AI evidence extraction

AI-based research mentors: Plausible scenarios and ethical issues

Daniel Crean, Michał Wieczorek, Bert Gordijn, Alan J. Kearns · Accountability in Research · 2025

AI-generated evidence extraction, verified across multiple analytical personas. Not a substitute for the peer-reviewed original.

9/10

Relevance

1/4

Quality (LMQS)

Evidence

Citations

0.00

FWCI

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.1080/08989621.2025.2551890

Methodology & findings

Study design

Technology foresight analysis guided by Brey's Anticipatory Technology Ethics with scenario planning employed to yield four plausible future scenarios.

Main result

The analysis revealed that "certain principles - openness, education, legality, and mutual respect - were violated in all scenarios." Additionally, "the guidance scenario showed that AIRM's responses could be manipulated to justify poor practice ('AIRMing')." The study found that "the guidance-only scenario was the least problematic" among the four scenarios examined, though ethical issues persist regarding honesty, openness, credit, education, legality, and mutual respect.

Reports effect sizes.

Research paradigm

Interpretive/normative ethics analysis using anticipatory technology ethics

Author conclusions

"Therefore, policy must be developed to ensure that AIRMs are used solely for guidance while mitigating these issues." The authors conclude that while the guidance-only scenario has benefits such as "providing expert guidance on research," ethical issues arise with regard to multiple principles, necessitating policy development to govern AIRM deployment.

Data: not_statedCode: not_statedExtracted from: pdfAgreement 78%

Explore related topics

Responsible AI Use AI Governance Conceptual