39 citations · 88 across the 63 of their papers we have counts for
10 papers · 1 filter
The 2026 Singapore Consensus on Global AI Safety Research Priorities
Stephen Casper, Oskar Galeev, Yoshua Bengio +117
Frontier AI capabilities and autonomy are advancing rapidly. A growing number of real-world incidents make a trusted AI ecosystem essential to embracing AI with confidence. The 202…
From Democracies to Autocracies: How AI Systems Enable Authoritarianism by Design
Jeba Sania, Marta Ziosi, Fazl Barez
AI-enabled authoritarianism is not confined to autocracies. In this paper, we provide greater transparency by investigating and mapping the lifecycles of six AI systems deployed in…
Make Mechanistic Interpretability Auditable: A Call to Develop Guidelines via Continuous Collaborative Reviewing
Michael Lan, Narmeen Fatimah Oozeer, Chaithanya Bandi +4
While mechanistic interpretability (MI) has produced important insights into neural network internals, the field has yet to establish a standardized system to audit experiments. As…
Rigorous Interpretation Is a Form of Evaluation
Isabelle Lee, Emmy Liu, Cathy Jiao +4
Current machine learning models are evaluated through behavioral snapshots, with benchmark accuracies, win rates and outcome-based metrics. Model explanations and evaluations, howe…
Position: Token Taxes Can Mitigate AI's Economic Risks
Lucas Irwin, Tung-Yu Wu, Fazl Barez
AI-driven automation threatens to erode government tax bases, lower living standards, and disempower citizens--risks that mirror the 40-year stagnation of wages during the first in…
Embodied AI: Emerging Risks and Opportunities for Policy Action
Jared Perlo, Alexander Robey, Fazl Barez +2
The field of embodied AI (EAI) is rapidly advancing. Unlike virtual AI, EAI systems can exist in, learn from, reason about, and act in the physical world. With recent advances in A…
Beyond Monoliths: Expert Orchestration for More Capable, Democratic, and Safe Language Models
Philip Quirke, Narmeen Oozeer, Chaithanya Bandi +8
This position paper argues that the prevailing trajectory toward ever larger, more expensive generalist foundation models controlled by a handful of companies limits innovation and…
AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons
Shaona Ghosh, Heather Frase, Adina Williams +99
The rapid advancement and deployment of AI systems have created an urgent need for standard safety-evaluation frameworks. This paper introduces AILuminate v1.0, the first comprehen…
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…
Fairness in AI and Its Long-Term Implications on Society
Ondrej Bohdal, Timothy Hospedales, Philip H. S. Torr +1
Successful deployment of artificial intelligence (AI) in various settings has led to numerous positive outcomes for individuals and society. However, AI systems have also been show…