{"database": "press", "table": "releases", "rows": [["https://mcbride.house.gov/media/press-releases/mcbride-introduces-bipartisan-read-ai-models-act-bring-more-transparency", "McBride Introduces Bipartisan \u201cREAD AI Models Act\u201d to Bring More Transparency to Artificial Intelligence", "2025-12-04", "2025", "2025-12", "Democrat", "House", "DE", "Sarah McBride", "M001238", "mcbride.house.gov", "mcbride", "https://mcbride.house.gov/media/press-releases", "scraper", "WASHINGTON, D.C. \u2014 Today, Delaware\u2019s Representative Sarah McBride (D-DE) and Representative Jay Obernolte (R-CA) introduced the Resources for Evaluating and Documenting AI (READ AI) Models Act, bipartisan legislation to put basic transparency at the center of how artificial intelligence is evaluated and deployed.\n\nRight now, most users of AI \u2014 from school districts to small businesses to local governments \u2014 have no consistent way to document how an AI model works, what data went into it, or how it was tested. Large tech companies often produce detailed documentation, but smaller teams may not have the staff or resources to do the same.\n\nThe READ AI Models Act compliments NIST\u2019s AI Risk Management Framework by creating a modular, easy-to-use \u201cnutrition label\u201d for AI models \u2014 helping developers, researchers, and government agencies consistently disclose the information needed to assess safety, performance, and risk of AI models. The bill also directs NIST to build an accompanying pilot tool and issue technical guidance to support implementation. All components would be built through a consensus-based process and adoption would be voluntary.\n\n\u201cArtificial intelligence is shaping everything from how hospitals manage data to how small businesses streamline tasks,\u201d said Rep. McBride. \u201cBut right now, only big tech companies have the manpower and capacity to steadily compile and release information about the AI models they build and deploy. Smaller teams \u2014 including government agencies, schools, and nonprofits \u2014 are left guessing and may lack the resources to accomplish the same.\n\n\u201cThe READ AI Models Act brings transparency to AI in a way that\u2019s simple, consistent and accessible. Think of it as a clear, easy-to-read snapshot \u2014 a \u2018nutrition label\u2019 for an AI model. It levels the playing field and helps people make informed decisions. That\u2019s what transparency is all about. This bill is voluntary, bipartisan, and grounded in NIST\u2019s world-class expertise.\u201d\n\n\u201cAs AI is deployed in every sector of our economy, it\u2019s essential that our sectoral regulators have the tools and information they need to oversee it effectively,\u201d said Rep. Obernolte. \u201cThe READ AI Models Act helps ensure agencies can understand and evaluate the models operating in their domains, strengthening our ability to manage risks while encouraging innovation. I\u2019m proud to support this important step toward responsible, sector-specific AI governance.\u201d\n\nThe bill is designed not for major tech companies \u2014 which already produce evaluation documentation \u2014 but for the many small teams now responsible for evaluating and deploying AI in their own workplaces. Across federal, state, and local governments \u2014 and in countless small businesses, school systems, and nonprofits \u2014 staff are being asked to wear multiple hats. Many are now tasked with overseeing procurement, IT, cybersecurity, and AI deployment all at once. This legislation will give those teams a practical, trusted resource for evaluating and comparing models. Delawareans applauded the bill\u2019s introduction.\n\n\u201cAs AI becomes more deeply embedded in how we work and live, we need clear, trustworthy information about the systems powering that change,\u201d said Delaware State Representative Krista Griffith, Chair of the Delaware AI Commission. \u201cThis legislation is a smart, practical step forward that complements the Delaware AI Commission\u2019s efforts to set strong, future-focused standards for this fast evolving technology.\u201d\n\n\u201cEstablishing clear, credible guidelines for how AI models are documented and evaluated is mission-critical for U.S. leadership in AI,\u201d said Sunita Chandrasekaran, Ph.D., Director, First State AI Institute. \u201cWith NIST\u2019s involvement, the READ AI Models Act is poised to set a trusted standard for both the public and private sectors\u2014ensuring developers can consistently disclose how models are trained, validated, and tested before deployment. Without these guidelines, we risk fragmentation and bias.\u201d\n\n\"As a member of Delaware's AI Commission, I strongly support Congresswoman McBride's READ AI Models Act,\u201d said Patrick Callahan, member of the Delaware AI Commission. \u201cIn working with organizations implementing AI, the biggest challenge is building trust through transparency. NIST's voluntary documentation framework addresses exactly this need, particularly for smaller organizations and public sector entities that lack the resources of major tech companies. Delaware is building a regulatory sandbox to enable safe AI innovation, and this federal framework would complement that work. The modular approach recognizes that a healthcare AI system needs different documentation than a financial services model. This is the kind of consensus-based policy that will accelerate responsible AI adoption nationwide.\u201d\n\nThe READ AI Models Act would:\n\nDirect NIST to develop a structured, consensus-based template for AI model evaluation documentation, similar to a \u201cnutrition label\u201d that developers can voluntarily use.\n\nRequire that the template be modular, allowing organizations to adopt only the sections relevant to their sector or use case.\n\nProduce technical guidance that incorporates voluntary standards, benchmarks, and industry best practices.\n\nLaunch a pilot tool to help users generate documentation easily and consistently.\n\nRequire NIST to seek public comment, collaborate with researchers, industry, and international standards bodies, and publish the final template and guidance publicly.\n\nMcBride serves on the House Science, Space, and Technology Committee and is a Member of the bipartisan Artificial Intelligence Caucus where she champions practical, trustworthy AI governance policy that strengthens innovation while protecting the public.\n\n###", 1, "2026-03-30T01:40:41Z", "2026-04-06T20:09:11Z"]], "columns": ["url", "title", "date", "year", "month", "party", "chamber", "state", "member_name", "bioguide_id", "domain", "scraper", "source", "date_source", "text", "has_text", "collected_at", "updated_at"], "primary_keys": ["url"], "primary_key_values": ["https://mcbride.house.gov/media/press-releases/mcbride-introduces-bipartisan-read-ai-models-act-bring-more-transparency"], "units": {}, "query_ms": 1.6266750171780586, "source": "dwillis/congress-press", "source_url": "https://github.com/dwillis/congress-press", "license": "MIT", "license_url": "https://github.com/dwillis/congress-press/blob/main/LICENSE"}