Open-Source Lessons for Regulating Open ML Systems in the EU: The ai Act
The contact Union (EU) is currently debating the new artificial intelligence (ai) Act, a groundbreaking legislation aiming to regulate ai while fostering technological advancement. A key element of this Act is its support for open-source, non-profit, and academic research and development in the ai ecosystem. This approach can ensure safe, transparent, and accountable ai systems that benefit all EU citizens.
Encouraging Open ai Development
Drawing from the success of open-source software development, policymakers can create regulations that foster open ai development while safeguarding user interests. By providing exemptions and reasonable requirements for open Machine Learning (ML) systems, the EU can encourage innovation and competition in the ai market while preserving a vibrant open-source ecosystem.
Organizations like GitHub, Hugging Face, EleutherAI, and Creative Commons, representing both commercial and nonprofit stakeholders, have released a policy paper urging EU policymakers to protect open-source innovation. They propose the following:
Advantages of Open-Source ai Development
Open-source ai development offers several advantages, including transparency, inclusivity, and modularity. It enables stakeholders to collaborate and build on each other’s work, leading to more robust and diverse ai models. For instance, the popular community, which has become a leading open-source ML lab, releases pre-trained models and code libraries that have facilitated foundational research and reduced barriers to developing large ai models.
Another example is the Project, which brought together over 1200 multidisciplinary researchers, emphasizing the importance of facilitating direct access to ai components across institutions and disciplines. Such collaborations have democratized access to large ai models, allowing researchers to fine-tune and adapt them to various languages and specific tasks, ultimately contributing to a more diverse and representative ai landscape.
Transparency and Accountability in Open ai
Open research and development also promote transparency and accountability in ai systems. For example, the non-profit research organization, OpenAI, released openCLIP models, which have been instrumental in identifying and addressing biases in ai applications. Access to training data and model components allows researchers and the public to scrutinize the inner workings of ai systems, challenging misleading or erroneous claims.
Striking a Balance: Regulation and Open ai Ecosystem
The success of the EU’s ai Act hinges on achieving a balance between regulation and support for the open ai ecosystem. While transparency and openness are essential, regulations must also mitigate risks, ensure standards, and establish clear liability for ai systems’ potential harms.
As the EU shapes the future of ai regulation, embracing open source and open science will be crucial to ensure that ai technology benefits all citizens while maintaining trust and security. Implementing the recommendations provided by organizations representing stakeholders in the open ai ecosystem can foster a collaborative, transparent, and innovative environment, making Europe a leader in responsible development and deployment of ai technologies.
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