Kweku Kwegyir-Aggrey Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Researcher

John Brown University

unknown

1 h-index 4 pubs 3 cited

Research Areas

Ethics and Social Impacts of AI Privacy-Preserving Technologies in Data Risk and Safety Analysis Machine Learning and Data Classification Racial and Ethnic Identity Research Explainable Artificial Intelligence (XAI) Auction Theory and Applications Experimental Behavioral Economics Studies

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OverviewAI-generated summary

Kweku Kwegyir-Aggrey is a researcher at John Brown University whose work addresses the ethical and societal implications of artificial intelligence. His research integrates perspectives from computer science, economics, and social science, with a particular focus on fairness, accountability, and transparency in machine learning systems. Kwegyir-Aggrey investigates privacy-preserving technologies, risk and safety analysis, and explainable AI (XAI). Recent work examines the limitations of commonly used evaluation metrics like AUC in high-impact risk assessment scenarios and the disparate impact of model selection in deep learning applications. He also explores methods for repairing regressors to ensure fair binary classification across different decision thresholds. Additionally, Kwegyir-Aggrey's interests extend to experimental behavioral economics, auction theory, and the study of racial and ethnic identity.

Metrics

h-index: 1
Publications: 4
Citations: 3

Selected Publications

Observing Context Improves Disparity Estimation when Race is Unobserved (2024) DOI
The Misuse of AUC: What High Impact Risk Assessment Gets Wrong (2023) DOI