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Open-source artificial intelligence

Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share.[1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development.[1] Free and open-source software (FOSS) licenses, such as the Apache License, MIT License, and GNU General Public License, outline the terms under which open-source artificial intelligence can be accessed, modified, and redistributed.[2]

The open-source model provides widespread access to new AI technologies, allowing individuals and organizations of all sizes to participate in AI research and development.[3][4] This approach supports collaboration and allows for shared advancements within the field of artificial intelligence.[3][4] In contrast, closed-source artificial intelligence is proprietary, restricting access to the source code and internal components.[3] Only the owning company or organization can modify or distribute a closed-source artificial intelligence system, prioritizing control and protection of intellectual property over external contributions and transparency.[3][5][6] Companies often develop closed products in an attempt to keep a competitive advantage in the marketplace.[6] However, some experts suggest that open-source AI tools may have a development advantage over closed-source products and have the potential to overtake them in the marketplace.[6][4]

Popular open-source artificial intelligence project categories include large language models, machine translation tools, and chatbots.[7] For software developers to produce open-source artificial intelligence (AI) resources, they must trust the various other open-source software components they use in its development.[8][9] Open-source AI software has been speculated to have potentially increased risk compared to closed-source AI as bad actors may remove safety protocols of public models as they wish.[4] Similarly, closed-source AI has also been speculated to have an increased risk compared to open-source AI due to issues of dependence, privacy, opaque algorithms, corporate control and limited availability while potentially slowing beneficial innovation.[10][11][12]

There also is a debate about the openness of AI systems as openness is differentiated[13] – an article in Nature suggests that some systems presented as open, such as Meta's Llama 3, "offer little more than an API or the ability to download a model subject to distinctly non-open use restrictions". Such software has been criticized as "openwashing"[14] systems that are better understood as closed.[11] There are some works and frameworks that assess the openness of AI systems[15][13] as well as a new definition by the Open Source Initiative about what constitutes open source AI.[16][17][18]

  1. ^ a b "The Open Source AI Definition – 1.0". Open Source Initiative. Retrieved 2024-11-14.
  2. ^ "Licenses". Open Source Initiative. Retrieved 2024-11-14.
  3. ^ a b c d Hassri, Myftahuddin Hazmi; Man, Mustafa (2023-12-07). "The Impact of Open-Source Software on Artificial Intelligence". Journal of Mathematical Sciences and Informatics. 3 (2). doi:10.46754/jmsi.2023.12.006. ISSN 2948-3697.
  4. ^ a b c d Eiras, Francisco; Petrov, Aleksandar; Vidgen, Bertie; Schroeder, Christian; Pizzati, Fabio; Elkins, Katherine; Mukhopadhyay, Supratik; Bibi, Adel; Purewal, Aaron (2024-05-29), Risks and Opportunities of Open-Source Generative AI, arXiv:2405.08597
  5. ^ Isaac, Mike (2024-05-29). "What to Know About the Open Versus Closed Software Debate". The New York Times. Retrieved 2024-11-13.
  6. ^ a b c Solaiman, Irene (May 24, 2023). "Generative AI Systems Aren't Just Open or Closed Source". Wired.
  7. ^ Castelvecchi, Davide (29 June 2023). "Open-source AI chatbots are booming — what does this mean for researchers?". Nature. 618 (7967): 891–892. Bibcode:2023Natur.618..891C. doi:10.1038/d41586-023-01970-6. PMID 37340135.
  8. ^ Thummadi, Babu Veeresh (2021). "Artificial Intelligence (AI) Capabilities, Trust and Open Source Software Team Performance". In Denis Dennehy; Anastasia Griva; Nancy Pouloudi; Yogesh K. Dwivedi; Ilias Pappas; Matti Mäntymäki (eds.). Responsible AI and Analytics for an Ethical and Inclusive Digitized Society. 20th International Federation of Information Processing WG 6.11 Conference on e-Business, e-Services and e-Society, Galway, Ireland, September 1–3, 2021. Lecture Notes in Computer Science. Vol. 12896. Springer. pp. 629–640. doi:10.1007/978-3-030-85447-8_52. ISBN 978-3-030-85446-1.
  9. ^ Mitchell, James (2023-10-22). "How to Create Artificial intelligence Software". AI Software Developers. Retrieved 2024-03-31.
  10. ^ Cite error: The named reference 10.1038/d41586-023-03803-y was invoked but never defined (see the help page).
  11. ^ a b Widder, David Gray; Whittaker, Meredith; West, Sarah Myers (November 2024). "Why 'open' AI systems are actually closed, and why this matters". Nature. 635 (8040): 827–833. Bibcode:2024Natur.635..827W. doi:10.1038/s41586-024-08141-1. ISSN 1476-4687. PMID 39604616.
  12. ^ "What is open source AI and why is profit so important to the debate?". euronews. 20 February 2024. Retrieved 28 November 2024.
  13. ^ a b Liesenfeld, Andreas; Lopez, Alianda; Dingemanse, Mark (19 July 2023). "Opening up ChatGPT: Tracking openness, transparency, and accountability in instruction-tuned text generators". Proceedings of the 5th International Conference on Conversational User Interfaces. Association for Computing Machinery. pp. 1–6. arXiv:2307.05532. doi:10.1145/3571884.3604316. ISBN 979-8-4007-0014-9.
  14. ^ Liesenfeld, Andreas; Dingemanse, Mark (5 June 2024). "Rethinking open source generative AI: Open washing and the EU AI Act". The 2024 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery. pp. 1774–1787. doi:10.1145/3630106.3659005. ISBN 979-8-4007-0450-5.
  15. ^ White, Matt; Haddad, Ibrahim; Osborne, Cailean; Xiao-Yang Yanglet Liu; Abdelmonsef, Ahmed; Varghese, Sachin; Arnaud Le Hors (2024). "The Model Openness Framework: Promoting Completeness and Openness for Reproducibility, Transparency, and Usability in Artificial Intelligence". arXiv:2403.13784 [cs.LG].
  16. ^ "The Open Source AI Definition — by The Open Source Initiative". opensource.org. Retrieved 28 November 2024.
  17. ^ "We finally have a definition for open-source AI". MIT Technology Review. Retrieved 28 November 2024.
  18. ^ Robison, Kylie (28 October 2024). "Open-source AI must reveal its training data, per new OSI definition". The Verge. Retrieved 28 November 2024.

Open-source artificial intelligence

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