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Evidence record 8871 · automatically gathered

Ethics of AI in Education: Towards a Community-Wide Framework

Abstract While Artificial Intelligence in Education (AIED) research has at its core the desire to support student learning, experience from other AI domains suggest that such ethical intentions are not by themselves sufficient. There is also the need to consider explicitly issues such as fairness, accountability, transparency, bias, autonomy, agency, and inclusion. At a more general level, there is also a need to differentiate between doing ethical things and doing things ethically , to understa

Record details

Published: 9 April 2021
Source: OpenAlex
Category: Research
Topics: Bias & fairness · Children & education · Agents & autonomy · Transparency
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Bias & fairness · Shared topic: Agents & autonomy

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Shared topic: Bias & fairness · Shared topic: Children & education

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Shared topic: Bias & fairness · Shared topic: Children & education

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Shared topic: Bias & fairness · Shared topic: Children & education

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Shared topic: Bias & fairness · Shared topic: Agents & autonomy

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Shared topic: Bias & fairness · Shared topic: Children & education

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How to cite this record

ethics.ai (9 April 2021), “Ethics of AI in Education: Towards a Community-Wide Framework,” evidence record 8871, https://ethics.ai/record/8871 (originally published by OpenAlex).

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