CDT Comment Welcomes NIST Effort to Develop Zero Draft
The Center for Democracy & Technology (CDT) submitted comments to the National Institute of Standards and Technology (NIST) on its Guidance and Templates for Public-Facing AI Documentation: An AI Standards ‘Zero Draft.’ The draft provides guidance for documenting AI datasets and models, with the goal of informing the development of voluntary standards for AI development and deployment.
Drawing on CDT’s previous comments on this NIST effort and our prior research on documentation, our submission welcomes NIST’s effort to develop the zero draft, which provides a much-needed step toward more standardized, high-quality guidance on how developers of AI system components should document key properties and potential sources of AI risk. This guidance will be a valuable resource for organizations to improve interoperability, build more performant AI products, and more effectively identify and mitigate AI risks.
Our comments also recommend that NIST prioritize expanding its guidance to system-level documentation, which is beyond the scope of the current draft. System-level components, such as user interfaces, connected tools, and content filtering mechanisms, present some of the most important factors for consumers of documentation to understand when determining how to effectively and responsibly integrate AI products into broader systems. We look forward to future work by NIST that provides guidance on system documentation. Our comments also suggest other ways that NIST can continue to improve the guidance, including through greater emphasis on interoperability, availability, known limitations of models and datasets, and organizational incentives to improve documentation.
Coalition Urges Senate Not to Let Companies Waive Financial Regulations for AI
CDT joined AI Now Institute, American Civil Liberties Union, and several organizations dedicated to tech policy, consumer protection, and civil rights in a letter to Senate leadership and the Senate Banking, Housing, and Urban Affairs Committee opposing the “AI Innovation Labs” language in Sec. 10509 of the CLARITY Act.
As concern about risks and harms related to AI systems continue to grow, a growing chorus of policymakers, industry leaders, and advocates have called for independent AI assessments. This explainer provides an overview of recent proposals for third-party assessment in the United States, including state and federal legislation, executive actions, and industry proposals.
Having third parties assess AI systems might seem like common sense, but crafting effective policies toward this goal can be devilishly tricky. A poorly-constructed ecosystem for third-party assessment could easily fail to consider the most consequential mechanisms of risk, neglect the AI harms that most impact people, or do more to protect AI companies than people.
Not All Guardrails Are Created Equal: Comparing Content Safety and Copyright Filtering
As courts and policymakers work through questions about chatbot liability, they should be wary of analogies that flatten meaningful technical differences. Copyright filtering and safety intervention share real challenges around ambiguity and evasion, but they diverge in what each control must assess, how each manifests over the course of a conversation, and how much can be verified from the outside.
