The Human Ecology of Artificial Intelligence: Problems and Projects
This course examines the challenges, threats and opportunities emerging with technologies associated with Artificial Intelligence. It will consider the nature of intelligence in its many forms in humans and nature and examine how these and other forms of intelligence may be coded into emerging AI technologies or developed through various forms of machine learning, evolutionary programming, et cetera. Sample topics include roles of AI in education, health, agriculture, transportation, policing, military, scientific research, the arts, spiritual traditions, religions, government, language translation, and bridging relations between different cultures.
Goals are to develop: understandings of the basic programming principles, research and development strategies and underlying philosophical assumptions guiding development in such technologies; abilities to use interdisciplinary, problem centered approaches to understand complicated vs. “wicked” problems associated with rapid technological change and key approaches to dealing with them; collaborative skills for problem-centered studies and programming projects in AI in areas of student interest; and meta-cognitive abilities to learn these kinds of material in groups as well as on your own.
Students pursue term projects individually or collaboratively which may include; futures studies use of methods of historical and/or social science research to investigate some emerging, AI-related social or environmental concern; a computer programming project that solves a practical problem, is conducive to artistic expression, performs scientific analysis of quantitative data, or demonstrates an established or experimental feature of an Machine Learning or otherwise AI system; or a philosophical and/or theoretical critical analysis of underlying concepts, values or assumptions that are at stake in the emerging AI technologies.
Readings will include classic texts in AI theory, philosophy, and futures studies as well as selections from standard texts on AI programming like that of Stuart Russell and Peter Norvig. We will also use podcasts, films, and other media to pursue key topics and trends. There will be a series of short programming activities to study basic principles and try modelling aspects of more complicated and/or complex systems. These will be done, at least initially, in block coding accessible to students without previous programming experience. We will examine the ways in which they can be coded in Python and students familiar with that or other languages will be able to pursue homework and final project work in whatever language they may prefer.
Class sessions and lab will vary in format from extended discussion of texts and problems to supplementary lecture, visiting speakers, collaborative coding activities and extended project work. The class as a group will develop at least one major hackathon style project as a way of exploring key issues and developing key skills.
Evaluation will be based on the extent to which students demonstrate in homework, class participation and term projects that they have advanced in each of the four main goals for the course.