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Paul Christiano - Alignment Forum Author Page
webalignment.org·alignment.org/author/paul/
Paul Christiano is one of the most influential technical AI safety researchers; his author page collects writings foundational to modern alignment research including scalable oversight and RLHF.
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Summary
Author page for Paul Christiano on alignment.org, aggregating his published work on AI alignment. Paul Christiano is a prominent AI safety researcher known for foundational contributions including RLHF, debate, and iterated amplification. This page serves as a hub for his technical alignment writings.
Key Points
- •Paul Christiano is a leading AI alignment researcher, formerly at OpenAI and founder of the Alignment Research Center (ARC).
- •Known for developing influential alignment proposals including Reinforcement Learning from Human Feedback (RLHF), debate, and iterated amplification.
- •His work focuses on scalable oversight, eliciting latent knowledge, and ensuring AI systems are honest and corrigible.
- •Contributions span both theoretical alignment proposals and practical safety techniques now widely used in industry.
- •This page indexes his blog posts and technical writings on alignment-related topics.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| Sharp Left Turn | Risk | 69.0 |
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# Paul Christiano [https://paulfchristiano.com/](https://paulfchristiano.com/)[Paul Christiano](https://www.alignment.org/author/paul/rss) Paul Christiano has published **14 posts**: Earlier this year ARC posted a prize for two matrix completion problems. We received a number of submissions we considered useful, but not any complete solutions. We are closing the contest and awarding … [»](https://www.alignment.org/blog/matrix-completion-prize-results/) * * * The Alignment Research Center’s Theory team is starting a new hiring round for researchers with a theoretical background. Please apply here. Update January 2024: we have paused hiring and expect to reopen … [»](https://www.alignment.org/blog/arc-is-hiring-theoretical-researchers/) * * * Here are two self-contained algorithmic questions that have come up in our research. We're offering a bounty of $5k for a solution to either of them—either an algorithm, or a … [»](https://www.alignment.org/blog/prize-for-matrix-completion-problems/) * * * This post is an elaboration on “tractability of discrimination” as introduced in section III of "Can we efficiently explain model behaviors? For an overview of the general plan this fits into, see "Mechanistic anomaly detection" and "Finding gliders in the game of life". … [»](https://www.alignment.org/blog/can-we-efficiently-distinguish-different-mechanisms/) * * * Finding explanations is a relatively unambitious interpretability goal. If it is intractable then that’s an important obstacle to interpretability in general. If we formally define “explanations,” then finding them is a well-posed search problem and there is a plausible argument for tractability. … [»](https://www.alignment.org/blog/can-we-efficiently-explain-model-behaviors/) * * *  ARC’s current approach to ELK is to point to latent structure within a model by searching for the “reason” for particular correlations in the model’s output. In this post we’ll walk through a very simple example of using this approach to identify gliders in the game of life. … [»](https://www.alignment.org/blog/finding-gliders-in-the-game-of-life/) * * * An informal description of ARC’s current research approach, follow-up to Eliciting Latent Knowledge … [»](https://www.alignment.org/blog/mechanistic-anomaly-detection-and-elk/) * * *
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