Claims

Faculty members and students identify both user-related and algorithm-related ethical risks in AI use in education

Claim · All claims
Evidence · 1 study (2 entries) · qualitative r3 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2031: baselines and conditions change

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q2 i? Faculty members framed ethical risks as user-related (academic integrity violations, lack of ethical oversight, professional competence erosion) and algorithm-related (manipulation, information reliability, privacy, bias). → Buket Bilgiç and Demet Sever 2026 q2 i? Students reported parallel user-related and algorithm-related risks, including false information, manipulation, privacy concerns, bias, and intellectual property violations. → Buket Bilgiç and Demet Sever 2026 (2)

Evidence

Buket Bilgiç and Demet Sever 2026

Buket Bilgiç and Demet Sever (2026). Understanding ethical dimensions of AI in higher education: insights from faculty members and students. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-026-00601-0

q2 · i? · qualitative · r3

Qualitative theme from faculty interviews. Under user-related risks participants cited academic integrity violations and lack of ethical oversight; under "Algorithm-Related Ethical Risks", they highlighted algorithmic manipulation, information reliability, privacy and data security, and algorithmic bias.

"Faculty members assessed ethical risks in terms of user-related and algorithm-related forms"

Buket Bilgiç and Demet Sever 2026 (2)

Buket Bilgiç and Demet Sever (2026). Understanding ethical dimensions of AI in higher education: insights from faculty members and students. International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-026-00601-0

q2 · i? · qualitative · r3

Qualitative theme from student interviews mirroring the faculty structure. Students cited academic integrity violations and lack of oversight as user-related risks, and "the production of false information", algorithmic manipulation, privacy and data security, algorithmic bias, and intellectual property violations as algorithm-related risks.

"Students also expressed ethical risks in a similar manner, based on users and algorithms"

Discussion

Page metadata
Field Value
type claim
id user-and-algorithm-related-ethical-risks-ai-education
title Faculty members and students identify both user-related and algorithm-related ethical risks in AI use in education
description Faculty members and students identify both user-related and algorithm-related ethical risks in AI use in education
status review
evidence_strength moderate
newest_evidence 2026
recheck_by 2031
generated by process:wiki-ingest on 2026-10-10
trust unverified — no one has confirmed this page's content
sources 2 — buket-bilgiç-and-demet-sever-2026, buket-bilgiç-and-demet-sever-2026-2

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