What can we do to build algorithms that are safe, reliable and robust? And what are the responsibilities of technologists who work in this area? In this talk, Chongli Qin and Iason Gabriel explore these questions — connected through the lens of responsible innovation — in two parts. In the first part, Chongli explores the question of why and how we can design algorithms that are safe, reliable and trustworthy through the lens of specification driven machine learning. In the second part, Iason looks more closely at ethical dimensions of machine learning, at the responsibility of researchers, and at processes that can structure ethical deliberation in this domain. Taken together, they suggest that there are important measures that we can, and should, put in place — if we want to build systems that are beneficial to society.

#deep learning

Deep Learning Lectures
1.10 GEEK