Medical publication policies and guidelines offer a framework for best practices, but there may be situations when more than one approach seems reasonable. The primary purpose of “What Would You Do?” is to explore examples of such situations. With the limited information provided to interpret the scenarios, you may find yourself agreeing with one, more than one, or none of the proposed actions. And that’s the point ‒ you should debate, contemplate, and communicate (with a comment) before selecting your “best” answer.
Now let’s find out how you responded and read through some commentary (for context only; not meant to be comprehensive) to the below scenario.
Your team at a sponsoring pharmaceutical company recently published a clinical study in a reputable journal. Soon after, a healthcare professional shared a summary generated by an AI-powered medical tool that appears to overstate the study’s efficacy and underrepresent key limitations. The AI summary is gaining traction in online discussions.
While the original published abstract is accurate, you recognize that its structure may make it easier for AI tools to generate simplified, and potentially misleading, interpretations. Now, there is internal debate about whether your team has any responsibility to respond. Some colleagues argue that once the manuscript is published, interpretation by third-party tools is out of the authors’ or the company’s control. Others believe there is a professional obligation to step in when summaries derived from a company-sponsored publication could influence clinical understanding. As a publications lead, you are asked how to proceed.
What Would You Do?
A total of 56 people replied to this poll.
This scenario explored how publication teams should respond when an AI-generated medical summary appears to overstate the results of a sponsor’s published clinical study and downplay its limitations. It raised a timely and increasingly important question for pharmaceutical publication professionals: once a sponsored study is published accurately in a peer-reviewed journal, do authors and company teams still have a responsibility to address misleading third-party interpretations that may circulate online? This question aligns with publication ethics guidance emphasizing that authors and journals may need to address substantive concerns through correspondence, corrections, or other formal communication channels when the published record or its interpretation is at issue.
Consistent with longstanding expectations for accountability and engagement in medical publications, respondents showed a clear preference for active response and stewardship rather than a passive approach. A majority of respondents, 62.5%, selected the option to work closely with the lead author and senior corresponding author to issue a clarification through company channels, author commentary, or correspondence. This indicates that most participants believe publication teams should take some responsibility for protecting the integrity of the scientific record when AI tools create distorted summaries of company-sponsored research. The choice of a clarification reflects a practical and collaborative approach: rather than challenging the existence of third-party AI tools directly, respondents favored reinforcing the correct interpretation of the published findings through authoritative, transparent communication. That approach is consistent with ICMJE guidance that authors should respond to substantial criticism and that correspondence can be an appropriate mechanism for doing so.
The second most common response, chosen by 21.4% of respondents, was to engage with the AI tool or platform provider after consulting with the authors, to flag the issue and explore possible corrections or refinements. This suggests that about one-fifth of respondents saw value in addressing the problem at its source. Their response implies that publication teams may not only have a duty to clarify the record, but also a role in trying to improve how AI systems present scientific information more broadly. This perspective is consistent with broader publication ethics discussions about transparency and responsible use of AI in scholarly communication.
A smaller proportion of respondents, 10.7%, chose to treat the issue as a learning opportunity for future publication practices without intervening retroactively. This response indicates that some participants viewed the situation as important, but not necessarily one that justified direct action in the present case. Their position may reflect a desire to improve future abstract writing, publication structure, or communication strategies so that studies are less vulnerable to oversimplified AI interpretation. Even so, this option stops short of immediate corrective action and therefore represents a more cautious, forward-looking approach.
Only 5.4% said they would take no direct action and trust that the full publication provides sufficient context. This was the least-selected substantive response, showing that very few respondents felt the issue could simply be left alone. In other words, the poll suggests that most publication professionals do not believe responsibility ends at publication when AI-generated summaries may distort the message and influence clinical understanding. That view is broadly consistent with ICMJE and WAME principles emphasizing accountability, transparency, and the need for authors to engage responsibly in the scholarly record.
Overall, the poll reveals a strong consensus that publication teams should not remain passive when AI summaries misrepresent published research. Most respondents favored proactive clarification, and many also supported direct engagement with platform providers. The findings suggest growing recognition that in the AI era, publication responsibility may extend beyond manuscript publication to include monitoring, correcting, and helping shape how evidence is interpreted in the broader scientific ecosystem. This interpretation is supported by ICMJE guidance on correspondence and corrections, as well as WAME’s emphasis on transparency and responsible AI use in scholarly publishing.
This article was prepared by members of the ISMPP Insider Committee. The opinions expressed within are the authors’ own and do not necessarily reflect the views of their employers or of ISMPP.
References
International Committee of Medical Journal Editors. (n.d.). Corrections and version control. ICMJE Recommendations. https://www.icmje.org/recommendations/browse/publishing-and-editorial-issues/corrections-and-version-control.html
International Committee of Medical Journal Editors. (n.d.). Correspondence. ICMJE Recommendations. https://www.icmje.org/recommendations/browse/publishing-and-editorial-issues/correspondence.html
International Committee of Medical Journal Editors. (n.d.). Defining the role of authors and contributors. ICMJE Recommendations. https://www.icmje.org/recommendations/browse/roles-and-responsibilities/defining-the-role-of-authors-and-contributors.html
World Association of Medical Editors. (n.d.). Chatbots, generative AI, and scholarly manuscripts. https://www.wame.org/page2.php?id=106
