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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Martins BMCMedInfoDecMak2017 17-1.gif|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Niszczota EconBusRev23 9-2.png|240px]]</div>
'''"[[Journal:The effect of a test ordering software intervention on the prescription of unnecessary laboratory tests - A randomized controlled trial|The effect of a test ordering software intervention on the prescription of unnecessary laboratory tests - A randomized controlled trial]]"'''
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''
The way [[electronic health record]] and [[Computerized physician order entry|laboratory test ordering system]] software is designed may influence physicians’ prescription. A randomized controlled trial was performed to measure the impact of a diagnostic and laboratory tests ordering system software modification.


Participants were family physicians working and prescribing diagnostic and [[laboratory]] tests. The intervention group had modified software with basic shortcut menu changes, where some tests were withdrawn or added, and with the implementation of an evidence-based [[clinical decision support system]] based on United States Preventive Services Task Force (USPSTF) recommendations. This intervention group was compared with typically used software (control group).
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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The outcomes were the number of tests prescribed from those: withdrawn from the basic menu; added to the basic menu; marked with green dots (USPSTF’s grade A and B); and marked with red dots (USPSTF’s grade D). ('''[[The effect of a test ordering software intervention on the prescription of unnecessary laboratory tests - A randomized controlled trial|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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