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Protecting scientific integrity in an age of generative AI
63
Zitationen
24
Autoren
2024
Jahr
Abstract
Revolutionary advances in AI have brought us to a transformative moment for science. AI is accelerating scientific discoveries and analyses. At the same time, its tools and processes challenge core norms and values in the conduct of science, including accountability, transparency, replicability, and human responsibility (1–3). These difficulties are particularly apparent in recent advances with generative AI. Future innovations with AI may mitigate some of these or raise new concerns and challenges.
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Autoren
- Wolfgang Blau
- Vinton G. Cerf
- Juan Enriquez
- Joseph S. Francisco
- Urs Gasser
- Mary L. Gray
- Mark Greaves
- Barbara J. Grosz
- Kathleen Hall Jamieson
- Gerald H. Haug
- John L. Hennessy
- Eric Horvitz
- David Kaiser
- Alex John London
- Robin Lovell‐Badge
- Marcia McNutt
- Martha Minow
- Tom M. Mitchell
- Susan Ness
- Shobita Parthasarathy
- S. Perlmutter
- William H. Press
- Jeannette M. Wing
- M. S. Witherell
Institutionen
- BG Group (United Kingdom)(GB)
- Google (United States)(US)
- University of Pennsylvania(US)
- Technical University of Munich(DE)
- Indiana University Bloomington(US)
- Microsoft Research New England (United States)
- Microsoft (United States)(US)
- Harvard University(US)
- German National Academy of Sciences Leopoldina(DE)
- Stanford University(US)
- Massachusetts Institute of Technology(US)
- Carnegie Mellon University(US)
- The Francis Crick Institute(GB)
- National Academy of Sciences(US)
- Harvard University Press(US)
- University of Michigan–Ann Arbor(US)
- Lawrence Berkeley National Laboratory(US)
- University of California, Berkeley(US)
- The University of Texas at Austin(US)
- Columbia University(US)
- Executive Office of the President(US)