Burton, Emanuelle (University of Kentucky) | Goldsmith, Judy (University of Kentucky) | Koenig, Sven (University of Southern California) | Kuipers, Benjamin (University of Michigan) | Mattei, Nicholas (IBM Research) | Walsh, Toby (University of New South Wales and Data61)
The recent surge in interest in ethics in artificial intelligence may leave many educators wondering how to address moral, ethical, and philosophical issues in their AI courses. As instructors we want to develop curriculum that not only prepares students to be artificial intelligence practitioners, but also to understand the moral, ethical, and philosophical impacts that artificial intelligence will have on society. In this article we provide practical case studies and links to resources for use by AI educators. We also provide concrete suggestions on how to integrate AI ethics into a general artificial intelligence course and how to teach a stand-alone artificial intelligence ethics course.
Anand, Sarabjot Singh, Bahls, Daniel, Burghart, Catherina R., Burstein, Mark, Chen, Huajun, Collins, John, Dietterich, Tom, Doyle, Jon, Drummond, Chris, Elazmeh, William, Geib, Christopher, Goldsmith, Judy, Guesgen, Hans W., Hendler, Jim, Jannach, Dietmar, Japkowicz, Nathalie, Junker, Ulrich, Kaminka, Gal A., Kobsa, Alfred, Lang, Jerome, Leake, David B., Lewis, Lundy, Ligozat, Gerard, Macskassy, Sofus, McDermott, Drew, Metzler, Ted, Mobasher, Bamshad, Nambiar, Ullas, Nie, Zaiqing, Orsvarn, Klas, O'Sullivan, Barry, Pynadath, David, Renz, Jochen, Rodriguez, Rita V., Roth-Berghofer, Thomas, Schulz, Stefan, Studer, Rudi, Wang, Yimin, Wellman, Michael
The AAAI-07 workshop program was held Sunday and Monday, July 22-23, in Vancouver, British Columbia, Canada. The program included the following thirteen workshops: (1) Acquiring Planning Knowledge via Demonstration; (2) Configuration; (3) Evaluating Architectures for Intelligence; (4) Evaluation Methods for Machine Learning; (5) Explanation-Aware Computing; (6) Human Implications of Human-Robot Interaction; (7) Intelligent Techniques for Web Personalization; (8) Plan, Activity, and Intent Recognition; (9) Preference Handling for Artificial Intelligence; (10) Semantic e-Science; (11) Spatial and Temporal Reasoning; (12) Trading Agent Design and Analysis; and (13) Information Integration on the Web.