63 citations · 64 across the 6 of their papers we have counts for
6 papers · 1 filter
Applications of Risk Science to AI Fairness Evaluation: Principles, Challenges, and Best Practices
Kyra Wilson, Sabrina Kang, Saloni Dash +1
Scholarly work which aims to describe potential societal impacts (e.g., risks) of proliferating technology (especially related to artificial intelligence or other algorithmic syste…
Resume Screening, Fast and Slow: (Biased) AI Recommendations' Influence on Human Decision Making
Kyra Wilson, Mattea Sim, Anna-Maria Gueorguieva +2
AI is increasingly being used collaboratively with people to make decisions in high-stakes domains, but this new paradigm is still not well-understood in many respects -- particula…
VEAT Quantifies Implicit Associations in Text-to-Video Generator Sora and Reveals Challenges in Bias Mitigation
Yongxu Sun, Michael Saxon, Ian Yang +2
Text-to-Video (T2V) generators such as Sora raise concerns about whether generated content reflects societal bias. We extend embedding-association tests from words and images to vi…
No Thoughts Just AI: Biased LLM Hiring Recommendations Alter Human Decision Making and Limit Human Autonomy
Kyra Wilson, Mattea Sim, Anna-Maria Gueorguieva +1
In this study, we conduct a resume-screening experiment (N=528) where people collaborate with simulated AI models exhibiting race-based preferences (bias) to evaluate candidates fo…
A Taxonomy of Stereotype Content in Large Language Models
Gandalf Nicolas, Aylin Caliskan
This study introduces a taxonomy of stereotype content in contemporary large language models (LLMs). We prompt ChatGPT 3.5, Llama 3, and Mixtral 8x7B, three powerful and widely use…
Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval
Kyra Wilson, Aylin Caliskan
Artificial intelligence (AI) hiring tools have revolutionized resume screening, and large language models (LLMs) have the potential to do the same. However, given the biases which…