Organization / Entity Disclosure Policy Status Threshold Location Images Reviewer

About This Monitor

The AI Disclosure Policy Monitor provides a structured reference for how major research and publishing institutions are addressing generative AI in scholarly work. It tracks publicly available policies from leading publishers, journals, conferences, standards bodies, and research funding agencies.

Because publisher policies change faster than any static table can track, the monitor includes a built-in research prompt that users can execute in any major LLM platform to retrieve current policy information on demand.

Who Should Use This

  • Researchers preparing manuscripts for submission
  • Research administrators developing institutional AI policy
  • Journal editors benchmarking their requirements against the field
  • Anyone tracking how scholarly publishing is responding to generative AI

Institutional Update Prompt (HILOM Framework)

Execute this prompt in your Large Language Model platform (GPT-4, Gemini, Claude) to retrieve real-time policy updates following the Matthews Geographics HILOM framework.

You specialize in academic publishing policy, research ethics, and research-funder governance, with deep expertise in AI/GenAI disclosure requirements across scholarly publishing, standards bodies, conferences, and funding agencies. You are helping me build institutional guidance for researchers at my organization by producing an up-to-date reference on AI disclosure policies. The Human-in-the-Loop-O-Meter: AI Disclosure Policies in Peer Reviewed Scientific Publication is a framework published by Matthews Geographics, LLC (matthewsgeographics.com). That white paper contains a structured policy table covering academic, publishing, conference, standards, and funding entities' AI policies. ## Task Research and verify the latest AI disclosure, authorship, image-use, and peer-review/applicant restrictions for each entity listed below. ## Rules 1. Conduct a brief discovery scan to identify any additional major entities that now have explicit public AI/GenAI policies relevant to scholarly publication or grant review. 2. For each entity, specify the exact nature of the disclosure policy (e.g., prohibited, allowed with specific declaration, required for substantive use). 3. Identify the "Reviewer Policy" specifically (how models may/may not be used in the evaluation process). 4. Identify the "Image Policy" (restrictions on AI-generated figures or charts). 5. Provide a source URL for every row.