Deep Dive: AI Webinar Series (2023)
As part of our Deep Dive:AI, the Open Source Initiative (OSI) is gathering a diverse collection of leaders to collaborate in drafting a definition for “Open Source AI.” Speakers from law, academia, NGOs, enterprise, and the OSS community will present webinars addressing pressing issues and potential solutions in our development and use of AI systems.
As the leading voice on the policies and principles of Open Source, OSI is the steward of the Open Source Definition, the foundation of the modern software ecosystem. The time has come for a shared set of principles to create the permission-less, pragmatic, and simplified Definition of Open Source AI.
Video recordings
The Turing Way Fireside Chat: Who is building Open Source AI?
Jennifer Ding, Arielle Bennett, Anne Steele, Kirstie Whitaker, Marzieh Fadaee, Abinaya Mahendiran, David Gray Widder, Mophat Okinyi
Operationalising the SAFE-D principles for Open Source AI
Kirstie Whitaker
Commons-based data governance
Alek Tarkowski, Zuzanna Warso
Preempting the Risks of Generative AI: Responsible Best Practices for Open-Source AI Initiatives
Monica Lopez, PhD
Data privacy in AI
Michael Meehan
Perspectives on Open Source Regulation in the upcoming EU AI Act
Katharina Koerner
Data Cooperatives and Open Source AI
Tarunima Prabhakar, Siddharth Manohar
Fairness & Responsibility in LLM-based Recommendation Systems: Ensuring Ethical Use of AI Technology
Rohan Singh Rajput
Challenges welcoming AI in openly-developed open source projects
Thierry Carrez, Davanum Srinivas, Diane Mueller
Opening up ChatGPT: a case study in operationalizing openness in AI
Andreas Liesenfeld, Mark Dingemanse
Open source AI between enablement, transparency and reproducibility
Ivo Emanuilov, Jutta Suksi
Federated Learning: A Paradigm Shift for Secure and Private Data Analysis
Dimitris Stripelis
Should OpenRAIL licenses be considered OS AI Licenses?
Daniel McDuff, Danish Contractor, Luis Villa, Jenny Lee
Copyright — Right Answer for Open Source Code, Wrong Answer for Open Source AI?
McCoy Smith
Should we use open source licenses for ML/AI models?
Mary Hardy
Covering your bases with IP Indemnity
Justin Dorfman, Tammy Zhu, Samantha Mandell
The Ideology of FOSS and AI: What “Open” means relating to platforms and black box systems
Mike Nolan
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