9 citations · 35 across the 12 of their papers we have counts for
13 papers
Sycophantic AI makes human interaction feel more effortful and less satisfying over time
Lujain Ibrahim, Franziska Sofia Hafner, Myra Cheng +5
Millions of people now turn to artificial intelligence (AI) systems for personal advice, guidance, and support. Such systems can be sycophantic, frequently affirming users' views a…
Interactive visualizations for adolescents to understand and challenge algorithmic profiling in online platforms
Yui Kondo, Kevin Dunnell, Isobel Voysey +6
Social media platforms regularly track, aggregate, and monetize adolescents' data, yet provide them with little visibility or agency over how algorithms construct their digital ide…
Measuring what Matters: Construct Validity in Large Language Model Benchmarks
Andrew M. Bean, Ryan Othniel Kearns, Angelika Romanou +39
Evaluating large language models (LLMs) is crucial for both assessing their capabilities and identifying safety or robustness issues prior to deployment. Reliably measuring abstrac…
Framing Migration: A Computational Analysis of UK Parliamentary Discourse
Vahid Ghafouri, Robert McNeil, Teodor Yankov +4
We present a large-scale computational analysis of migration-related discourse in UK parliamentary debates spanning over 75 years and compare it with US congressional discourse. Us…
Training language models to be warm and empathetic makes them less reliable and more sycophantic
Lujain Ibrahim, Franziska Sofia Hafner, Luc Rocher
Artificial intelligence (AI) developers are increasingly building language models with warm and empathetic personas that millions of people now use for advice, therapy, and compani…
Gender Trouble in Language Models: An Empirical Audit Guided by Gender Performativity Theory
Franziska Sofia Hafner, Ana Valdivia, Luc Rocher
Language models encode and subsequently perpetuate harmful gendered stereotypes. Research has succeeded in mitigating some of these harms, e.g. by dissociating non-gendered terms s…
Clinical knowledge in LLMs does not translate to human interactions
Andrew M. Bean, Rebecca Payne, Guy Parsons +8
Global healthcare providers are exploring use of large language models (LLMs) to provide medical advice to the public. LLMs now achieve nearly perfect scores on medical licensing e…
Algorithmic Mirror: Designing an Interactive Tool to Promote Self-Reflection for YouTube Recommendations
Yui Kondo, Kevin Dunnell, Qing Xiao +2
Big Data analytics and Artificial Intelligence systems derive non-intuitive and often unverifiable inferences about individuals' behaviors, preferences, and private lives. Drawing…
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…
Characterizing and modeling harms from interactions with design patterns in AI interfaces
Lujain Ibrahim, Luc Rocher, Ana Valdivia
The proliferation of applications using artificial intelligence (AI) systems has led to a growing number of users interacting with these systems through sophisticated interfaces. H…
Into the crossfire: evaluating the use of a language model to crowdsource gun violence reports
Adriano Belisario, Scott A. Hale, Luc Rocher
Gun violence is a pressing human rights issue that affects nearly every dimension of the social fabric, from healthcare and education to psychology and the economy. Reliable data o…
A Linear Reconstruction Approach for Attribute Inference Attacks against Synthetic Data
Meenatchi Sundaram Muthu Selva Annamalai, Andrea Gadotti, Luc Rocher
Recent advances in synthetic data generation (SDG) have been hailed as a solution to the difficult problem of sharing sensitive data while protecting privacy. SDG aims to learn sta…
When the signal is in the noise: Exploiting Diffix's Sticky Noise
Andrea Gadotti, Florimond Houssiau, Luc Rocher +2
Anonymized data is highly valuable to both businesses and researchers. A large body of research has however shown the strong limits of the de-identification release-and-forget mode…