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:Fig1 Pineda-Pampliega EFSAJournal2023 20-S2.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:Developing a framework for open and FAIR data management practices for next generation risk- and benefit assessment of fish and seafood|Developing a framework for open and FAIR data management practices for next generation risk- and benefit assessment of fish and seafood]]"'''
'''"[[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]"'''


[[Risk assessment|Risk and risk–benefit assessments]] of food are complex exercises, in which access to and use of several disconnected individual stand-alone [[database]]s is required to obtain hazard and exposure information. Data obtained from such databases ideally should be in line with the [[Journal:The FAIR Guiding Principles for scientific data management and stewardship|FAIR principles]], i.e. the data must be findable, accessible, interoperable, and reusable. However, often cases are encountered when one or more of these principles are not followed. In this project, we set out to assess if existing commonly used databases in risk assessment are in line with the FAIR principles ... ('''[[Journal:Developing a framework for open and FAIR data management practices for next generation risk- and benefit assessment of fish and seafood|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 />
''Recently featured'':
''Recently featured'':
{{flowlist |
{{flowlist |
* [[Journal:An extract-transform-load process design for the incremental loading of German real-world data based on FHIR and OMOP CDM: Algorithm development and validation|An extract-transform-load process design for the incremental loading of German real-world data based on FHIR and OMOP CDM: Algorithm development and validation]]
* [[Journal:Geochemical biodegraded oil classification using a machine learning approach|Geochemical biodegraded oil classification using a machine learning approach]]
* [[Journal:Potency and safety analysis of hemp-derived delta-9 products: The hemp vs. cannabis demarcation problem|Potency and safety analysis of hemp-derived delta-9 products: The hemp vs. cannabis demarcation problem]]
* [[Journal:Knowledge of internal quality control for laboratory tests among laboratory personnel working in a biochemistry department of a tertiary care center: A descriptive cross-sectional study|Knowledge of internal quality control for laboratory tests among laboratory personnel working in a biochemistry department of a tertiary care center: A descriptive cross-sectional study]]
* [[Journal:The NOMAD Artificial Intelligence Toolkit: Turning materials science data into knowledge and understanding|The NOMAD Artificial Intelligence Toolkit: Turning materials science data into knowledge and understanding]]
* [[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study]]
}}
}}

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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