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:Fig8 Lee Sustain20 13-1.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:Towards a risk catalog for data management plans|Towards a risk catalog for data management plans]]"'''
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


[[Personal health record]]s (PHRs) have many benefits for things such as [[Public health surveillance|health surveillance]], [[Epidemiology|epidemiological surveillance]], self-control, links to various services, [[public health]] and health management, and international surveillance. The implementation of an international standard for interoperability is essential to accessing PHRs. In Taiwan, the nationwide exchange platform for [[electronic medical record]]s (EMRs) has been in use for many years. The [[Health Level 7|Health Level Seven International]] (HL7) Clinical Document Architecture (CDA) was used as the standard for those EMRs. However, the complication of implementing CDA became a barrier for many [[hospital]]s to realizing standard EMRs. In this study, we implemented a [[Health Level 7#Fast Healthcare Interoperability Resources (FHIR)|Fast Healthcare Interoperability Resources]] (FHIR)-based PHR transformation process, including a user interface module to review the contents of PHRs. ('''[[Journal:Towards a risk catalog for data management plans|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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