PHIL 286

This course focuses on social, economic, legal, and ethical issues that arise from the collection, analysis, and use of large data sets, especially when these processes are automated or embedded within artificial intelligence systems. The course explores the design of ethical algorithms by considering questions like the following: what kinds of biases are ethically problematic and how can they be avoided? what are the effects of automation on jobs and inequality? what are the privacy considerations that arise when collecting and using data? what is the ethical significance of transparency in automation? who owns data sets and who has the right to access information? who is responsible for actions that result from artificial intelligence systems? In thinking about these complex questions, students consider specific case studies of controversial uses of data and algorithms in fields such as medicine, biotechnology, military, advertising, social media, finance, transportation, and criminal justice, among others. In addition to relevant ethical theories, students are introduced to philosophical, legal, and scientific theories that play a central role in debates regarding the ethics of data and artificial intelligence. Readings are drawn from a number of classic and contemporary texts in philosophy, science and technology studies, law, public policy, and the emerging fields of "data ethics" and "robot ethics".

Offered every year.

CO24 - ARTHUM (Artistic and Humanistic), INTD - BIOE (Bioethics BIOE), INTD - HUM-SCIVAL (Intd Humanities-Science IHE), INTD - NRSC-MN (Neuroscience Minor NRSC), INTD - NRSCMJARTS (Neuro Arts Major NRSC), INTD - NRSCMJBIOE (Neuro Bioethics Major NRSC), INTD - NRSCMJECON (Neuro Economics Major NRSC), INTD - NRSCMJPHIL (Neuro Philosophy Major NRSC), INTD - NRSCMJSPIR (Neuro Spirituality Major NRSC), INTD - STS (Sci Tech Health Society STHS)