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'''"[[Journal:Data without software are just numbers|Data without software are just numbers]]"'''
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


Great strides have been made to encourage researchers to [[Archival informatics|archive]] data created by research and provide the necessary systems to support their storage. Additionally, it is recognized that data are meaningless unless their provenance is preserved, through appropriate [[metadata]]. Alongside this is a pressing need to ensure the [[Software quality|quality]] and archiving of the software that generates data, through simulation and control of experiment or data collection, and that which [[Data analysis|analyzes]], modifies, and draws value from raw data. In order to meet the aims of reproducibility, we argue that [[Information management|data management]] alone is insufficient: it must be accompanied by [[Systems development life cycle|good software practices]], the training to facilitate it, and the support of stakeholders, including appropriate recognition for software as a research output. ('''[[Journal:Data without software are just numbers|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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