ChatGPT and artificial hallucinations in stem cell research : assessing the accuracy of generated references - a preliminary study
Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc..
Stem cell research has the transformative potential to revolutionize medicine. Language models like ChatGPT, which use artificial intelligence (AI) and natural language processing, generate human-like text that can aid researchers. However, it is vital to ensure the accuracy and reliability of AI-generated references. This study assesses Chat Generative Pre-Trained Transformer (ChatGPT)'s utility in stem cell research and evaluates the accuracy of its references. Of the 86 references analyzed, 15.12% were fabricated and 9.30% were erroneous. These errors were due to limitations such as no real-time internet access and reliance on preexisting data. Artificial hallucinations were also observed, where the text seems plausible but deviates from fact. Monitoring, diverse training, and expanding knowledge cut-off can help to reduce fabricated references and hallucinations. Researchers must verify references and consider the limitations of AI models. Further research is needed to enhance the accuracy of such language models. Despite these challenges, ChatGPT has the potential to be a valuable tool for stem cell research. It can help researchers to stay up-to-date on the latest developments in the field and to find relevant information.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:85 |
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| Enthalten in: |
Annals of medicine and surgery (2012) - 85(2023), 10 vom: 04. Okt., Seite 5275-5278 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Sharun, Khan [VerfasserIn] |
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| Links: |
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| Themen: |
Artificial intelligence |
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| Anmerkungen: |
Date Revised 18.10.2023 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1097/MS9.0000000000001228 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. | ||
| 520 | |a Stem cell research has the transformative potential to revolutionize medicine. Language models like ChatGPT, which use artificial intelligence (AI) and natural language processing, generate human-like text that can aid researchers. However, it is vital to ensure the accuracy and reliability of AI-generated references. This study assesses Chat Generative Pre-Trained Transformer (ChatGPT)'s utility in stem cell research and evaluates the accuracy of its references. Of the 86 references analyzed, 15.12% were fabricated and 9.30% were erroneous. These errors were due to limitations such as no real-time internet access and reliance on preexisting data. Artificial hallucinations were also observed, where the text seems plausible but deviates from fact. Monitoring, diverse training, and expanding knowledge cut-off can help to reduce fabricated references and hallucinations. Researchers must verify references and consider the limitations of AI models. Further research is needed to enhance the accuracy of such language models. Despite these challenges, ChatGPT has the potential to be a valuable tool for stem cell research. It can help researchers to stay up-to-date on the latest developments in the field and to find relevant information | ||
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