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AI evidence extraction

Challenges for enforcing editorial policies on AI-generated papers

Guangwei Hu · Accountability in Research · 2023

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

9/10
Relevance
0/4
Quality (LMQS)
I
Evidence
62
Citations
2.20
FWCI
Top 10%
Impact

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.1080/08989621.2023.2184262

Methodology & findings

Study design

Hermeneutic analysis and conceptual argument; this is a policy-focused letter that does not employ empirical measurement or experimentation

Main result

The paper identifies that "AI-generated papers are not easily discernible to the human eye, and we lack the right tools to implement the policies" regarding AI-generated content in academic publishing. The authors note that major journals such as Nature and professional societies have issued policies to ban or curb AI-written papers, but these policies face a critical implementation challenge.

Research paradigm

Critical analysis / interpretive

Author conclusions

The authors conclude that "amid the flurry of policy initiatives, one important challenge seems to be overlooked: AI-generated papers are not easily discernible to the human eye, and we lack the right tools to implement the policies." They argue that without such detection tools, "the well-intentioned policies are likely to remain on paper."

Open questions raised

  • The paper identifies the need for tools and methods to detect AI-generated papers as a critical gap, suggesting that future work must develop detection capabilities to make editorial policies enforceable.
  • The paper identifies the critical gap that tools and methods for detecting AI-generated papers are absent, preventing effective implementation of editorial policies despite their existence.
  • The paper identifies a critical gap: the absence of effective tools and methods to detect and discern AI-generated papers in academic submission systems, which undermines the enforceability of editorial policies.
Data: not_statedCode: not_statedExtracted from: pdfAgreement 80%

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