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The Need for Prospective Integrity Standards for the Use of Generative AI in Research
1University of Michigan, Ann Arbor, MI, United States.
Abstract:
The federal government has a long history of trying to find the right balance in supporting scientific and medical research while protecting the public and other researchers from potential harms. To date, this balance has been generally calibrated differently across contexts - including in clinical care, human subjects research, and research integrity. New challenges continue to face this disparate model of regulation, including novel Generative Artificial Intelligence (GenAI) tools. Because of potential increases in unintentional fabrication, falsification, and plagiarism using GenAI - and challenges establishing both these errors and intentionality in retrospect - this article argues that we should instead move toward a system that sets accepted community standards for the use of GenAI in research as prospective requirements.
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