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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Prahladh EgyptJofForSci22 12.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Niszczota EconBusRev23 9-2.png|240px]]</div>
'''"[[Journal:Introductory evidence on data management and practice systems of forensic autopsies in sudden and unnatural deaths: A scoping review|Introductory evidence on data management and practice systems of forensic autopsies in sudden and unnatural deaths: A scoping review]]"'''
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


The investigation into sudden unexpected and unnatural deaths supports criminal justice, aids in litigation, and provides important information for [[public health]], including surveillance, [[epidemiology]], and prevention programs. The use of mortality data to convey trends can inform policy development and resource allocations. Hence, data practices and [[Information management|data management systems]] in [[Forensic science|forensic medicine]] are critical. This study scoped literature and described the body of knowledge on data management and practice systems in forensic medicine. Five steps of the methodological framework of Arksey and O’Malley guided this scoping review. A combination of keywords, Boolean terms, and medical subject headings was used to search [[PubMed]], EBSCOhost (CINAHL with full text and Health Sources), Cochrane Library, Scopus, Web of Science, Science Direct, WorldCat, and Google Scholar for peer review papers in English ... ('''[[Journal:Introductory evidence on data management and practice systems of forensic autopsies in sudden and unnatural deaths: A scoping review|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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Latest 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...)
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