Authentic Integration of Ethics and AI through Sociotechnical, Problem-Based Learning

Authors

  • Ari Krakowski University of California, Berkeley, Lawrence Hall of Science
  • Eric Greenwald University of California, Berkeley, Lawrence Hall of Science
  • Timothy Hurt University of California, Berkeley, Lawrence Hall of Science
  • Brandie Nonnecke CITRIS Policy Lab, CITRIS and the Banatao Institute, UC Berkeley
  • Matthew Cannady University of California, Berkeley, Lawrence Hall of Science

DOI:

https://doi.org/10.1609/aaai.v36i11.21556

Keywords:

Artificial Intelligence, Ethics, High School, Curriculum, Sociotechnical, Problem-based Learning, Interdisciplinary

Abstract

Growing awareness of both the demand for artificial intelligence (AI) expertise and of the societal impacts of AI systems has led to calls to integrate learning of ethics alongside learning of technical skills in AI courses and pathways. In this paper, we discuss our experiences developing and piloting the TechHive:AI curriculum for high school youth that integrates AI ethics and technical learning. The design of the curriculum was guided by the following pedagogical goals: (1) to respond to the capacity-building need for critical sociotechnical competencies in AI workforce pathways; and (2) to broaden participation in AI pathways through intentional instructional design to center equity in learning experiences. We provide an overview of the 30-hour learning sequence’s instructional design, and our “4D Framework,” which we use as a heuristic to help students conceptualize and inspect AI systems. We then provide a focused description of one of three 8-hour modules that make up the sequence. Finally, we present evidence of promise from an exploratory study of TechHive:AI with a small sample of students, and discuss insights from implementation, including from our use of established resources for AI learning within the learning sequence as well as those created by our team.

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Published

2022-06-28

How to Cite

Krakowski, A., Greenwald, E., Hurt, T., Nonnecke, B., & Cannady, M. (2022). Authentic Integration of Ethics and AI through Sociotechnical, Problem-Based Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 36(11), 12774-12782. https://doi.org/10.1609/aaai.v36i11.21556