A Framework for Socio-Developmental Ethics in Educational AI
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Date
2023-01-03
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6208
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Abstract
In recent years there have been many attempts to create ethical frameworks for AI. Theoretical concepts, such as privacy, fairness, transparency, explainability, responsibility, risk, and trustworthiness have been used as key elements in these frameworks. The use of these concepts is often justified by their wide use in similar frameworks and guidelines but does not seem to result from any coherent shared theoretical foundation. Educational and developmental theories and research have so far had little impact on ethical debates but become important when AI is used in education and learning (AIEd). A socio-developmental view on ethics naturally emerges in the educational context, and the paper shows that it has important implications also beyond the education sector. This paper describes an ethical framework structured in three thematic domains: agency, social fairness, and justified choice, that links AI with theories of education and human development, opening new ways to understand ethics of AI and the social and technical challenges and opportunities in AIEd.
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Social Good and Ill: Implications for Research, Practice, and Policy, artificial intelligence, capability development, education, ethics, learning
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10
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Proceedings of the 56th Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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