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Present and future of AI, open science, and transparency in regulatory science

Authors: Tsaioun, Katya; Hartung, Thomas;

Present and future of AI, open science, and transparency in regulatory science

Abstract

Workshop report from the EBTC and EFSA Workshop at the 13th Global Summit on Regulatory Science September 25, 2023 in Parma, Italy. The participants included the regulators from around the owrld, who shared their experiences, expectations and concerns about using AI and other new technologies in regulatory context. The topic of the workshop was "Present and future of AI, open science, and transparency in regulatory science". The workshop opened with three talks addressing the potential of AI in regulatory science, the need for effective data pipelines and practical application of AI bridging data gaps. The workshop discused the challenge to balance consumer and patient protection in regulatory decision-making while incorporating the latest advances in science and, at the same time, to increase efficiency, accuracy and transparency of their assessments. The participants agreed that AI and other new technologies hold a great potential for regulatory science but the incorporation into decisionmaking should be based on the best practices and successful applications in other fields, be transparent, step-wise and prioritize publuc safety.

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Keywords

transparency, Regulatory science, data, AI, open science

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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