| Current and near-term AI as a potential existential risk factor BS Bucknall, S Dori-Hacohen Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 119-129, 2022 | 51 | 2022 |
| Black-box access is insufficient for rigorous ai audits S Casper, C Ezell, C Siegmann, N Kolt, TL Curtis, B Bucknall, A Haupt, ... The 2024 ACM Conference on Fairness, Accountability, and Transparency, 2254-2272, 2024 | 46 | 2024 |
| Open-sourcing highly capable foundation models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives E Seger, N Dreksler, R Moulange, E Dardaman, J Schuett, K Wei, ... arXiv preprint arXiv:2311.09227, 2023 | 36 | 2023 |
| Towards Publicly Accountable Frontier LLMs: Building an External Scrutiny Ecosystem under the ASPIRE Framework M Anderljung, ET Smith, J O'Brien, L Soder, B Bucknall, E Bluemke, ... arXiv preprint arXiv:2311.14711, 2023 | 21* | 2023 |
| Open Problems in Technical AI Governance A Reuel, B Bucknall, S Casper, T Fist, L Soder, O Aarne, L Hammond, ... arXiv preprint arXiv:2407.14981, 2024 | 15* | 2024 |
| Structured Access for Third-Party Research on Frontier AI Models: Investigating Researchers' Model Access Requirements BS Bucknall, RF Trager | 14 | 2023 |
| Position: Technical Research and Talent is Needed for Effective AI Governance A Reuel, L Soder, B Bucknall, TA Undheim Forty-first International Conference on Machine Learning, 2024 | 6* | 2024 |
| Hazards from Increasingly Accessible Fine-Tuning of Downloadable Foundation Models A Chan, B Bucknall, H Bradley, D Krueger arXiv preprint arXiv:2312.14751, 2023 | 3 | 2023 |
| Promoting Exploration in Reinforcement Learning through Surprise-Based Intrinsic Motivation BS Bucknall | | 2022 |
