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20192024
most citedA Review of Fairness and A Practical Guide to Selecting Context-Appropriate Fairness Metrics in Machine Learning

2 citations · 4 across the 3 of their papers we have counts for

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Showing 2021Show all

2 papers · 1 filter

cs.CY2021★ 1 cited

Randomized Classifiers vs Human Decision-Makers: Trustworthy AI May Have to Act Randomly and Society Seems to Accept This

Gábor Erdélyi, Olivia J. Erdélyi, Vladimir Estivill-Castro

As \emph{artificial intelligence} (AI) systems are increasingly involved in decisions affecting our lives, ensuring that automated decision-making is fair and ethical has become a…

cs.CY2021★ 1 cited

Data Fusion Challenges Privacy: What Can Privacy Regulation Do?

Gábor Erdélyi, Olivia J. Erdélyi, Andreas W. Kempa-Liehr

This paper focuses on some shortcomings in current privacy and data protection regulations' ability to adequately address the ramifications of AI-driven data processing practices,…