{
  "id": 9583906,
  "title": "HHS AI Research Misconduct Guidance: Old Rules for New Evidence",
  "url": "https://urgent.news/2026/09/24/hhs-ai-research-misconduct-guidance-old-rules-for-new-evidence",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-24T16:03:01.000Z",
  "source": {
    "name": "PYMNTS",
    "slug": "pymnts",
    "url": "https://www.pymnts.com/news/artificial-intelligence/2026/hhs-ai-research-misconduct-guidance-old-rules-for-new-evidence/"
  },
  "original_language": "en",
  "account": "The Department of Health and Human Services' Office of Research Integrity (ORI) issued new guidance on the use of generative artificial intelligence (AI) in public health service-funded research. The guidance applies the existing research misconduct framework to AI use, which requires a significant departure from accepted practices, intentional, knowing or reckless conduct, and proof by a preponderance of the evidence. ORI recommends researchers disclose AI tools used in research and manuscript preparation, explaining their usage. However, disclosure does not excuse misconduct. Institutions must determine the AI tool's name, inputs, outputs, and verification steps, as well as any AI policies issued by funding agencies. Determining accepted practice can be challenging, as research fields differ in their approaches and funding agency policies can also inform the standard. An allegation of misconduct will follow the ordinary institutional process, and an inquiry may be warranted if a credible, sufficiently specific allegation is made. Institutions must notify the respondent, obtain necessary records and evidence, and include appropriate scientific expertise in the investigation. Some AI errors defy simple classification, and AI-generated text or ideas can amount to plagiarism if they reproduce another person's work without credit. Institutions must retain records for seven years after a misconduct proceeding ends and consider updating disclosure and training policies, checking AI vendors' retention practices, and identifying AI experts before cases arise.",
  "summary": "A researcher uses generative artificial intelligence (AI) to process data, draft a grant application or assemble a literature review. If the work is later challenged, investigators may need to reconstruct what the tool produced, what the researcher checked and whether the underlying records still exist. That is the practical challenge in new guidance from the […] The post HHS AI Research…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}