Reviewed studies identify data privacy, algorithmic bias, unequal access, and epistemic trust as central ethical concerns in educational AI¶

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2031: baselines and conditions change

Subclaims¶

q2 i? Ethics and governance emerge as a prominent cross-cutting theme, with data privacy, algorithmic bias, unequal access and epistemic trust frequently cited concerns. → Ikram M 2026

Evidence¶

Ikram M 2026¶

Ikram M, Hanefar SBM, Saleem SMU and Zulfiqar F (2026) Artificial intelligence in education: a systematic review of personalized learning trends and future directions. Front. Educ. 11:1782626. https://doi.org/10.3389/feduc.2026.1782626

q2 · i? · review · r2

Thematic synthesis (Section 4.4). The review reports that "Concerns frequently cited include data privacy, bias in algorithms, unequal access, and questions of epistemic trust," with learners voicing apprehension about inaccuracies and misuse of AI-generated information, especially in medicine.

"Concerns frequently cited include data privacy, bias in algorithms, unequal access, and questions of epistemic trust"

Discussion¶

Related Claims¶

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