649 citations · 1.1k across the 15 of their papers we have counts for
27 papers
Language Models Change Facts Based on the Way You Talk
Matthew Kearney, Reuben Binns, Yarin Gal
Large language models (LLMs) are increasingly being used in user-facing applications, from providing medical consultations to job interview advice. Recent research suggests that th…
Not Even Nice Work If You Can Get It; A Longitudinal Study of Uber's Algorithmic Pay and Pricing
Reuben Binns, Jake Stein, Siddhartha Datta +2
Ride-sharing platforms like Uber market themselves as enabling `flexibility' for their workforce, meaning that drivers are expected to anticipate when and where the algorithm will…
Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
Alexandra Olteanu, Su Lin Blodgett, Agathe Balayn +7
In AI research and practice, rigor remains largely understood in terms of methodological rigor -- such as whether mathematical, statistical, or computational methods are correctly…
Access Denied: Meaningful Data Access for Quantitative Algorithm Audits
Juliette Zaccour, Reuben Binns, Luc Rocher
Independent algorithm audits hold the promise of bringing accountability to automated decision-making. However, third-party audits are often hindered by access restrictions, forcin…
Governance of Generative AI in Creative Work: Consent, Credit, Compensation, and Beyond
Lin Kyi, Amruta Mahuli, M. Six Silberman +3
Since the emergence of generative AI, creative workers have spoken up about the career-based harms they have experienced arising from this new technology. A common theme in these a…
Reputation Management in the ChatGPT Era
Lilian Edwards, Reuben Binns
Generative AI systems often generate outputs about real people, even when not explicitly prompted to do so. This can lead to significant reputational and privacy harms, especially…