Part of the Deep Dive: AI Webinar Series
This presentation will delve into the legal perspectives surrounding the upcoming EU AI Act, with a specific focus on the role of open source, non-profit, and academic research and development in the AI ecosystem. The session will cover crucial topics such as defining open data and AI/ML systems, copyrightability of AI outputs, control over code and data, data privacy, and fostering fair competition while encouraging open innovation. Drawing from existing and upcoming AI regulations globally, we will present recommendations to facilitate the growth of an open ecosystem while safeguarding ethical and accountable AI practices. Join this session for an insightful exploration of the legal landscape shaping the future of open source.
What You Will Learn in the Presentation:
The key problems faced by open source projects under the draft EU AI Act.
The significance of clear definitions and exemptions for open source AI components.
The need for effective coordination and governance to support open source development.
The challenges in implementing the R&D exception for open source AI.
The importance of proportional requirements for “foundation models” to encourage open source innovation and competition.
Recommendation to address the concerns of open source platform providers and ensure an open and thriving AI ecosystem under the AI Act.
In this webinar hosted by the Open Source Initiative as a part of the “Deep Dive: Defining Open Source AI” series, Katharina Koerner, from the Tech Diplomacy Network, discusses the implications of the upcoming EU AI Act for the open source ecosystem. She highlights the significance of open source in the EU and the various initiatives supporting it, emphasizing that the EU is committed to open source as a driver of innovation and accessibility. Katharina provides an overview of the draft EU AI Act, which categorizes AI systems based on risk levels and outlined the scope of the Act, including its application to providers, deployers, importers, and distributors. She also discusses exceptions for open source, emphasizing that collaborative development and open repositories are not considered making AI systems available on the market unless they turn commercial. Furthermore, she explains the unique challenges and requirements related to foundation models within the AI Act, underscoring the need for compliance, transparency, and responsible practices in the open source AI community to prepare for the impending regulations.