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The '''[[National Institute for Occupational Safety and Health]]''' ('''NIOSH''') is the U.S. Federal agency responsible for conducting research and making recommendations for the prevention of work-related injury and illness. NIOSH is part of the [[Centers for Disease Control and Prevention]] (CDC) within the [[United States Department of Health and Human Services|U.S. Department of Health and Human Services]]. NIOSH provides national and world leadership to prevent work-related illness, injury, disability, and death by gathering information, conducting scientific research, and translating the knowledge gained into products and services.
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


NIOSH is headquartered in Washington, D.C., with research laboratories and offices in Cincinnati, Ohio; Morgantown, West Virginia; Pittsburgh, Pennsylvania; Denver, Colorado; Anchorage, Alaska; Spokane, Washington; and Atlanta, Georgia. NIOSH is a professionally diverse organization with a staff ceiling of over 1,400 (as of 2005; operating with about 1,300 full-time employees) people representing a wide range of disciplines including epidemiology, medicine, industrial hygiene, safety, psychology, engineering, chemistry, and statistics. NIOSH was established to help ensure safe and healthful working conditions by providing research, information, education, and training in the field of occupational safety and health. ('''[[National Institute for Occupational Safety and Health|Full article...]]''')<br />
The introduction of [[ChatGPT]] has fuelled a public debate on the appropriateness of using generative [[artificial intelligence]] (AI) ([[large language model]]s or LLMs) in work, including a debate on how they might be used (and abused) by researchers. In the current work, we test whether delegating parts of the research process to LLMs leads people to distrust researchers and devalues their scientific work. Participants (''N'' = 402) considered a researcher who delegates elements of the research process to a PhD student or LLM and rated three aspects of such delegation. Firstly, they rated whether it is morally appropriate to do so. Secondly, they judged whether—after deciding to delegate the research process—they would trust the scientist (who decided to delegate) to oversee future projects ... ('''[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Full article...]]''')<br />
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{{flowlist |
* [[Journal:Geochemical biodegraded oil classification using a machine learning approach|Geochemical biodegraded oil classification using a machine learning approach]]
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Revision as of 15:26, 20 May 2024

Fig1 Niszczota EconBusRev23 9-2.png

"Judgements of research co-created by generative AI: Experimental evidence"

The introduction of ChatGPT has fuelled a public debate on the appropriateness of using generative artificial intelligence (AI) (large language models or LLMs) in work, including a debate on how they might be used (and abused) by researchers. In the current work, we test whether delegating parts of the research process to LLMs leads people to distrust researchers and devalues their scientific work. Participants (N = 402) considered a researcher who delegates elements of the research process to a PhD student or LLM and rated three aspects of such delegation. Firstly, they rated whether it is morally appropriate to do so. Secondly, they judged whether—after deciding to delegate the research process—they would trust the scientist (who decided to delegate) to oversee future projects ... (Full article...)
Recently featured: