https://github.com/tamaraaPrs/awesome-openness-AI
Curated list of papers or contents about openness in AI, in particular, in the context of AI ethics
https://github.com/tamaraaPrs/awesome-openness-AI
Last synced: 3 months ago
JSON representation
Curated list of papers or contents about openness in AI, in particular, in the context of AI ethics
- Host: GitHub
- URL: https://github.com/tamaraaPrs/awesome-openness-AI
- Owner: tamaraaPrs
- Created: 2024-03-10T23:10:04.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-03-11T05:49:19.000Z (over 1 year ago)
- Last Synced: 2025-08-28T05:43:34.172Z (3 months ago)
- Homepage:
- Size: 43 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome_ai_agents - Awesome-Openness-Ai - Curated list of papers or contents about openness in AI, in particular, in the context of AI ethics (Building / Ethics)
README
# Awesome Openness in AI [](https://awesome.re)
**Openness** in the context of AI encompasses all principles or philosophies surrounding the ability and right to freely use, share, modify, and study the AI system or its components (weights, code, dataset, research paper, development framework, etc) without restriction of purpose and without discrimination against individuals or groups, similar to other philosophies of openness such as Open Source or Open Access.
This repo collects relevant papers or other content for research on openness in the field of AI and AI ethics. Given that the research on openness in AI is still relatively recent and lacks scientific literature, this repo also incorporates blog posts from reliable sources (such as university websites, recognized organizations in the field, etc).
If you want to contribute, feel free to send me a message or make a pull request!
## Table of Contents
1. [Definitions, degrees of openness and terminologies](#definitions-degrees-of-openness-and-terminologies)
2. [Costs, risks and benefits](#costs-risks-and-benefits)
3. [AI systems described as 'Open' or 'Open Source'](#ai-systems-described-as-open-or-open-source)
## Definitions, degrees of openness and terminologies
- **Deep Dive: AI**
*Open Source Initiative*
since 2022 [[Website]](https://opensource.org/deepdive)
- **The Gradient of Generative AI Release: Methods and Considerations**
*I. Solaiman*
Proceedings of the 2023 ACM conference on fairness, accountability, and transparency, 2023, [[Paper]](http://arxiv.org/abs/2302.04844)
- **Opening up ChatGPT: Tracking openness, transparency, and accountability in instruction-tuned text generators**
*A. Liesenfeld, A. Lopez, and M. Dingemanse*
Proceedings of the 5th International Conference on Conversational User Interfaces, Jul. 2023, [[Paper]](https://arxiv.org/abs/2307.05532) [[Live Table]](https://opening-up-chatgpt.github.io/)
- **AI weights are not open ‘source.’**
*Sid Sijbrandij*
Jun 27, 2023, [[Blog Post]](https://opencoreventures.com/blog/2023-06-27-ai-weights-are-not-open-source/)
- **The Time Is Now to Develop Community Norms for the Release of Foundation Models.**
*Percy Liang, Rishi Bommasani, Kathleen Creel, and Rob Reich*
May 17, 2022, [[Blog Post]](https://hai.stanford.edu/news/time-now-develop-community-norms-release-foundation-models)
- **Beyond “Release” vs. “Not Release”**
*Girish Sastry*
2021, [[Blog Post]](https://crfm.stanford.edu/commentary/2021/10/18/sastry.html)
## Costs, risks and benefits
- **Hazards from Increasingly Accessible Fine-Tuning of Downloadable Foundation Models**
*A. Chan, B. Bucknall, H. Bradley, and D. Krueger*
arXiv, Dec. 22, 2023, [[Paper]](http://arxiv.org/abs/2312.14751)
- **Open-Sourcing Highly Capable Foundation Models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives.**
*E. Seger et al.*
arXiv, Sep. 29, 2023, [[Paper]](http://arxiv.org/abs/2311.09227)
- **Limits and Possibilities for ‘Ethical AI’ in Open Source: A Study of Deepfakes**
*D. G. Widder, D. Nafus, L. Dabbish, and J. Herbsleb*
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, Jun. 2022, [[Paper]](https://dl.acm.org/doi/abs/10.1145/3531146.3533779)
- **The tension between openness and prudence in AI research**
*J. Whittlestone and A. Ovadya*
arXiv, Jan. 13, 2020, [[Paper]](10.48550/arXiv.1910.01170)
- **Open (For Business): Big Tech, Concentrated Power, and the Political Economy of Open AI**
*D. G. Widder, S. West, and M. Whittaker*
Aug. 17, 2023, [[Paper]](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4543807)
- **Strategic Implications of Openness in AI Development**
*N. Bostrom*
Global Policy, 2017, [[Paper]](https://onlinelibrary.wiley.com/doi/full/10.1111/1758-5899.12403)
- **The Offense-Defense Balance of Scientific Knowledge: Does Publishing AI Research Reduce Misuse?**
*T. Shevlane and A. Dafoe*
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, in AIES ’20, Feb. 2020, [[Paper]](https://arxiv.org/abs/2001.00463)
- **How Open Source Machine Learning Software Shapes AI**
*M. Langenkamp*
Thesis, Massachusetts Institute of Technology, Nov. 01, 2023, [[Paper]](https://dspace.mit.edu/handle/1721.1/145076)
- **Democratising AI: Multiple Meanings, Goals, and Methods**
*E. Seger, A. Ovadya, D. Siddarth, B. Garfinkel, and A. Dafoe*
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, in AIES ’23, Aug. 2023, [[Paper]](https://arxiv.org/abs/2303.12642)
- **Building open-source AI**
*Y. R. Shrestha, G. von Krogh, and S. Feuerriegel*
Nature Computational Science, 2023, [[Paper]](https://www.nature.com/articles/s43588-023-00540-0#:~:text=Artificial%20intelligence%20(AI)%20drives%20innovation,%2C%20collaboration%2C%20responsibility%20and%20interoperability)
- **On the Societal Impact of Open Foundation Models**
*S. Kapoor et al.*
2024, [[Paper]](https://crfm.stanford.edu/open-fms/paper.pdf) [[Website]](https://crfm.stanford.edu/open-fms/#:~:text=Open%20foundation%20models%20can%20distribute,accelerate%20science%2C%20and%20enable%20transparency)
## AI systems described as 'Open' or 'Open Source'
- **Llama 2 (Meta)** [[Paper]](https://arxiv.org/abs/2307.09288) [[Model Card]](https://github.com/facebookresearch/llama/blob/main/MODEL_CARD.md) [[Download weights]](https://llama.meta.com/llama-downloads) [[Inference Code]](https://github.com/facebookresearch/llama)
- **Meta’s LLaMa 2 license is not Open Source**, *Open Source Initiative*, July 20, 2023, [[Blog Post]](https://opensource.org/blog/metas-llama-2-license-is-not-open-source)
- **BLOOM and BLOOMZ (BigScience)** [[Paper]](https://arxiv.org/abs/2211.05100) [[Model Card]](https://huggingface.co/bigscience/bloomz) [[Github]](https://github.com/bigscience-workshop/xmtf)
- **Alpaca (Stanford)** [[Website]](https://crfm.stanford.edu/2023/03/13/alpaca.html) [[Model Card]](https://github.com/tatsu-lab/stanford_alpaca/blob/main/model_card.md) [[Github]](https://github.com/tatsu-lab/stanford_alpaca)
- **Mistral** [[Website]](https://mistral.ai/) [[Dowload weights]](https://docs.mistral.ai/models/#downloading)