2 citations · 4 across the 3 of their papers we have counts for
4 papers
A Review of Fairness and A Practical Guide to Selecting Context-Appropriate Fairness Metrics in Machine Learning
Caleb J. S. Barr, Olivia Erdelyi, Paul D. Docherty +1
Recent regulatory proposals for artificial intelligence emphasize fairness requirements for machine learning models. However, precisely defining the appropriate measure of fairness…
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…
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,…
The AI Liability Puzzle and A Fund-Based Work-Around
Olivia J. Erdélyi, Gábor Erdélyi
Certainty around the regulatory environment is crucial to enable responsible AI innovation and foster the social acceptance of these powerful new technologies. One notable source o…