Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Physical Sciences and Mathematics
Examining Bias In Jury Selection For Criminal Trials In Dallas County, Megan Ball, Brandon Birmingham, Matt Farrow, Katherine Mitchell, Bivin Sadler, Lynne Stokes
Examining Bias In Jury Selection For Criminal Trials In Dallas County, Megan Ball, Brandon Birmingham, Matt Farrow, Katherine Mitchell, Bivin Sadler, Lynne Stokes
SMU Data Science Review
One of the hallmarks of the American judicial system is the concept of trial by jury, and for said trial to consist of an impartial jury of your peers. Several landmark legal cases in the history of the United States have challenged this notion of equal representation by jury—most notably Batson v. Kentucky, 476 U.S. 79 (1986). Most of the previous research, focus, and legal precedence has centered around peremptory challenges and attempting to prove if bias was suspected in excluding certain jurors from serving. Few studies, however, focus on examining challenges for cause based on self-reported biases from the …
Reducing Age Bias In Machine Learning: An Algorithmic Approach, Adriana Solange Garcia De Alford, Steven K. Hayden, Nicole Wittlin, Amy Atwood
Reducing Age Bias In Machine Learning: An Algorithmic Approach, Adriana Solange Garcia De Alford, Steven K. Hayden, Nicole Wittlin, Amy Atwood
SMU Data Science Review
In this paper, we study the prevalence of bias in machine learning; we explore the life cycle phases where bias is potentially introduced into a machine learning model; and lastly, we present how adversarial learning can be leveraged to measure unwanted bias and unfair behavior from a machine learning algorithm. This study focuses particularly on the topics of age bias in predicting employee attrition and presents a practical approach for how adversarial learning can be successful in mitigating age bias. To measure bias, we calculate group fairness metrics across five-year age groups and evaluate fairness between a baseline predictive model …