Cited by 109Ethics and Social Impacts of AIAcademic Publishing and Open AccessScientific Computing and Data Management

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Why open-source generative AI models are an ethical way forward for science

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Spirling, Arthur·2023·Nature

DOI 10.1038/d41586-023-01295-4

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Authors: Spirling, A.
Affiliations: New York University (US)
Corresponding author: Spirling, Arthur
ORCID: Spirling, Arthur
Venue: Nature
Publisher: Springer Science and Business Media LLC
Published: 2023-04-18
Volume: 616
Issue: 7957
Pages: 413-413
ISSN: 0028-0836 (ISSN-L)
1476-4687
DOI: 10.1038/d41586-023-01295-4
OpenAlex: W4366277658
Cited by: 104
References: 0
Citations by year: 2026: 23 · 2025: 32 · 2024: 28 · 2023: 20
FWCI: 26.08
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Nature (publishedVersion)
PubMed (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
Social Sciences › Library and Information Sciences › Academic Publishing and Open Access
Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
Keywords: open-source models, generative AI, large language models, research ethics, reproducibility, transparency, scientific research
MeSH terms: Artificial Intelligence, Natural Language Processing, Research, Reproducibility of Results, Access to Information

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