# Why Companies "Democratise" Artificial Intelligence: The Case of Open Source Software Donations

arXiv: https://arxiv.org/abs/2409.17876 · HTML: https://mlsanity.com/paper/2409.17876/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 157 references that are in the map.
- First posted on arXiv 26 Sep 2024.

## Builds on (most cited first, 18 of 18)

- [Opening up ChatGPT: Tracking openness, transparency, and accountability in instruction-tuned text generators](https://mlsanity.com/paper/2307.05532/) (2023)
- [Hype, Sustainability, and the Price of the Bigger-is-Better Paradigm in AI](https://mlsanity.com/paper/2409.14160/) (2024)
- [Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives](https://mlsanity.com/paper/2311.09227/) (2023)
- [Democratising AI: Multiple Meanings, Goals, and Methods](https://mlsanity.com/paper/2303.12642/) (2023)
- [The AI Community Building the Future? A Quantitative Analysis of Development Activity on Hugging Face Hub](https://mlsanity.com/paper/2405.13058/) (2024)
- [BigScience: A Case Study in the Social Construction of a Multilingual Large Language Model](https://mlsanity.com/paper/2212.04960/) (2022)
- [The Future of Open Human Feedback](https://mlsanity.com/paper/2408.16961/) (2024)
- [Towards Openness Beyond Open Access: User Journeys through 3 Open AI Collaboratives](https://mlsanity.com/paper/2301.08488/) (2023)
- [Public-private funding models in open source software development: A case study on scikit-learn](https://mlsanity.com/paper/2404.06484/) (2024)
- [Systematic Literature Review of Commercial Participation in Open Source Software](https://mlsanity.com/paper/2405.16880/) (2024)
- [Do software firms collaborate or compete? A model of coopetition in community-initiated OSS projects](https://mlsanity.com/paper/1808.06489/) (2018)
- [Collaboration in the open-source arena: The WebKit case](https://mlsanity.com/paper/1401.5996/) (2014)
- [Cooperation among competitors in the open-source arena: The case of OpenStack](https://mlsanity.com/paper/1612.09462/) (2016)
- [The Shifting Sands of Motivation: Revisiting What Drives Contributors in Open Source](https://mlsanity.com/paper/2101.10291/) (2021)
- [How Firms Adapt and Interact in Open Source Ecosystems: Analyzing Stakeholder Influence and Collaboration Patterns](https://mlsanity.com/paper/2208.02628/) (2022)
- [Lessons Learned from Applying Social Network Analysis on an Industrial Free/Libre/Open Source Software Ecosystem](https://mlsanity.com/paper/1507.04587/) (2015)
- [Coopetition of software firms in Open source software ecosystems](https://mlsanity.com/paper/1711.07049/) (2017)
- [Public Sector Platforms going Open: Creating and Growing an Ecosystem with Open Collaborative Development](https://mlsanity.com/paper/2208.00510/) (2022)

## Built on by (most cited first, 4 of 4)

- [Characterising Open Source Co-opetition in Company-hosted Open Source Software Projects: The Cases of PyTorch, TensorFlow, and Transformers](https://mlsanity.com/paper/2410.18241/) (2024)
- [A Cartography of Open Collaboration in Open Source AI: Mapping Practices, Motivations, and Governance in 14 Open Large Language Model Projects](https://mlsanity.com/paper/2509.25397/) (2025)
- [Opening the Scope of Openness in AI](https://mlsanity.com/paper/2505.06464/) (2025)
- [The Right to Be Remembered: Preserving Maximally Truthful Digital Memory in the Age of AI](https://mlsanity.com/paper/2510.16206/) (2025)

## Abstract (arXiv)

Companies claim to "democratise" artificial intelligence (AI) when they donate AI open source software (OSS) to non-profit foundations or release AI models, among others, but what does this term mean and why do they do it? As the impact of AI on society and the economy grows, understanding the commercial incentives behind AI democratisation efforts is crucial for ensuring these efforts serve broader interests beyond commercial agendas. Towards this end, this study employs a mixed-methods approach to investigate commercial incentives for 43 AI OSS donations to the Linux Foundation. It makes contributions to both research and practice. It contributes a taxonomy of both individual and organisational social, economic, and technological incentives for AI democratisation. In particular, it highlights the role of democratising the governance and control rights of an OSS project (i.e., from one company to open governance) as a structural enabler for downstream goals, such as attracting external contributors, reducing development costs, and influencing industry standards, among others. Furthermore, OSS donations are often championed by individual developers within companies, highlighting the importance of the bottom-up incentives for AI democratisation. The taxonomy provides a framework and toolkit for discerning incentives for other AI democratisation efforts, such as the release of AI models. The paper concludes with a discussion of future research directions.