Abstract

Recent theoretical and practical achievements in machine learning (ML) and, in particular, artificial neural networks, have motivated ethical questions about their deployment. This chapter critically examines the nature of doing ethics in and for contemporary ML and artificial intelligence (AI). It discusses some prominent epistemological problems, ethical problems regarding bias and fairness, the moral status of AI and how it bears on the problems of responsibility gaps and alignment, the use or misuse of ethical theory in AI, and attendant problems of ethicswashing. Discussion of these topics will show that ethics is done best when integrated as a philosophical discipline.