Value Cards: An Educational Toolkit for Teaching Social Impacts of Machine Learning through Deliberation
This addresses the problem of integrating ethics and social considerations into computer science education for students and practitioners, though it is incremental as it builds on existing calls for such curricula.
The paper tackles the need to teach social impacts of machine learning by introducing Value Cards, an educational toolkit used in a college course, which improved students' understanding of technical metrics and social values, and enhanced their communication and negotiation skills.
Recently, there have been increasing calls for computer science curricula to complement existing technical training with topics related to Fairness, Accountability, Transparency, and Ethics. In this paper, we present Value Card, an educational toolkit to inform students and practitioners of the social impacts of different machine learning models via deliberation. This paper presents an early use of our approach in a college-level computer science course. Through an in-class activity, we report empirical data for the initial effectiveness of our approach. Our results suggest that the use of the Value Cards toolkit can improve students' understanding of both the technical definitions and trade-offs of performance metrics and apply them in real-world contexts, help them recognize the significance of considering diverse social values in the development of deployment of algorithmic systems, and enable them to communicate, negotiate and synthesize the perspectives of diverse stakeholders. Our study also demonstrates a number of caveats we need to consider when using the different variants of the Value Cards toolkit. Finally, we discuss the challenges as well as future applications of our approach.