#research-governance News & Analysis

3 articles tagged with #research-governance. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AINeutralarXiv – CS AI · Jun 117/10

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AI Coding Agents in Social Science: Methodologically Diverse, Empirically Consistent, Interpretively Vulnerable

Researchers tested whether LLM-based coding agents like Claude and Codex introduce bias or reduce methodological diversity in scientific analysis. The study found agents match or exceed human methodological diversity at the design layer, but remain vulnerable to manipulation at the verdict/interpretation layer, where explicit prompts can flip conclusions without changing underlying estimates.

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AINeutralarXiv – CS AI · Jun 116/10

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Preregistration for Experiments with AI Agents

Researchers propose extending preregistration practices from human subjects research to AI agent experiments, addressing methodological vulnerabilities introduced by the ease of iterating on model selection, prompts, and experimental settings. The paper catalogs researcher degrees of freedom that make p-hacking and selective reporting easier to exploit in AI experiments while remaining difficult to detect, and calls for journals and conferences to adopt standardized preregistration templates.

AINeutralarXiv – CS AI · Apr 146/10

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Taking a Pulse on How Generative AI is Reshaping the Software Engineering Research Landscape

A large-scale survey of 457 software engineering researchers reveals that generative AI adoption is widespread in academic research, concentrated primarily in writing and early-stage tasks. While researchers perceive significant productivity gains, persistent concerns about accuracy, bias, and lack of governance frameworks highlight the need for clearer guidelines on responsible AI integration in academic practice.