Enterprise AI Analysis
Artificial intelligence policies in bioethics and health humanities: a comparative analysis of publishers and journals
Rapid advancements in artificial intelligence (AI) pose novel ethical and practical challenges for scholarly publishing. This report analyzes the current state of AI policies across bioethics and health humanities journals, highlighting inconsistencies and proposing a unified approach for responsible AI integration in academic publishing.
Our analysis reveals critical insights into the current landscape of AI policy adoption. These metrics quantify the immediate challenges and opportunities for academic publishers.
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Journals with Clear AI Policy
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Journals with Publisher AI Policy
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Journals Banning AI-Generated Text
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Journals with No AI Policy
Deep Analysis & Enterprise Applications
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Bioethics
Health Humanities
Bioethics: Navigating AI in Ethical Discourse
Bioethics, an interdisciplinary field, examines ethical, legal, and social issues in healthcare, medical research, and life sciences. AI introduces new complexities regarding patient rights, decision-making, biotechnology, and public health ethics. The lack of clear AI policies can lead to inconsistent handling of AI-assisted submissions and raise concerns about research integrity and authorship accountability.
Specifically, the study found that 16% of bioethics journals had a clear AI policy, while 54% relied on publisher-level policies. A concerning 10% of bioethics journals explicitly prohibit AI-generated text, contrasting with more permissive publisher guidelines.
Health Humanities: AI and Human Experience
Health humanities explores the human experience of health, illness, and medicine through the lens of literature, philosophy, history, visual arts, and cultural studies. AI tools offer potential for enhancing understanding of patient narratives and medical practice, but their ethical integration requires careful consideration.
The analysis showed that a significantly smaller proportion of health humanities journals had clear AI policies compared to bioethics journals. Only 1 out of 14 health humanities journals (7%) had an identifiable AI policy, with the remaining largely relying on publisher policies or having no formal guidance at all. This highlights a greater need for tailored guidelines that respect the discipline's unique focus on humanistic inquiry.
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Journals explicitly ban AI-generated text in submissions.
Our analysis reveals a significant divergence among journal and publisher policies regarding the permissible extent of AI assistance. While some publishers like Sage indicate openness to manuscripts "primarily or partially generated using AI" (Sage [35]), others, such as John Hopkins University Press [17], explicitly state they "will not accept any work that is substantially written by an AI or LLM tool." This inconsistency creates confusion for authors and highlights the need for clearer, more unified guidelines across the academic publishing landscape.
Varying Disclosure Requirements for AI Use
| Publisher/Journal | Policy Stance | Specifics |
|---|---|---|
| Springer Nature [36] | Partial Disclosure |
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| Cambridge University Press [5] | Full Disclosure |
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| Johns Hopkins University Press [17] | Mandatory Disclosure |
|
Another area of discrepancy is whether every use of AI requires disclosure. Springer Nature [36] posits that AI-assisted "copy editing" does not need to be declared, while Cambridge University Press [5] and Johns Hopkins University Press [17] require broader disclosure for any AI or LLM use. This highlights the urgent need for a standardized approach to AI disclosure to ensure transparency and prevent issues of academic integrity.
Case Study: Rationale for AI-Generated Text Bans
Some journals, such as Christian Bioethics, Journal of Philosophy and Medicine, Kennedy Institute of Ethics Journal, and Voices in Bioethics, explicitly prohibit AI-generated text. While the rationale isn't always explained, Voices in Bioethics [16] states it constitutes plagiarism. However, given that AI lacks personhood, this definition of plagiarism is debatable. Publishers and journals must articulate clear reasons for their AI policies, addressing concerns like generating original scholarship, deskilling, and epistemic risk [10, 25].
Enterprise Process Flow: AI Policy Adoption
Identification of AI Use
→
Review against Journal/Publisher Policy
→
Editor Decision (Consistent/Inconsistent)
→
Author Transparency Requirement
→
Publication / Revision
The adoption of AI policies across bioethics and health humanities journals remains highly inconsistent. This leads to varied interpretations and potential for inconsistent editorial decision-making, creating confusion for authors. Journals without explicit policies leave authors guessing about acceptable levels of AI involvement, from grammar checks to content generation. This fragmented landscape necessitates a unified, transparent approach to AI governance in scholarly publishing.
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Your AI Implementation Roadmap
A structured approach to integrating AI into your publishing workflows, ensuring ethical compliance and maximum efficiency.
Phase 1: Policy Assessment & Gap Analysis
Evaluate existing journal and publisher policies against emerging AI guidelines. Identify areas of inconsistency or absence regarding AI-assisted content, authorship, and disclosure requirements.
Phase 2: Stakeholder Consultation & Consensus Building
Engage editors, authors, peer reviewers, and ethics committees to discuss AI implications. Facilitate expert groups to develop a unified set of ethical guidelines tailored to your specific discipline (e.g., bioethics, health humanities).
Phase 3: Policy Development & Communication
Draft clear, transparent, and enforceable AI policies for journal homepages, author guidelines, and submission portals. Explicitly define permissible AI uses, disclosure requirements, and the rationale for any prohibitions.
Phase 4: Training & Monitoring
Implement training for editorial staff and reviewers on new AI policies. Develop tools or processes to detect undisclosed AI use, ensuring ongoing compliance and adaptability as AI technology evolves.
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