Keeping it Real: Using Real-World Problems to Teach AI to Diverse Audiences


Nicole Sintov, Debarun Kar, Thanh Nguyen, Fei Fang, Kevin Hoffman, Arnaud Lyet, and Milind Tambe. 2017. “Keeping it Real: Using Real-World Problems to Teach AI to Diverse Audiences.” AI Magazine (To appear).


In recent years, AI-based applications have increasingly been used in real-world domains. For example, game theorybased decision aids have been successfully deployed in various security settings to protect ports, airports, and wildlife. This paper describes our unique problem-to-project educational approach that used games rooted in real-world issues to teach AI concepts to diverse audiences. Specifically, our educational program began by presenting real-world security issues, and progressively introduced complex AI concepts using lectures, interactive exercises, and ultimately hands-on games to promote learning. We describe our experience in applying this approach to several audiences, including students of an urban public high school, university undergraduates, and security domain experts who protect wildlife. We evaluated our approach based on results from the games and participant surveys.
See also: 2017