Artificial Intelligence Use
Overview
Artificial Intelligence (AI) and Generative AI (GenAI) are rapidly reshaping open research by transforming how knowledge is created, shared, accessed, and evaluated. GenAI models go beyond traditional AI by generating new, original content based on learned patterns. These models are trained on vast amounts of data, some of which may be unknown to the user. As GenAI is integrated more widely and quickly into academic workflows, this ability raises crucial questions for scholarly communication, including authorship, integrity, transparency, and research reliability. Recognizing these issues, FSR commits to monitoring and reviewing developments such as updates to the Committee on Publication Ethics (COPE) guidelines for AI use and will revise this policy to reflect the most current best practice to support openness, honesty, and transparency in research. Updates will be reflected on the webpage. The policy is expected to be reviewed regularly by the editorial team.
We encourage all authors, reviewers, editors, and readers to approach the use of GenAI responsibly, with open engagement and critical discernment. When Artificial Intelligence Generated Content (AIGC) tools are used, we believe full disclosure should apply, with information provided regarding the tool or model, and why and how it was applied to the research conception, writing, and editing of a manuscript.
Definitions
‘AI’, ‘AIGC’, and ‘automation’ are not interchangeable.
AI-assisted search engines or “agents” refer to search engines utilizing AI to retrieve, summarize, categorize, and extract parts of records in response to a (sometimes iterative) search query. The influence the tool exerts on the results retrieved and how they are presented is unclear at this point. AI tools can present or create factually incorrect results or nonsensical “information”.
AIGC refers to unique content created by tools using predictions made via machine learning from LLMs (large language models) or SMLs (small language models). AIGC tools include, but are not limited to, tools that provide functions for text generation, image generation, resource discovery, text-to-video, etc., and other tools trained on LLMs (LLMs) or SMLs that generate unique content based on predictions. This also applies to AIGC add-ons within software.
Automation refers to rules-based software, and includes tools like spelling and grammar checkers.
This policy covers the use of AIGC and AI, whether by authors, editors, or peer reviewers. Use of automation is not included in this policy and is permitted by FSR.
Should you have any concerns, questions, or issues regarding generative AI within FSR publications, please contact fsr@academyfinancial.org.
Data Privacy and AI Training Models
Authors should proceed with caution when uploading research data and/or authored content into generative AI tools, and always avoid inputting sensitive or confidential data. Data privacy and intellectual property ownership guidelines vary by tool, are often updated regularly, may be dependent on geographic location (of both the tool and the individual using it), and are not always evident. There is the potential that the creator of the tool retains the right to use some or all of the content fed into it.
Openly accessible academic publications, such as those published by FSR, are frequently utilized by various entities for AI model training. This practice is widespread and often occurs without the explicit permission of authors or publishers.
Work published in FSR is assigned a CC BY-NC 4.0 License, allowing you to contribute to the global dissemination of open and free knowledge. However, please be aware that this openness may also result in your work being incorporated into AI training datasets. We encourage authors to consider this information when deciding to publish. FSR does not engage in or profit from the use of your work for AI training purposes.
For Authors
At this time, FSR allows the use of generative AI as a tool to support authors’ original research and submitted manuscripts. Manuscripts must be written by human authors, and AI tools should only be used to support the author’s own ideation, critical thinking, and creative processes.
A GenAI Disclosure Statement is required for all manuscript submissions to FSR. This applies regardless of whether GenAI tools were used. Authors must select the applicable option and upload the completed statement as a separate submission component. A template for the GenAI Disclosure Statement is available for download from the FSR website.
FSR is in agreement with the following statement from COPE:
AI tools cannot meet the requirements for authorship as they cannot take responsibility for the submitted work. As non-legal entities, they cannot assert the presence or absence of conflicts of interest nor manage copyright and license agreements.
See COPE’s Full statement on AI authorship.
Manuscripts cannot list AI tools as coauthors because they cannot take responsibility for the content when submitting to FSR.
Authors are prohibited from using AI tools to create falsified data and content, including text, data, images, etc., unless for the explicit purposes of illustrating a specific and stated argument. Authors may use AI tools to sort, categorize, clean, order, or present data, provided the results are a true representation of the data collected and have been verified as such by the author.
If authors submitting to FSR have used AIGC in any portion of a manuscript, including text, data, images, graphics, videos, citations, or translations, the tool and its use must be described in detail in the methods section and other sections of the manuscript when appropriate.
In the statement, it is essential to disclose not just the version used, but also which specific model, especially since models like GPT-3.5 and GPT-4 (available in the same version of ChatGPT) can produce different responses to the same prompt. Tracking these details is crucial for transparency, as models evolve quickly and their outputs may change over time.
If authors discover sources through the use of AI tools, they must access those sources directly and not rely on or cite AI-generated summaries to use and cite them in their manuscripts. As with standard manuscript submission, the author is responsible for the accuracy of all information provided by the tool.
For Editors
Editors may search AI-supported discovery tools with keywords of their own design to assist in finding expert researchers in a particular field, much as they would consult resources such as FSR’s records of registered users, Google Scholar, or Scopus to find names of prominent authors in a given area of expertise. FSR editors are aware of many inherent biases in AI tools and consult a range of sources when selecting peer reviewers.
Manuscripts will be treated confidentially throughout the editorial and peer-review process. Editors must not upload, paste, or otherwise input any manuscript content, author information, reviewer identities, or other confidential materials into any AI tools that may incorporate content into training data. As it is currently unclear how data ingested in AI tools is stored and reused, sharing any part of the manuscript, including text, figures, graphs, and images, potentially violates confidentiality. Editors will not use AI detection tools for the same reason.
For Peer Reviewers
Peer review is fundamental to the research mission because it subjects scholarly work to expert scrutiny, ensuring research quality, integrity, and credibility. FSR thanks all those who have contributed their time and expertise to furthering the work of the journal via peer review.
FSR expects reviewers to be responsible for the content of their reviews. The core concern regarding AI use in peer review is confidentiality: uploading any part of a manuscript into an AI tool potentially compromises the author's proprietary rights, as it is currently unclear how content ingested by AI tools is stored or reused. For this reason, reviewers must not upload, paste, or otherwise input any manuscript content into any AI tool during the review process. Reviewers who are uncertain about a tool's data retention and privacy practices should err on the side of caution and not use it for manuscript-related tasks.
Peer reviewers will be required to acknowledge FSR’s policy on the use of AI in peer review when accepting manuscripts for review and take full responsibility for the reports they provide to FSR.
This policy has been adapted from the Journal of Librarianship and Scholarly Communication (JLSC) found here: https://iastatedigitalpress.com/jlsc/site/editorial-policies/#aigc.
Version: 15 June 2026.
