14 citations · 17 across the 6 of their papers we have counts for
4 papers · 1 filter
The Singapore Consensus on Global AI Safety Research Priorities
Yoshua Bengio, Tegan Maharaj, Luke Ong +84
Rapidly improving AI capabilities and autonomy hold significant promise of transformation, but are also driving vigorous debate on how to ensure that AI is safe, i.e., trustworthy,…
HCAST: Human-Calibrated Autonomy Software Tasks
David Rein, Joel Becker, Amy Deng +19
To understand and predict the societal impacts of highly autonomous AI systems, we need benchmarks with grounding, i.e., metrics that directly connect AI performance to real-world…
DarkBench: Benchmarking Dark Patterns in Large Language Models
Esben Kran, Hieu Minh "Jord" Nguyen, Akash Kundu +3
We introduce DarkBench, a comprehensive benchmark for detecting dark design patterns--manipulative techniques that influence user behavior--in interactions with large language mode…
Measuring AI Ability to Complete Long Software Tasks
Thomas Kwa, Ben West, Joel Becker +23
Despite rapid progress on AI benchmarks, the real-world meaning of benchmark performance remains unclear. To quantify the capabilities of AI systems in terms of human capabilities,…