We appreciate NIST’s leadership on these issues and highlight below our key recommendations for each publication:

Generative AI Profile

• Enable full legal use of data to train AI systems, including copyrighted data and personal data;
• Acknowledge privacy issues implicated by long-term retention of documentation;
• Align recommended practices to organizations’ role in the AI ecosystem;
• Revise recommendations for obtaining independent audits;
• Tailor recommendations for red teaming to specific circumstances;
• Revise the trigger for conducting impact assessments;  

A Plan for Global Engagement on AI Standards  

• Continue support for private sector-led, multistakeholder, voluntary standards development;
• Maintain recommendation to prioritize supply chain transparency in standardization process;
• Exclude upstream reporting from the standardization priority areas;  

Reducing the Risks of Synthetic Content  

• Leverage existing industry tools to improve digital content transparency;
• Support technical research and policy approaches for limiting the ability to remove metadata or watermarks from digital content;  

Secure Software Development Practices  

• Continue risk-based approach that provides flexibility for application to varied use cases;
• Revise the recommendations on tracking and verifying data provenance;
• Revise the recommendation to revert to previous models to respond to AI risks; and
• Acknowledge that the varied roles of AI actors and different deployment contexts will affect how recommendations on reporting security issues are implemented.