The Journal of Data and Societal Endeavors (JDSE) is a student-led journal at the University of Notre Dame, operated in connection with the Lucy Family Institute for Data & Society. JDSE recognizes artificial intelligence as both an important area of research and a tool that can support scholarly work. Consistent with our commitment to academic integrity, student development, and socially responsible data science, we welcome appropriate AI use when it is transparent, critically evaluated, and subject to human accountability.
This policy applies to authors, reviewers, and editors.
1. Responsible use and author accountability
Authors may use AI tools to support activities such as brainstorming, language editing, translation, programming, and research analysis. Such use must support the authors’ intellectual contributions and understanding of their work.
Authors remain fully responsible for every part of their submission, including AI-assisted text, code, calculations, figures, and interpretations. They must independently verify factual claims, references, analytical methods, and results. AI-generated content must meet the same standards of accuracy, originality, attribution, and methodological rigor as all other content.
AI tools cannot be listed as authors because they cannot take responsibility for the work, approve its publication, or respond to questions about its integrity.
2. Disclosure of AI assistance
Authors must include an “AI Use Statement” before the references when generative AI has contributed to manuscript preparation, coding, analysis, or visual content. The statement must identify:
- The tool and model or version, when available.
- The purpose and extent of its use.
- How the authors reviewed and verified its outputs.
Routine spelling and grammar correction does not require disclosure when it does not generate substantive content or change meaning. Generative rewriting, translation, drafting, and coding assistance must be disclosed.
Disclosure alone does not affect a manuscript’s eligibility for publication. JDSE evaluates the quality, integrity, and contribution of the submitted work.
3. AI as a research method
JDSE welcomes research that develops, evaluates, or applies AI and machine learning methods. Authors must describe these methods in sufficient detail for readers to assess their validity and, where feasible, reproduce the work.
Relevant details may include model versions, data sources, preprocessing, training and evaluation procedures, prompts, parameters, software dependencies, and access dates. Authors must distinguish observed data from synthetic or AI-generated data and explain how generated material was validated.
Where relevant to the study, authors should discuss bias, data representativeness, privacy, uncertainty, and potential societal consequences. Restrictions that prevent sharing data, code, prompts, or models must be explained.
4. Unacceptable uses
AI must not be used to fabricate or falsify evidence, invent references, conceal plagiarism, or misrepresent the authors’ contributions.
AI-generated images, illustrative material, and synthetic data must be clearly identified. They must not be presented as photographs, measurements, participant responses, or other observed evidence unless their generation is explicitly part of the disclosed research design.
Authors must understand and be able to explain and defend the methods, analysis, and conclusions in their submission.
5. Privacy and confidentiality
Authors, reviewers, and editors must protect personal information, confidential research materials, and intellectual property. Such material may be entered into an AI system only when the necessary permissions and appropriate data protections are in place.
Reviewers and editors must not upload unpublished submissions, manuscript excerpts, supplementary files, or confidential review correspondence to external AI services without prior authorization from the journal and any necessary permission from the authors. Access to an institutionally provided tool does not, by itself, establish permission to process confidential submissions.
6. Peer review and editorial decisions
Peer review and publication decisions remain human responsibilities. Reviewers must personally assess the manuscript and develop their own substantive feedback. AI must not replace this evaluation or independently determine acceptance or rejection.
Any authorized AI assistance that materially contributes to a review must be disclosed to the handling editor. Editors remain accountable for editorial communications and decisions.
AI-detection scores must not serve as the sole basis for an allegation of misconduct or an adverse editorial decision.
7. Concerns and policy review
When concerns arise, JDSE will request clarification and give the affected authors or reviewers an opportunity to respond. Depending on the circumstances, the journal may require a revised disclosure, additional verification, manuscript revision, rejection, or a post-publication correction or retraction. Authors may appeal through JDSE’s editorial appeals process.
The editorial board will periodically review this policy, in consultation with faculty advisors and Institute representatives as appropriate, as AI tools and scholarly practices evolve.
Example AI Use Statement
“During preparation of this manuscript, the authors used [tool/model/version] to [describe specific tasks and affected sections or components]. The authors reviewed and revised the generated material and verified [references, code, calculations, or results, as applicable]. The authors take full responsibility for the final manuscript.”