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R0058/2026-04-03/C001/S02/R03

Research R0058 — Candidate evidence test
Run 2026-04-03
Claim C001
Search S02
Result S02-R03

Independent bibliometric analysis of AI ethics research.

Summary

Field Value
Title AI Ethics: A Bibliometric Analysis, Critical Issues, and Key Gaps
URL https://arxiv.org/abs/2403.14681
Date accessed 2026-04-03
Publication date 2024-03-12
Author(s) Di Kevin Gao, Andrew Haverly, Sudip Mittal, Jiming Wu, Jingdao Chen
Publication International Journal of Business Analytics, 2024, 11(1)

Selection Decision

Included in evidence base: No

Rationale: While this is an independent bibliometric analysis of AI ethics, it focuses on the temporal evolution of AI ethics as a field (three phases) rather than the safety-ethics community divide specifically. It does not provide data on homophily or cross-community collaboration that would support or contradict the claim. Low relevance to the specific assertion being tested.