{"title":"Assessing the Decision-Making Capabilities of Artificial Intelligence Platforms as Institutional Review Board Members.","authors":"Kannan Sridharan, Gowri Sivaramakrishnan","doi":"10.1177/15562646241263200","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background:</b> Institutional review boards (IRBs) face delays in reviewing research proposals, underscoring the need for optimized standard operating procedures (SOPs). This study assesses the abilities of three artificial intelligence (AI) platforms to address IRB challenges and draft essential SOPs. <b>Methods:</b> An observational study was conducted using three AI platforms in 10 case studies reflecting IRB functions, focusing on creating SOPs. The accuracy of the AI outputs was assessed against good clinical practice (GCP) guidelines. <b>Results:</b> The AI tools identified GCP issues, offered guidance on GCP violations, detected conflicts of interest and SOP deficiencies, recognized vulnerable populations, and suggested expedited review criteria. They also drafted SOPs with some differences. <b>Conclusion:</b> AI platforms could aid IRB decision-making and improve review efficiency. However, human oversight remains critical for ensuring the accuracy of AI-generated solutions.</p>","PeriodicalId":50211,"journal":{"name":"Journal of Empirical Research on Human Research Ethics","volume":" ","pages":"83-91"},"PeriodicalIF":1.7000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Empirical Research on Human Research Ethics","FirstCategoryId":"98","ListUrlMain":"https://doi.org/10.1177/15562646241263200","RegionNum":4,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/17 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ETHICS","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Institutional review boards (IRBs) face delays in reviewing research proposals, underscoring the need for optimized standard operating procedures (SOPs). This study assesses the abilities of three artificial intelligence (AI) platforms to address IRB challenges and draft essential SOPs. Methods: An observational study was conducted using three AI platforms in 10 case studies reflecting IRB functions, focusing on creating SOPs. The accuracy of the AI outputs was assessed against good clinical practice (GCP) guidelines. Results: The AI tools identified GCP issues, offered guidance on GCP violations, detected conflicts of interest and SOP deficiencies, recognized vulnerable populations, and suggested expedited review criteria. They also drafted SOPs with some differences. Conclusion: AI platforms could aid IRB decision-making and improve review efficiency. However, human oversight remains critical for ensuring the accuracy of AI-generated solutions.
期刊介绍：
The Journal of Empirical Research on Human Research Ethics (JERHRE) is the only journal in the field of human research ethics dedicated exclusively to empirical research. Empirical knowledge translates ethical principles into procedures appropriate to specific cultures, contexts, and research topics. The journal''s distinguished editorial and advisory board brings a range of expertise and international perspective to provide high-quality double-blind peer-reviewed original articles.
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