PHIL 330 - Ethics and Data Science

Credits: (3)
College Curriculum: COLL 200
Domain (Anchored): ALV
Domain (Reaching Out): CSI, NQR

This course is an introduction to some of the ethical and societal problems that are posed by recent developments in data science, artificial intelligence, and the pervasiveness of the Internet in everyday life. The course begins by introducing students to the nature of information and data, to two major normative ethical theories (consequentialism and deontology), and to some common biases and fallacies concerning probability and statistics. We will then explore moral issues concerning privacy and freedom in connection with big data and the Internet. What, if anything, justifies the right to privacy? How does privacy relate to autonomy and to property rights? Are traditional justifications of the right to privacy still adequate in the age of big data and social media? How does the right to freedom of speech interact with “echo chambers” and the spread of disinformation online? The course concludes by surveying a number of ethical problems posed by machine learning and artificial intelligence, such as: Should machine learning algorithms be transparent or interpretable by humans? How do biases arise in algorithms, and how can they be prevented or corrected? How do we make sense of questions of moral accountability in cases in which machines are autonomous? How will automation affect the nature of human labor, and how will it affect inequality? Should we be worried about the creation of a “superintelligence” that could destroy humanity?