most citedA Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models

99 citations · 115 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY2025★ 1 cited

Stop treating `AGI' as the north-star goal of AI research

Borhane Blili-Hamelin, Christopher Graziul, Leif Hancox-Li +13

The AI research community plays a vital role in shaping the scientific, engineering, and societal goals of AI research. In this position paper, we argue that focusing on the highly…

cs.CL2024★ 7 cited

AfriMed-QA: A Pan-African, Multi-Specialty, Medical Question-Answering Benchmark Dataset

Tobi Olatunji, Charles Nimo, Abraham Owodunni +23

Recent advancements in large language model(LLM) performance on medical multiple choice question (MCQ) benchmarks have stimulated interest from healthcare providers and patients gl…

cs.LG2024★ 6 cited

Nteasee: Understanding Needs in AI for Health in Africa -- A Mixed-Methods Study of Expert and General Population Perspectives

Mercy Nyamewaa Asiedu, Iskandar Haykel, Awa Dieng +7

Artificial Intelligence (AI) for health has the potential to significantly change and improve healthcare. However in most African countries, identifying culturally and contextually…

cs.CL2024★ 2 cited

Contextual Evaluation of Large Language Models for Classifying Tropical and Infectious Diseases

Mercy Asiedu, Nenad Tomasev, Chintan Ghate +9

While large language models (LLMs) have shown promise for medical question answering, there is limited work focused on tropical and infectious disease-specific exploration. We buil…

cs.CY2024★ 99 cited

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models

Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres +27

Large language models (LLMs) hold promise to serve complex health information needs but also have the potential to introduce harm and exacerbate health disparities. Reliably evalua…