Ahead of May Deadline, EU Publishes Third Draft of Code of Practice for General-Purpose AI Models
Streamlined Code of Practice
Ahead of a May deadline to lock in guidance for providers of general-purpose AI (GPAI) models on complying with provisions of the EU AI Act that apply to Big AI, a third draft of the Code of Practice was published on Tuesday. The Code has been in formulation since last year, and this draft is expected to be the last revision round before the guidelines are finalized in the coming months.
Code of Practice Overview
The EU’s risk-based rulebook for AI includes a sub-set of obligations that apply only to the most powerful AI model makers, covering areas such as transparency, copyright, and risk mitigation. The Code is aimed at helping GPAI model makers understand how to meet the legal obligations and avoid the risk of sanctions for non-compliance. AI Act penalties for breaches of GPAI requirements, specifically, could reach up to 3% of global annual turnover.
Streamlined Structure
The latest revision of the Code is billed as having "a more streamlined structure with refined commitments and measures" compared to earlier iterations, based on feedback on the second draft that was published in December.
Feedback and Finalization
Further feedback, working group discussions, and workshops will feed into the process of turning the third draft into final guidance. Experts hope to achieve greater "clarity and coherence" in the final adopted version of the Code. The draft is broken down into a handful of sections covering commitments for GPAIs, along with detailed guidance for transparency and copyright measures. There is also a section on safety and security obligations that apply to the most powerful models (with so-called systemic risk, or GPAISR).
Transparency and Copyright
On transparency, the guidance includes an example of a model documentation form GPAIs might be expected to fill in to ensure that downstream deployers of their technology have access to key information to help with their own compliance.
Copyright Controversy
The copyright section likely remains the most immediately contentious area for Big AI. The current draft is replete with terms like "best efforts", "reasonable measures", and "appropriate measures" when it comes to complying with commitments such as respecting rights requirements when crawling the web to acquire data for model training, or mitigating the risk of models churning out copyright-infringing outputs.
US Pressure
Unmentioned in the EU press release about the latest draft are blistering attacks on European lawmaking generally, and the bloc’s rules for AI specifically, coming out of the U.S. administration led by President Donald Trump. At the Paris AI Action summit last month, U.S. Vice President JD Vance dismissed the need to regulate to ensure AI is applied safety, and warned Europe that overregulation could kill the golden goose.
Conclusion
The EU’s efforts to establish a Code of Practice for general-purpose AI models are crucial in ensuring the responsible development and deployment of AI systems. By providing a clear framework for compliance, the Code can help mitigate the risks associated with AI and promote its safe and ethical use.
FAQs
Q: What is the EU AI Act?
A: The EU AI Act is a set of regulations aimed at ensuring the safe and ethical development and deployment of AI systems.
Q: What is the Code of Practice for General-Purpose AI Models?
A: The Code of Practice is a set of guidelines aimed at helping providers of general-purpose AI models comply with the provisions of the EU AI Act that apply to Big AI.
Q: What is the deadline for the Code of Practice?
A: The deadline for the Code of Practice is May.
Q: What is the purpose of the Code of Practice?
A: The purpose of the Code of Practice is to help GPAI model makers understand how to meet the legal obligations and avoid the risk of sanctions for non-compliance.
Q: What is the scope of the Code of Practice?
A: The scope of the Code of Practice includes commitments for GPAIs, along with detailed guidance for transparency and copyright measures, and a section on safety and security obligations that apply to the most powerful models.
