🔬 Research Summary by Edward Small, a Ph.D. candidate in computer science at the Royal Melbourne Institute of Technology with his research focused on fair and explainable artificial intelligence. [Original paper … [Read more...] about Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse
Fairness
Bias and Fairness in Large Language Models: A Survey
🔬 Research Summary by Isabel O. Gallegos, a Ph.D. student in Computer Science at Stanford University, researching algorithmic fairness to interrogate the role of artificial intelligence in equitable … [Read more...] about Bias and Fairness in Large Language Models: A Survey
Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision Making
🔬 Research Summary by Min Lee, an Assistant Professor in Computer Science at Singapore Management University, where he creates and evaluates interactive, human-centered AI systems for societal problems (e.g. … [Read more...] about Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision Making
Benchmark Dataset Dynamics, Bias and Privacy Challenges in Voice Biometrics Research
🔬 Research Summary by Anna Leschanowsky, a research associate at Fraunhofer IIS in Germany working at the intersection of voice technology, human-machine interaction and privacy. [Original paper by Casandra … [Read more...] about Benchmark Dataset Dynamics, Bias and Privacy Challenges in Voice Biometrics Research
Target specification bias, counterfactual prediction, and algorithmic fairness in healthcare
🔬 Research Summary by Eran Tal, Canada Research Chair in Data Ethics and Associate Professor of Philosophy at McGill University. He studies the epistemology and ethics of data collection and data use in scientific … [Read more...] about Target specification bias, counterfactual prediction, and algorithmic fairness in healthcare