Generative Artificial Intelligence for Academic Research: Evidence from Guidance Issued for Researchers by Higher Education Institutions in the United States

2025-03-01

AI Summary

The widespread adoption of generative AI in academic research has intensified ethical governance challenges—including authorship attribution, data bias, transparency, and privacy—while university policies lag behind technological practice. Method: This study constructs the first nationwide database of AI research guidelines from 127 U.S. universities and proposes a three-dimensional analytical framework (“applicable scenarios–responsible actors–risk levels”). It integrates computational content analysis, LDA topic modeling, and expert-validated coding to identify governance paradigms. Contribution/Results: Two dominant paradigms emerge: “tool neutrality” and “process embedding.” Critically, only 38% of guidelines explicitly define authorship norms for AI-assisted writing and data analysis, exposing significant policy gaps and implementation ambiguity. The study delivers a reproducible methodological toolkit and empirically grounded benchmarks to advance ethical AI governance in higher education.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Machine Learning: Ethics, Bias, and Fairness

Application Category

• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Technology governance, policy, and regulations
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data

Problem

• Balancing GenAI productivity with ethical concerns in research.
• Understanding and addressing GenAI's impact on authorship and privacy.
• Ensuring compliance and responsibility in GenAI use among researchers.

Innovation

• Refer to external sources for updates and training
• Understand GenAI attributes and ethical concerns
• Acknowledge and disclose GenAI use effectively