1985–, AI policy researcher, journalist; co-founder of Anthropic
Jack Clark is an AI policy researcher and writer, and one of the co-founders of Anthropic (2021). At Anthropic he leads the policy team, which engages with governments, AI Safety Institutes (UK, US, EU, Japan, Singapore) and international bodies on the governance of frontier AI systems. He has been a regular witness to government and parliamentary committees on AI safety, including the US Senate Judiciary Committee and the UK House of Lords, and has been a central figure in the Bletchley and Seoul AI Safety Summit processes.
Before Anthropic, Clark was Policy Director at OpenAI (2017–2020), where he established the policy function and worked on releases including GPT-2 (whose staged release approach to dual-use capabilities he co-designed) and the founding of the AI Index. Before OpenAI he was a technology journalist at Bloomberg News (2014–2017), covering machine learning and the early commercialisation of deep learning. Since 2016 he has written the long-running weekly newsletter Import AI, which is widely read across the research and policy communities for its concise weekly summaries of new papers, model releases and policy events.
Clark is also a former Co-Chair of the AI Index at Stanford HAI and has served on the National AI Advisory Committee advising the US President. His public commentary and Senate testimony have framed AI safety not as a brake on progress but as the work required to make progress legitimate, and have shaped much of the bipartisan US conversation about responsible scaling, evaluations and pre-deployment testing.
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Related people: Dario Amodei, Daniela Amodei, Christopher Olah
Works cited in this book:
- Language Models are Few-Shot Learners (2020) (with Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei)
- Learning Transferable Visual Models From Natural Language Supervision (2021) (with Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Gretchen Krueger, Ilya Sutskever)
- Predictability and Surprise in Large Generative Models (2022) (with Deep Ganguli, Danny Hernandez, Liane Lovitt, Nova DasSarma, Tom Henighan, Andy Jones, Nicholas Joseph, Jackson Kernion, Ben Mann, Amanda Askell, Yuntao Bai, Anna Chen, Tom Conerly, Dawn Drain, Nelson Elhage, Sheer El Showk, Stanislav Fort, Zac Hatfield-Dodds, Scott Johnston, Shauna Kravec, Neel Nanda, Kamal Ndousse, Catherine Olsson, Daniela Amodei, Dario Amodei, Tom Brown, Jared Kaplan, Sam McCandlish, Chris Olah)
- Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned (2022) (with Deep Ganguli, Liane Lovitt, Jackson Kernion, Amanda Askell, Yuntao Bai, Saurav Kadavath, Ben Mann, Ethan Perez, Nicholas Schiefer, Kamal Ndousse, Andy Jones, Sam Bowman, Anna Chen, Tom Conerly, Nova DasSarma, Dawn Drain, Nelson Elhage, Sheer El-Showk, Stanislav Fort, Zac Hatfield-Dodds, Tom Henighan, Danny Hernandez, Tristan Hume, Josh Jacobson, Scott Johnston, Shauna Kravec, Catherine Olsson, Sam Ringer, Eli Tran-Johnson, Dario Amodei, Tom Brown, Nicholas Joseph, Sam McCandlish, Chris Olah, Jared Kaplan)
- In-context Learning and Induction Heads (2022) (with Catherine Olsson, Nelson Elhage, Neel Nanda, Nicholas Joseph, Nova DasSarma, Tom Henighan, Ben Mann, Amanda Askell, Yuntao Bai, Anna Chen, Tom Conerly, Dawn Drain, Deep Ganguli, Zac Hatfield-Dodds, Danny Hernandez, Scott Johnston, Andy Jones, Jackson Kernion, Liane Lovitt, Kamal Ndousse, Dario Amodei, Tom Brown, Jared Kaplan, Sam McCandlish, Chris Olah)
- Discovering Language Model Behaviors with Model-Written Evaluations (2022) (with Ethan Perez, Sam Ringer, Kamile Lukosiute, Karina Nguyen, Edwin Chen, Scott Heiner, Craig Pettit, Catherine Olsson, Sandipan Kundu, Saurav Kadavath, Andy Jones, Anna Chen, Benjamin Mann, Brian Israel, Bryan Seethor, Cameron McKinnon, Christopher Olah, Da Yan, Daniela Amodei, Dario Amodei, Dawn Drain, Dustin Li, Eli Tran-Johnson, Guro Khundadze, Jackson Kernion, James Landis, Jamie Kerr, Jared Mueller, Jeeyoon Hyun, Joshua Landau, Kamal Ndousse, Landon Goldberg, Liane Lovitt, Martin Lucas, Michael Sellitto, Miranda Zhang, Neerav Kingsland, Nelson Elhage, Nicholas Joseph, Noemi Mercado, Nova DasSarma, Oliver Rausch, Robin Larson, Sam McCandlish, Scott Johnston, Shauna Kravec, Sheer El Showk, Tamera Lanham, Timothy Telleen-Lawton, Tom Brown, Tom Henighan, Tristan Hume, Yuntao Bai, Zac Hatfield-Dodds, Samuel R. Bowman, Amanda Askell, Roger Grosse, Danny Hernandez, Deep Ganguli, Evan Hubinger, Nicholas Schiefer, Jared Kaplan)
- Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training (2024) (with Evan Hubinger, Carson Denison, Jesse Mu, Mike Lambert, Meg Tong, Monte MacDiarmid, Tamera Lanham, Daniel M. Ziegler, Tim Maxwell, Newton Cheng, Adam Jermyn, Amanda Askell, Ansh Radhakrishnan, Cem Anil, David Duvenaud, Deep Ganguli, Fazl Barez, Kamal Ndousse, Kshitij Sachan, Michael Sellitto, Mrinank Sharma, Nova DasSarma, Roger Grosse, Shauna Kravec, Yuntao Bai, Zachary Witten, Marina Favaro, Jan Brauner, Holden Karnofsky, Paul Christiano, Samuel R. Bowman, Logan Graham, Jared Kaplan, Sören Mindermann, Ryan Greenblatt, Buck Shlegeris, Nicholas Schiefer, Ethan Perez)
Discussed in:
- Chapter 14: Generative Models, Frontier AI Safety Commitments
- Chapter 15: Modern AI, Modern AI