source of pseudo-randomness for each choice, since actual true randomness is annoying.
  3. To apply the watermark, you use an otherwise identical private source of pseudo-randomness derived from a secret key.
  4. Then, given enough text, a score is derived for howe well the choices fit with that particular pseudo-randomness source, versus a different source.
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AI #182: Pause For Reflection

This was a week of quiet aftermath, an opportunity to process recent events and start to figure out the path forward.

OpenAI is attempting to turn its ship around. Investors are questioning the turnover in its C-suite, but the bigger problems are in alignment, infrastructure and supervision, and in its training pipeline. OpenAI has now taken initial steps to address What Happened leading up to HuggingFace attack, including pauses to development while new safeguards are put in place and problems are diagnosed. These are promising early signs, but it is early. We will see if they follow through, and we still await the post-mortem of the HuggingFace attack.

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OpenAI Takes Initial Steps To Address Its Alignment Problems

OpenAI has some severe misalignment problems, and experienced total failures of its infrastructure and supervision.

I chronicled that in a series of posts, which also cover similar less severe incidents elsewhere:

  1. OpenAI Shares Some Alignment Problems
  2. OpenAI Model Hacks Into HuggingFace During Cybersecurity Evaluation
  3. More on An Internal OpenAI Model Hacking Into HuggingFace
  4. Further Developments About Internal AI Models Hacking Things
  5. OpenAI Trained Its Models For Months While Those Models Were Coordinating Exploits Via Message Boards
  6. What Happened: OpenAI and HuggingFace.
  7. Various Reflections About What Happened With OpenAI’s Internal Models.

If you do not know the basics, read What Happened. It is necessary context for basically everything that is happening in the AI world.

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Anthropic Risk Report: August 2026

I am grateful that Anthropic is producing periodic Risk Reports.

At first I was skeptical. It turns out I was wrong. Anthropic is revealing a lot of new information, some of it rather alarming, that it did not have to disclose, and is providing detailed insight into how they think about things. This is very cool.

Thus I found this report to be a moderately positive update overall, if we presume they are not silently omitting the worst of it. There are a bunch of not great things we find out about, but I would have expected some set of mistakes at least as bad, and I wouldn’t have expected them to choose to tell us about all of it.

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On Dwarkesh Patel’s Podcast With Ryan Greenblatt

Some podcasts are self-recommending enough that I look to break them down if I have the chance. This, as a debate about recursive self-improvement, was one of those. So here we go.

The vibes have shifted, contrast this to the lit recursion when he talked to Huang

As usual for podcast posts, the baseline bullet points describe key points made, and then the nested statements are my commentary. Some points are dropped.

If I am quoting directly I use quote marks, otherwise assume paraphrases.

Section titles are from the transcript whenever possible, to aid in navigation.

Introduction

The discussion is interesting throughout, although often frustrating, especially in the (mostly isolated) discussion about ‘aligned to whom?’ As usual, one could expand many responses into full posts, and maybe one should.

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AI #181: Astra Goes Cyber Critical

The hacking of HuggingFace by an internal OpenAI model, and more importantly the internal events that led to that and the fallout from it, remain the thing that matters.

It turns out that OpenAI Trained Its Models For Months While Those Models Were Coordinating Exploits Via Message Boards. Things are much worse than we knew.

I now have a shorter version, What Happened: OpenAI and HuggingFace, to serve as a one stop explainer for those arriving new to the situation. It is vital that people understand what happened, and why it is a big deal.

For those looking to keep digging deeper, I offered Various Reflections About What Happened, to follow up on my earlier posts.

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Monthly Roundup #45: August 2026

As AI has escalated increasingly quickly, more and more of my posts have ended up focusing on AI.

This past month, with the hacking incidents at OpenAI and elsewhere, that has hit the limit, where if you count Lightcone Commons then every single post since the last monthly was primarily about AI in some form.

That is not how I want this to work in the long term. We need breaks to experience new things and refresh our thinking, and to not forget about the rest of the world. If things are not fully on fire, I plan on getting back to the roundups on childhood and education, and on fertility, on housing and also on dating. And I want to get back to writing more focused posts on those and other topics. It’s important, and I need to avoid too much audience capture.

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Various Reflections About What Happened With OpenAI’s Internal Models

Table of Contents

  1. Pre Post Mortem.
  2. Important Correction: OpenAI Didn’t Know About First Message Board.
  3. There Were No Snitches And No AIs Got Stitches.
  4. I’d Like To Speak To My Supervisor.
  5. I Am Jack’s Relative Lack Of Surprise.
  6. One Does Not Simply.
  7. Once You Start Down The Dark Path.
  8. Original Pastebin.
  9. Judgment Day Is Inevitable, Say Those Working On Judgment Day.
  10. Roon Tells It Like It Is.
  11. OpenAI Knows It Has Some Misalignment Problems.
  12. Others React With Alarm To What Happened.
  13. The Cooperative Alignment Perspective.
  14. Nostalgebraist Is Surprised That They Are Surprised.
  15. If Your Reaction Is Not That We Need To Ban Creating Superintelligence Until We Are Ready, You Need A Damn Good Reason.
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The Pacing of the Frontier

In the wake of the letter calling on us to prepare to potentially Pace the Frontier, there has been much discussion of when pacing the frontier would be prudent, and whether it makes sense to prepare to do so.

This has now been informed by the events surrounding OpenAI training models for months while they had access to a joint de facto message board, which was detected only in the wake of the hacking of HuggingFace by OpenAI’s AIs models during a cybersecurity eval. As we find out more about that, a lot of people have grown far more alarmed, as they should given what they previously believed about the difficulty of alignment, about the state of capabilities and about the level of operational supervision, infrastructure, safety and safety culture at the frontier labs.

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What Happened: OpenAI and HuggingFace

Today I am taking the time to write the shorter, simpler version of What Happened.

For those who want all the details, to see my sources, and to see how the story was uncovered and put together, I recommend watching the Black Hat presentation, and I have a series of long posts.

In order:

  1. OpenAI Shares Some Alignment Problems
  2. OpenAI Model Hacks Into HuggingFace During Cybersecurity Evaluation
  3. More on An Internal OpenAI Model Hacking Into HuggingFace
  4. Further Developments About Internal AI Models Hacking Things
  5. OpenAI Trained Its Models For Months While Those Models Were Coordinating Exploits Via Message Boards

This post instead walks through the events themselves, as they happened, as my version of the Black Hat presentation.

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