Applied Ethics in Artificial Intelligence and Deep Learning
AI/Machine Learning/Deep Learning
Big Data Analytics
TimeMonday, June 17th5pm - 5:30pm
DescriptionThere is an ongoing debate about ethical artificial intelligence. Unfortunately, parts of this debate do not address the technical dimensions of state of the art methods, especially deep learning. From an interdisciplinary perspective there are three main challenges for ethical deep learning: hidden bias, confusion of causality and correlation, and black-box algorithms. These challenges have to be addressed by technical solutions and sound social science analysis.
Associate Professor for Political Data Science