Plant blindness and diversity in AI language models.
ChatGPT
artificial intelligence models
diversity
large language models
plant blindness
Journal
Trends in plant science
ISSN: 1878-4372
Titre abrégé: Trends Plant Sci
Pays: England
ID NLM: 9890299
Informations de publication
Date de publication:
10 2023
10 2023
Historique:
received:
23
05
2023
revised:
13
06
2023
accepted:
20
06
2023
medline:
18
9
2023
pubmed:
5
8
2023
entrez:
4
8
2023
Statut:
ppublish
Résumé
Large language models (LLMs) will benefit science by accelerating task performance. We explored whether answers generated by ChatGPT (generative pretrained transformer) to questions of biology are sufficiently diverse. 'Plant awareness' in ChatGPT answers was found to be highly variable, illustrating the importance of scientists being involved in validating the data and methods used to train artificial intelligence (AI) models.
Identifiants
pubmed: 37541814
pii: S1360-1385(23)00207-8
doi: 10.1016/j.tplants.2023.06.016
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1095-1097Informations de copyright
Copyright © 2023 Elsevier Ltd. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of interests The authors declare no conflicts of interest.