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'''"[[Journal:Laboratory information system – Where are we today?|Laboratory information system – Where are we today?]]"'''
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Niszczota EconBusRev23 9-2.png|240px]]</div>
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


Wider implementation of [[laboratory information system]]s (LIS) in [[Clinical laboratory|clinical laboratories]] in Serbia was initiated 10 years ago. The first LIS in the Railway Health Care Institute was implemented nine years ago. Before the LIS was initiated, manual admission procedures limited daily output of patients. Moreover, manual entering of patient data and ordering tests on analyzers was problematic and time-consuming. After completing tests, [[laboratory]] personnel had to write results in a patient register (with potential errors) and provide invoices for health insurance organizations. The first LIS brought forward some advantages with regards to these obstacles, but it also showed various weaknesses. These can be summarized as rigidity of the system and inability to fulfill user expectation. After four years of use, we replaced this system with another LIS. Hence, the main aim of this paper is to evaluate the advantages of using LIS in the Railway Health Care Institute's laboratory and also to discuss further possibilities for its application. ('''[[Journal:Laboratory information system – Where are we today?|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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