ai-regulation-practices

Key points of this article:

  • Anthropic is signing the EU’s General-Purpose AI Code of Practice to promote responsible AI development and align with safety standards.
  • The Code emphasizes transparency, risk assessment, and collaboration with third-party organizations to manage systemic risks associated with AI.
  • This commitment reflects a broader trend in the tech industry towards formalizing safety and accountability in AI governance as technology evolves.
Good morning, this is Haru. Today is 2025‑07‑22—on this day in 1933, Wiley Post became the first person to fly solo around the world, a quiet reminder of how far innovation can take us; now, we turn to how today’s AI pioneers are navigating their own frontiers.

AI Development Safety

As artificial intelligence continues to evolve at a rapid pace, governments and companies around the world are working to ensure that its development remains safe, transparent, and beneficial for society. In this context, Anthropic, one of the leading AI research firms, has announced its intention to sign the European Union’s General-Purpose AI Code of Practice. This move reflects growing efforts across the tech industry to align with emerging regulatory frameworks while maintaining the flexibility needed to keep up with fast-moving innovation.

EU Code of Practice

The EU’s Code of Practice is designed to promote responsible AI development by encouraging transparency, safety, and accountability—principles that Anthropic says it has long supported. The Code works in tandem with broader initiatives like the EU AI Act and the AI Continent Action Plan, aiming to create a balanced environment where innovation can thrive without compromising public trust or safety. By signing on, Anthropic commits to adopting structured risk assessment processes and safety standards that help identify and mitigate potential harms from advanced AI systems.

Managing Systemic Risks

One of the key features of the Code is its emphasis on documenting how companies manage systemic risks. For instance, it includes guidelines for evaluating threats related to chemical or biological misuse—a concern as powerful AI models become more capable. Anthropic notes that these requirements build upon its own internal policies, such as its Responsible Scaling Policy, which outlines how it plans to scale AI systems safely over time. The company has already updated this policy several times based on real-world insights, showing a willingness to adapt as new challenges emerge.

Collaboration for Standards

However, implementing such standards isn’t without complexity. Different types of risks require different approaches, and there’s still no universal agreement on best practices across the industry. That’s why Anthropic emphasizes collaboration with third-party organizations like the Frontier Model Forum—groups that help bridge technical knowledge and policymaking by developing shared evaluation methods and safety benchmarks. These partnerships are seen as essential for creating policies that are both rigorous and adaptable.

Ongoing Regulatory Engagement

Looking at Anthropic’s recent history, this announcement fits into a broader pattern of cautious but proactive engagement with regulation. Over the past two years, the company has consistently voiced support for responsible AI governance while also contributing technical insights through forums and research publications. Its Responsible Scaling Policy was first introduced nearly two years ago and has since evolved in response to both internal learnings and external developments in the field. Signing onto the EU Code seems like a natural next step in this ongoing journey rather than a sudden shift in direction.

A Safer Future Ahead

In conclusion, Anthropic’s decision to align with the EU’s Code of Practice highlights an important moment in global AI governance: one where companies are beginning to formalize their commitments to safety and transparency in partnership with regulators. While challenges remain—particularly around defining consistent risk management practices—the move suggests a growing maturity in how frontier AI firms approach their responsibilities. For everyday users and professionals alike, it’s reassuring to see these conversations taking place not just within companies but also across borders and sectors. As technology continues to advance, thoughtful collaboration between industry and government will likely play a key role in shaping how we all benefit from AI in the years ahead.

Thanks for spending a moment here today—it’s encouraging to see thoughtful steps like these shaping the future of AI, and I hope you’ll join me again as we continue to follow how this story unfolds.

Term explanations

Artificial Intelligence (AI): A branch of computer science that focuses on creating machines capable of performing tasks that typically require human intelligence, such as understanding language, recognizing patterns, and making decisions.

Regulatory Frameworks: A set of rules and guidelines established by governments or organizations to ensure that certain activities, like the development of technology, are conducted safely and ethically.

Risk Assessment: The process of identifying and evaluating potential problems or dangers that could arise from a particular action or decision, especially in the context of safety and security.