Difference between revisions of "Template:Article of the week"

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Tomlinson JofMolDiag2022 S1525-1578-22.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Niszczota EconBusRev23 9-2.png|240px]]</div>
'''"[[Journal:A model for design and implementation of a laboratory information management system specific to molecular pathology laboratory operations|A model for design and implementation of a laboratory information management system specific to molecular pathology laboratory operations]]"'''
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


The Molecular Pathology Section of Cleveland Clinic (Cleveland, OH) has undergone enhancement of its testing portfolio and processes. An electronic- and paper-based [[Information management|data management]] system was replaced with a commercially available [[laboratory information management system]] (LIMS) solution, a separate [[bioinformatics]] platform, customized test-interpretation applications, a dedicated [[Accessioning (medical)|accessioning]] service, and a results-releasing solution. The LIMS solution manages complex [[workflow]]s, large-scale data packets, and process automation. However, a customized approach was required for the LIMS since a survey of commercially available off-the-shelf (COTS) software solutions revealed none met the diverse and complex needs of Cleveland Clinic's [[molecular pathology]] service ... ('''[[Journal:A model for design and implementation of a laboratory information management system specific to molecular pathology laboratory operations|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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''Recently featured'':
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{{flowlist |
{{flowlist |
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}}
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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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