AI for Social Good is a course jointly taught by Dr. Milind Tambe (Viterbi School of Engineering) and Dr. Eric Rice. The purpose of the class is to expose doctoral students and advanced masters level students to a new field of research which merges research techniques in artificial intelligence with theory and research contexts from social work. The course is attached to Drs. Tambe and Rice’s new Center for Artificial Intelligence in Society (CAIS). This course is intended to be trans-disciplinary. It will be a small seminar style course, with limited enrollment. The intention is to have half of the student body from engineering and social work respectively. There is no need for programming experience or social work practice experience per se, however, a deep connection to either social work or computer science is needed. The course will provide an overview of major methods that can advance this new trans-disciplinary work, from both a conceptual level in computer science and a conceptual level in social work. Topics from engineering will include decision theory, sequential planning under uncertainty, and machine learning predictive models. Topics from social work will include human behavior theories that can be modeled by AI (such as social cognitive theory and social network theory) as well as context driven topics, such as homelessness and health care access. The course meets weekly, is a discussion style course and will include an emphasis on group projects which are tackled in trans-disciplinary teams.
CSCI 599: Artificial Intellegence For Social Good
INSTRUCTORS MILIND TAMBE & ERIC RICE
PhD students are expected to participate heavily in teaching concepts to the other half of the class. PhD students should team up in exercises. Each class will typically introduce concepts and generate some exercises for the class to be jointly done.