2 papers
cs.CY2025
Facets of Disparate Impact: Evaluating Legally Consistent Bias in Machine Learning
Jarren Briscoe, Assefaw Gebremedhin
Leveraging current legal standards, we define bias through the lens of marginal benefits and objective testing with the novel metric "Objective Fairness Index". This index combines…
cs.LG2025
Algorithmic Accountability in Small Data: Sample-Size-Induced Bias Within Classification Metrics
Jarren Briscoe, Garrett Kepler, Daryl Deford +1
Evaluating machine learning models is crucial not only for determining their technical accuracy but also for assessing their potential societal implications. While the potential fo…