AI's Impact on Initial Peer Review
AI can potentially impact the some areas of the peer-review process. AI cannot replace human judgment in evaluating the merit and novelty of research. However, AI tools can assist in key parts of the review process:
AI programs can quickly check papers for issues like text duplication, references, image manipulation, and proper formatting. This relieves editors of mundane tasks so they can focus on higher judgment.
AI-enabled systems can conduct an initial technical screening of papers through natural language processing. They can identify key terms and topics in the paper to find the best potential reviewers. This improves matches between papers and reviewer expertise.
Calculations can remove semantic experiences from papers to feature key terms, results, and ends. This helps editors in understanding the center concentration and commitment. Artificial intelligence projects can likewise survey specialized quality and companion audit trouble to illuminate choices.
Since man-made intelligence frameworks apply predictable principles, they can possibly diminish human inclinations in light of institutional distinction, position, orientation, or different variables. In any case, care should be taken to guarantee man-made intelligence doesn’t repeat predispositions in the preparation information.
SOFIA RIAZ, "How AI Impacts Academic Publishing." Enago Academy. January 15, 2024. https://www.enago.com/academy/guestposts/sofia_riaz/impact-of-ai-in-academic-publishing/.
AI’s Impact on Journal Operations
Past companion survey, computer based intelligence can further develop productivity in taking care of papers and speaking with creators:
Mechanized frameworks fueled by computer based intelligence can in a flash confirm key necessities in a paper accommodation, diminishing dependence on manual quality checks. This speeds up introductory processes.
Man-made intelligence chatbots and savvy email projects can assume control over routine errands like affirming receipt, mentioning amendments, addressing status questions, and comparison of distribution charges. This saves time for human staff.
Algorithms can analyze citation patterns and usage metrics to inform decisions on journal priorities, scope expansion, special issues, and article promotions. This data enhances strategic planning.
Automating menial tasks at each stage—submission, review, revision, acceptance, formatting, and production—can significantly speed up publication while maintaining quality. This increases output and accessibility.
SOFIA RIAZ, "How AI Impacts Academic Publishing." Enago Academy. January 15, 2024. https://www.enago.com/academy/guestposts/sofia_riaz/impact-of-ai-in-academic-publishing/.
Informa publisher collaborates with Microsoft to:
Committee on Publication Ethics position
"The use of artificial intelligence (AI) tools such as ChatGPT or Large Language Models in research publications is expanding rapidly. COPE joins organisations, such as WAME and the JAMA Network among others, to state that AI tools cannot be listed as an author of a paper.
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.
Authors who use AI tools in the writing of a manuscript, production of images or graphical elements of the paper, or in the collection and analysis of data, must be transparent in disclosing in the Materials and Methods (or similar section) of the paper how the AI tool was used and which tool was used. Authors are fully responsible for the content of their manuscript, even those parts produced by an AI tool, and are thus liable for any breach of publication ethics" (COPE Council. COPE position - Authorship and AI - English. https://doi.org/10.24318/cCVRZBms).
Author Guidelines from Publishers
Before including AI-generated content in a project you intend to get published, check publisher policies regarding permissible use and attribution. Below are some examples of publisher policies regarding the use of AI.
General Guidelines for authors using AI-assisted technology for writing manuscripts:
Leverage these tools to augment language and improve readability exclusively; refrain from substituting them for critical research tasks such as data interpretation or scientific conclusion formulation.
Employ the technology under human supervision and control, meticulously reviewing and editing the output. AI, while capable of producing seemingly authoritative information, may introduce biases, inaccuracies, or incompleteness.
Avoid attributing authorship to AI or including AI and AI-assisted technologies as authors or co-authors. As per Elsevier's AI author policy, authorship responsibilities and tasks are exclusive to and executed by humans.
Transparently communicate the use of artificial intelligence (AI) and AI-assisted technologies in the writing process. Declarations about the utilization of AI will be incorporated into the published work when authors make such statements. Ultimately, authors bear the ultimate responsibility and accountability for the content of their work.
Jairoun, A. A., El-Dahiyat, F., ElRefae, G. A., Al-Hemyari, S. S., Shahwan, M., Zyoud, S. H., Hammour, K. A., & Babar, Z. U. (2024). Detecting manuscripts written by generative AI and AI-assisted technologies in the field of pharmacy practice. Journal of pharmaceutical policy and practice, 17(1), 2303759. https://doi.org/10.1080/20523211.2024.2303759
General methods for identifying use of generative AI and AI-assisted technologies in writing manuscripts. Editors and reviewers must stay well-informed about developments in AI technologies to effectively recognize AI-written papers.
Keep Up-To-Date with AI Developments: Keeping abreast of the latest developments in generative AI is essential. Editors and reviewers should read extensively, attend conferences, and rely on reputable sources to understand AI systems’ potential and limitations.
Identify Strange Language Patterns: AI-generated manuscripts will typically contain inconsistent or unexpected language patterns. Editors should watch for abrupt changes in writing style, sentence construction, or vocabulary that do not match authors’ experience or previous contributions to the journal.
Use Plagiarism-Detection Tools: Employ plagiarism-detection software to identify potential duplicates of previously published content. While AI-generated texts may not be exact copies, they can still contain content similar to that from various sources.
Scrutinise References and Citations: Thoroughly examine the references and citations provided. AI-generated content can include inconsistencies, reference unrelated and obscure sources, or fail to adhere to the journal’s formatting requirements.
Compare Articles with Existing AI Literature: Compare submitted articles with existing AI-generated articles to identify specific terms or patterns commonly used by AI models.
Examine Figures and Tables: Verify the accuracy of data presented in figures and tables. AI-generated manuscripts can include fabricated or misleading data inconsistent with the study’s objectives and findings.
Verify Authorship: Confirm the affiliations, email addresses, and prior publications of the corresponding author and co-authors. Contact authors to corroborate their genuine participation in a study.
Evaluate Submission Metadata: Check the manuscript’s metadata, such as file characteristics and creation date. AI-generated documents can exhibit unusual metadata patterns.
Request AI Model Code and Raw Data: Encourage authors to provide the AI model code and raw data they used in their study. Legitimate authors should have access to these details, whereas AI-generated texts may lack them.
Continuously Monitor Published Articles: Monitor published articles for any signs of AI-generated material even after initial checks. Some AI-generated articles may pass initial scrutiny but can be identified through further analysis later on.
Seek Assistance from AI Experts: If unsure about a manuscript’s origin, seek advice from AI or natural language processing professionals.
Encourage Ethical Engagement With AI: Educate scholars on the potential academic abuses of AI technologies and define a set of ethical guidelines to support their use and development.
Jairoun, A. A., El-Dahiyat, F., ElRefae, G. A., Al-Hemyari, S. S., Shahwan, M., Zyoud, S. H., Hammour, K. A., & Babar, Z. U. (2024). Detecting manuscripts written by generative AI and AI-assisted technologies in the field of pharmacy practice. Journal of pharmaceutical policy and practice, 17(1), 2303759. https://doi.org/10.1080/20523211.2024.2303759
Five C's of Ethics for Peer Review in Scientific Publishing
Qualitative indicators for detecting use generative AI tools