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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Mackert JournalOfMedIntRes2016 18-10.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:Health literacy and health information technology adoption: The potential for a new digital divide|Health literacy and health information technology adoption: The potential for a new digital divide]]"'''
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


Approximately one-half of American adults exhibit low health literacy and thus struggle to find and use [[Health informatics|health information]]. Low health literacy is associated with negative outcomes, including overall poorer health. [[Health information technology]] (HIT) makes health information available directly to patients through electronic tools including [[patient portal]]s, wearable technology, and mobile apps. The direct availability of this [[information]] to patients, however, may be complicated by misunderstanding of HIT privacy and information sharing. The purpose of this study was to determine whether health literacy is associated with patients’ use of four types of HIT tools: fitness and nutrition apps, activity trackers, and patient portals. ('''[[Journal:Health literacy and health information technology adoption: The potential for a new digital divide|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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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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