160 citations · 314 across the 32 of their papers we have counts for
15 papers · 1 filter
Embedded Assessments for Frontier AI
Jacob Charnock, Sophie Williams, Zaheed Kara +5
Third-party evaluations for frontier AI have mostly tested models through external interfaces before deployment. But the risks from frontier AI models depend on how their developer…
Frontier AI Auditing: Toward Rigorous Third-Party Assessment of Safety and Security Practices at Leading AI Companies
Miles Brundage, Noemi Dreksler, Aidan Homewood +45
We outline a vision for frontier AI auditing, which we define as rigorous third-party verification of frontier AI developers' safety and security claims, and evaluation of their sy…
Legal Alignment for Safe and Ethical AI
Noam Kolt, Nicholas Caputo, Jack Boeglin +14
Alignment of artificial intelligence (AI) encompasses the normative problem of specifying how AI systems should act and the technical problem of ensuring AI systems comply with tho…
Video Deepfake Abuse: How Company Choices Predictably Shape Misuse Patterns
Max Kamachee, Stephen Casper, Michelle L. Ding +4
In 2022, AI image generators crossed a threshold, enabling much more efficient and dynamic production of photorealistic deepfake images than before. This enabled opportunities for…
Who Evaluates AI's Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations
Anka Reuel, Avijit Ghosh, Jenny Chim +32
Foundation models are increasingly central to high-stakes AI systems, and governance frameworks now depend on evaluations to assess their risks and capabilities. Although general c…
An Adaptive Responsible AI Governance Framework for Decentralized Organizations
Kiana Jafari Meimandi, Anka Reuel, Gabriela Aranguiz-Dias +6
This paper examines the assessment challenges of Responsible AI (RAI) governance efforts in globally decentralized organizations through a case study collaboration between a leadin…
Measuring and mitigating overreliance to build human-compatible AI
Lujain Ibrahim, Katherine M. Collins, Sunnie S. Y. Kim +14
Large language models (LLMs) distinguish themselves from previous technologies by functioning as collaborative ``thought partners,'' capable of engaging more fluidly in natural lan…
Measurement to Meaning: A Validity-Centered Framework for AI Evaluation
Olawale Salaudeen, Anka Reuel, Ahmed Ahmed +6
While the capabilities and utility of AI systems have advanced, rigorous norms for evaluating these systems have lagged. Grand claims, such as models achieving general reasoning ca…
The California Report on Frontier AI Policy
Rishi Bommasani, Scott R. Singer, Ruth E. Appel +20
The innovations emerging at the frontier of artificial intelligence (AI) are poised to create historic opportunities for humanity but also raise complex policy challenges. Continue…
In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate?
Ben Bucknall, Saad Siddiqui, Lara Thurnherr +19
International cooperation is common in AI research, including between geopolitical rivals. While many experts advocate for greater international cooperation on AI safety to address…
Audit Cards: Contextualizing AI Evaluations
Leon Staufer, Mick Yang, Anka Reuel +1
AI governance frameworks increasingly rely on audits, yet the results of their underlying evaluations require interpretation and context to be meaningfully informative. Even techni…
On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective
Yue Huang, Chujie Gao, Siyuan Wu +63
Generative Foundation Models (GenFMs) have emerged as transformative tools. However, their widespread adoption raises critical concerns regarding trustworthiness across dimensions.…
Responsible AI in the Global Context: Maturity Model and Survey
Anka Reuel, Patrick Connolly, Kiana Jafari Meimandi +4
Responsible AI (RAI) has emerged as a major focus across industry, policymaking, and academia, aiming to mitigate the risks and maximize the benefits of AI, both on an organization…
Open Problems in Technical AI Governance
Anka Reuel, Ben Bucknall, Stephen Casper +30
AI progress is creating a growing range of risks and opportunities, but it is often unclear how they should be navigated. In many cases, the barriers and uncertainties faced are at…
Generative AI Needs Adaptive Governance
Anka Reuel, Trond Arne Undheim
Because of the speed of its development, broad scope of application, and its ability to augment human performance, generative AI challenges the very notions of governance, trust, a…