š¬ Research Summary by Satyapriya Krishna, a PhD student at Harvard University working on problems related to Trustworthy Machine Learning. [Original paper by Satyapriya Krishna, Rahul Gupta, Apurv Verma, Jwala … [Read more...] about Measuring Fairness of Text Classifiers via Prediction Sensitivity
Measuring Disparate Outcomes of Content Recommendation Algorithms with Distributional Inequality Metrics
š¬ Research Summary by Tomo Lazovich (they/them) is a Senior Machine Learning Researcher on Twitter's ML Ethics, Transparency, and Accountability (META) team. [Original paper by Tomo Lazovich, Luca Belli, Aaron … [Read more...] about Measuring Disparate Outcomes of Content Recommendation Algorithms with Distributional Inequality Metrics
Do Less Teaching, Do More Coaching: Toward Critical Thinking for Ethical Applications of Artificial Intelligence
š¬ Research summary by Connor Wright, our Partnerships Manager. [Original paper by Claire Su-Yeon Park, Haejoong Kim, Sangmin Lee] Overview: With new online educational platforms, a trend in pedagogy is to … [Read more...] about Do Less Teaching, Do More Coaching: Toward Critical Thinking for Ethical Applications of Artificial Intelligence
Explainable artificial intelligence (XAI) postāhoc explainability methods: risks and limitations in nonādiscrimination law
š¬ Research Summary by Ali El-Sharif, a college professor teaching data analytics and cybersecurity at the St. Clair Zemelman of School of IT in Windsor, Ontario. He earned his Ph.D. from Nova Southeastern … [Read more...] about Explainable artificial intelligence (XAI) postāhoc explainability methods: risks and limitations in nonādiscrimination law
Moral Dilemmas for Moral Machines
š¬ Research Summary by Travis LaCroix, an assistant professor (ethics and computer science) at Dalhousie University [Original paper by Travis LaCroix] Overview: Researchers focusing on implementable machine … [Read more...] about Moral Dilemmas for Moral Machines