Problem 11115. - Jack Clark (Am. Math. Mon., 2004)

A Sequence Given in Terms of Harmonic Numbers: 11115. - Jack Clark; Jaime Vinuesa (Am. Math. Mon., 2006)

The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation. - Miles Brundage; Shahar Avin; Jack Clark; Helen Toner; Peter Eckersley; Ben Garfinkel; Allan Dafoe; Paul Scharre; Thomas Zeitzoff; Bobby Filar; Hyrum S. Anderson; Heather Roff; et al. (CoRR, 2018)

Release Strategies and the Social Impacts of Language Models. - Irene Solaiman; Miles Brundage; Jack Clark; Amanda Askell; Ariel Herbert-Voss; Jeff Wu 003; Alec Radford; Jasmine Wang (CoRR, 2019)

Language Models are Few-Shot Learners. - 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; et al. (NeurIPS, 2020)

Regulatory Markets for AI Safety. - Jack Clark; Gillian K. Hadfield (CoRR, 2020)

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. - Miles Brundage; Shahar Avin; Jasmine Wang; Haydn Belfield; Gretchen Krueger; Gillian K. Hadfield; Heidy Khlaaf; Jingying Yang; Helen Toner; Ruth Fong; Tegan Maharaj; Pang Wei Koh; et al. (CoRR, 2020)

Measurement in AI Policy: Opportunities and Challenges. - Saurabh Mishra; Jack Clark; C. Raymond Perrault (CoRR, 2020)

Learning Transferable Visual Models From Natural Language Supervision. - Alec Radford; Jong Wook Kim; Chris Hallacy; Aditya Ramesh; Gabriel Goh; Sandhini Agarwal; Girish Sastry; Amanda Askell; Pamela Mishkin; Jack Clark; Gretchen Krueger; Ilya Sutskever (ICML, 2021)

Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models. - Alex Tamkin; Miles Brundage; Jack Clark; Deep Ganguli (CoRR, 2021)

The AI Index 2021 Annual Report. - Daniel Zhang; Saurabh Mishra; Erik Brynjolfsson; John Etchemendy; Deep Ganguli; Barbara J. Grosz; Terah Lyons; James Manyika; Juan Carlos Niebles; Michael Sellitto; Yoav Shoham; Jack Clark; et al. (CoRR, 2021)

Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications. - Sandhini Agarwal; Gretchen Krueger; Jack Clark; Alec Radford; Jong Wook Kim; Miles Brundage (CoRR, 2021)

Why and How Governments Should Monitor AI Development. - Jess Whittlestone; Jack Clark (CoRR, 2021)

A General Language Assistant as a Laboratory for Alignment. - Amanda Askell; Yuntao Bai; Anna Chen; Dawn Drain; Deep Ganguli; Tom Henighan; Andy Jones; Nicholas Joseph; Benjamin Mann; Nova DasSarma; Nelson Elhage; Zac Hatfield-Dodds; et al. (CoRR, 2021)

Predictability and Surprise in Large Generative Models. - Deep Ganguli; Danny Hernandez; Liane Lovitt; Amanda Askell; Yuntao Bai; Anna Chen; Tom Conerly; Nova DasSarma; Dawn Drain; Nelson Elhage; Sheer El Showk; Stanislav Fort; et al. (FAccT, 2022)

Predictability and Surprise in Large Generative Models. - Deep Ganguli; Danny Hernandez; Liane Lovitt; Nova DasSarma; Tom Henighan; Andy Jones; Nicholas Joseph; Jackson Kernion; Benjamin Mann; Amanda Askell; Yuntao Bai; Anna Chen; et al. (CoRR, 2022)

Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. - Yuntao Bai; Andy Jones; Kamal Ndousse; Amanda Askell; Anna Chen; Nova DasSarma; Dawn Drain; Stanislav Fort; Deep Ganguli; Tom Henighan; Nicholas Joseph; Saurav Kadavath; et al. (CoRR, 2022)

The AI Index 2022 Annual Report. - Daniel Zhang; Nestor Maslej; Erik Brynjolfsson; John Etchemendy; Terah Lyons; James Manyika; Helen Ngo; Juan Carlos Niebles; Michael Sellitto; Ellie Sakhaee; Yoav Shoham; Jack Clark; et al. (CoRR, 2022)

Language Models (Mostly) Know What They Know. - Saurav Kadavath; Tom Conerly; Amanda Askell; Tom Henighan; Dawn Drain; Ethan Perez; Nicholas Schiefer; Zac Hatfield-Dodds; Nova DasSarma; Eli Tran-Johnson; Scott Johnston; Sheer El Showk; et al. (CoRR, 2022)

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned. - Deep Ganguli; Liane Lovitt; Jackson Kernion; Amanda Askell; Yuntao Bai; Saurav Kadavath; Ben Mann; Ethan Perez; Nicholas Schiefer; Kamal Ndousse; Andy Jones; Sam Bowman 001; et al. (CoRR, 2022)

In-context Learning and Induction Heads. - Catherine Olsson; Nelson Elhage; Neel Nanda; Nicholas Joseph; Nova DasSarma; Tom Henighan; Ben Mann; Amanda Askell; Yuntao Bai; Anna Chen; Tom Conerly; Dawn Drain; et al. (CoRR, 2022)

Discovering Language Model Behaviors with Model-Written Evaluations. - Ethan Perez; Sam Ringer; Kamile Lukosiute; Karina Nguyen; Edwin Chen; Scott Heiner; Craig Pettit; Catherine Olsson; Sandipan Kundu; Saurav Kadavath; Andy Jones; Anna Chen; et al. (CoRR, 2022)

Discovering Language Model Behaviors with Model-Written Evaluations. - Ethan Perez; Sam Ringer; Kamile Lukosiute; Karina Nguyen; Edwin Chen; Scott Heiner; Craig Pettit; Catherine Olsson; Sandipan Kundu; Saurav Kadavath; Andy Jones; Anna Chen; et al. (ACL (Findings), 2023)

Visual Information Processing in Virtual Reality: Merging Theory and Practice. - Jack Clark (iConference (1), 2023)

The Capacity for Moral Self-Correction in Large Language Models. - Deep Ganguli; Amanda Askell; Nicholas Schiefer; Thomas I. Liao; Kamile Lukosiute; Anna Chen; Anna Goldie; Azalia Mirhoseini; Catherine Olsson; Danny Hernandez; Dawn Drain; Dustin Li; et al. (CoRR, 2023)

Regulatory Markets: The Future of AI Governance. - Gillian K. Hadfield; Jack Clark (CoRR, 2023)

Model evaluation for extreme risks. - Toby Shevlane; Sebastian Farquhar; Ben Garfinkel; Mary Phuong; Jess Whittlestone; Jade Leung; Daniel Kokotajlo; Nahema Marchal; Markus Anderljung; Noam Kolt; Lewis Ho; Divya Siddarth; et al. (CoRR, 2023)

Towards Measuring the Representation of Subjective Global Opinions in Language Models. - Esin Durmus; Karina Nyugen; Thomas I. Liao; Nicholas Schiefer; Amanda Askell; Anton Bakhtin; Carol Chen; Zac Hatfield-Dodds; Danny Hernandez; Nicholas Joseph; Liane Lovitt; Sam McCandlish; et al. (CoRR, 2023)

Artificial Intelligence Index Report 2023. - Nestor Maslej; Loredana Fattorini; Erik Brynjolfsson; John Etchemendy; Katrina Ligett; Terah Lyons; James Manyika; Helen Ngo; Juan Carlos Niebles; Vanessa Parli; Yoav Shoham; Russell Wald; et al. (CoRR, 2023)

Taking Back Control in an Intermediate Representation for GPU Computing. - Vasileios Klimis; Jack Clark; Alan Baker; David Neto; John Wickerson; Alastair F. Donaldson (Proc. ACM Program. Lang., 2023)

Validating Database System Isolation Level Implementations with Version Certificate Recovery. - Jack Clark; Alastair F. Donaldson; John Wickerson; Manuel Rigger (EuroSys, 2024)

Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training. - Evan Hubinger; Carson Denison; Jesse Mu; Mike Lambert; Meg Tong; Monte MacDiarmid; Tamera Lanham; Daniel M. Ziegler; Tim Maxwell; Newton Cheng; Adam S. Jermyn; Amanda Askell; et al. (CoRR, 2024)

Artificial Intelligence Index Report 2024. - Nestor Maslej; Loredana Fattorini; C. Raymond Perrault; Vanessa Parli; Anka Reuel; Erik Brynjolfsson; John Etchemendy; Katrina Ligett; Terah Lyons; James Manyika; Juan Carlos Niebles; Yoav Shoham; et al. (CoRR, 2024)

Clio: Privacy-Preserving Insights into Real-World AI Use. - Alex Tamkin; Miles McCain; Kunal Handa; Esin Durmus; Liane Lovitt; Ankur Rathi; Saffron Huang; Alfred Mountfield; Jerry Hong; Stuart Ritchie; Michael Stern; Brian Clarke; et al. (CoRR, 2024)

Exploring the Effects of Multi-sensory Extraneous Load on Attention and Task Performance in VR. - Jack Clark; Lila Boz (HCI (11), 2025)

Towards Using Biometric Transcripts for Analyzing Multimodal Sensory Information Processing Data. - Jack Clark; Lila Boz (HCI (13), 2025)

Which Economic Tasks are Performed with AI? Evidence from Millions of Claude Conversations. - Kunal Handa; Alex Tamkin; Miles McCain; Saffron Huang; Esin Durmus; Sarah Heck; Jared Mueller; Jerry Hong; Stuart Ritchie; Tim Belonax; Kevin K. Troy; Dario Amodei; et al. (CoRR, 2025)