219 citations · 641 across the 20 of their papers we have counts for
9 papers · 1 filter
Towards Publicly Accountable Frontier LLMs: Building an External Scrutiny Ecosystem under the ASPIRE Framework
Markus Anderljung, Everett Thornton Smith, Joe O'Brien +7
With the increasing integration of frontier large language models (LLMs) into society and the economy, decisions related to their training, deployment, and use have far-reaching im…
Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives
Elizabeth Seger, Noemi Dreksler, Richard Moulange +19
Recent decisions by leading AI labs to either open-source their models or to restrict access to their models has sparked debate about whether, and how, increasingly capable AI mode…
Coordinated pausing: An evaluation-based coordination scheme for frontier AI developers
Jide Alaga, Jonas Schuett
As artificial intelligence (AI) models are scaled up, new capabilities can emerge unintentionally and unpredictably, some of which might be dangerous. In response, dangerous capabi…
Risk assessment at AGI companies: A review of popular risk assessment techniques from other safety-critical industries
Leonie Koessler, Jonas Schuett
Companies like OpenAI, Google DeepMind, and Anthropic have the stated goal of building artificial general intelligence (AGI) - AI systems that perform as well as or better than hum…
Frontier AI Regulation: Managing Emerging Risks to Public Safety
Markus Anderljung, Joslyn Barnhart, Anton Korinek +21
Advanced AI models hold the promise of tremendous benefits for humanity, but society needs to proactively manage the accompanying risks. In this paper, we focus on what we term "fr…
Towards best practices in AGI safety and governance: A survey of expert opinion
Jonas Schuett, Noemi Dreksler, Markus Anderljung +4
A number of leading AI companies, including OpenAI, Google DeepMind, and Anthropic, have the stated goal of building artificial general intelligence (AGI) - AI systems that achieve…
Frontier AI developers need an internal audit function
Jonas Schuett
This article argues that frontier artificial intelligence (AI) developers need an internal audit function. First, it describes the role of internal audit in corporate governance: i…
How to design an AI ethics board
Jonas Schuett, Anka Reuel, Alexis Carlier
Organizations that develop and deploy artificial intelligence (AI) systems need to take measures to reduce the associated risks. In this paper, we examine how AI companies could de…
Auditing large language models: a three-layered approach
Jakob Mökander, Jonas Schuett, Hannah Rose Kirk +1
Large language models (LLMs) represent a major advance in artificial intelligence (AI) research. However, the widespread use of LLMs is also coupled with significant ethical and so…