Using AI for the submission process: Tools & trends

• Main Author: UPSHALL, Michael
• Format: text
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Artificial Intelligence and Robotics; Databases and Information Systems; Data Science; Library and Information Science
• Online Access: https://ink.library.smu.edu.sg/ai_research_week/Programme/Programme/12; https://ink.library.smu.edu.sg/context/ai_research_week/article/1008/type/native/viewcontent/AI_in_Publishing_and_Peer_Review__Tools___Trends___AI_for_Research_Week_2024__1_.mp4; https://ink.library.smu.edu.sg/context/ai_research_week/article/1008/filename/0/type/additional/viewcontent/Upshall_Using_AI_for_the_submission_process.pdf
• Institution: Singapore Management University

AI tools of varying kinds have been in use for some years now for the submission process for scholarly manuscripts, facilitating tasks such as consistency checking and peer reviewer identification. This talk will delve into examples of these tools, outlining which of the three main strands of AI: rule-based, statistics-based, and deep-learning based, are most appropriate in each case, while considering their benefits and drawbacks. Despite their potential, the inconsistent usage of these tools has sparked debates over the suitability of these tools ("Do these tools replace humans?") and their impact on publication quality. Decisions on AI integration into workflows are crucial, considering the limitations of certain AI methodologies.The talk aims to provide insights into the effective deployment of AI tools, emphasizing the combination of machine tools and human evaluation to enhance scholarly publication quality while minimizing human effort.