Using an Ethical Framework to Examine K-12 Leaders’ Perceived Risks About AI

Abstract

This article contributes to current debates around the ethics of using AI in K-12 education by extending an ethical framework based on the constructs of wellbeing, autonomy and justice to examine how AI may differentially impact specific stakeholders. Data about K-12 building and district leaders’ perceptions of AI risks were collected during the 2023–24 school year in Western New York as part of an exploratory sequential mixed methods study, which included semi-structured interviews with a diverse group of 36 K-12 leaders, followed by a survey (n = 160). Survey findings confirm K-12 leaders’ widespread recognition, although at varying levels of concern, of AI risks related to (a) students cheating, (b) students’ other questionable AI uses, (c) educators’ questionable AI uses, (d) increasing inequities due to AI, (e) cybersecurity and privacy breaches, and to a much lesser extent, the (f) potential for job replacement. The ethical analysis reveals major differences in the implications of each of these six kinds of AI risk for the wellbeing, autonomy, and justice of K-12 educators, K-12 students, and society, respectively, as well as tensions between competing needs and values, which in turn call for risk-specific strategies as well as inevitable tradeoffs. A comparison with a study of musicians’ perceptions of AI using the same ethical framework reveals interesting similarities and differences in ethical concerns about AI in different fields, suggesting the value of more cross-disciplinary studies.

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