Algorithmic bias and data privacy are central ethical risks of AI in adult education¶

Claim · All claims
Evidence · 1 study · review r? · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? AI systems trained on datasets reflecting existing social inequalities can produce biased outcomes in assessment, recommendations, or learner profiling, disproportionately affecting vulnerable groups. → Theodora 2026 q2 i? AI reliance on large amounts of personal data, including learning behaviours and sometimes biometric information, creates risks of unauthorized access, misuse, or lack of informed consent. → Theodora 2026

Evidence¶

Theodora 2026¶

Theodora, A., & Tselios, N. (2026). Artificial Intelligence in Lifelong Learning: Opportunities and Challenges in Adult Education Policy. https://arxiv.org/abs/2605.16296 doi:10.48550/arxiv.2605.16296

q2 · i? · review · r?

The review identifies algorithmic bias as central to AI-in-education debates, citing Holmes et al., and separately discusses privacy and surveillance risks from collection of personal data, citing Williamson & Eynon. It concludes transparency, accountability, and ethical oversight are needed.

"AI systems are trained on datasets that may reflect existing social inequalities, which can lead to biased outcomes in areas such as assessment, recommendations, or learner profiling."

Discussion¶

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