Senate AI Workgroup Calls for $32 Billion for AI Research in New AI Policy Framework

Senate Majority Leader Chuck Schumer and the bi-partisan Senate artificial intelligence working group released a legislative framework for artificial intelligence policy on May 15. The plan called for $32 billion in annual spending to stimulate AI research and innovation and a stand-alone federal data privacy law focused on AI.

The $32 billion in annual non-defense AI spending aligns with recommendations made by the National Security Commission on Artificial Intelligence (NSCAI) report published in 2021.

The four-person Senate working group, consisting of Schumer, fellow Democratic senator Martin Heinrich, and Republicans Mike Rounds and Todd Young, endorsed several areas of focus to target while increasing current funding to match NSCAI recommended levels by 2026. Those areas include:

• Cross-government focus on AI research and development of “AI ready data initiative,” including foundational trustworthy AI topics, such as transparency, explainability, privacy, interoperability and security
• Fully fund the CHIPS and Science Act accounts related to AI
• Passing the Create AI Act (S. 4236) to authorize the National AI Research Resource (NAIRR)
• Passing the Future of AI Innovation Act (S. 4178) and the AI Grand Challenges Act (S. 4236) to fund a series of “AI Grand Challenges” to promote AI innovation
• Funding an AI evaluation infrastructure at the National Institute of Standards and Technology (NIST) and supporting the creation of a NIST testbed to test and synthesize innovation AI tools
• Supporting research and development for the intersection of AI and critical infrastructure (like healthcare)
• Funding AI work through Federally Funded Research and Development Centers (FFRDCs)
• Develop legislation related to training, retraining and upskilling the private sector workforce to successfully participate in an AI-enabled economy

Specific to healthcare, the working group recommended passing legislation to:

• Support deployment of AI in healthcare
• Implement guardrails and safety measures to protect patients, including consumer protection, preventing fraud and abuse and promoting the usage of accurate and representative data
• Support NIH development and improvement of AI, particularly data governance
• Ensure that the Food and Drug Administration (FDA) and the Office of the National Coordinator for Health Information Technology (ONC). can create a predictable regulatory structure for AI-enabled tools
• Provide transparency for providers and the public about the use of AI in medical products and clinical support services, including the data used to train the AI models
• Promote innovation of AI systems, potentially through Centers for Medicare and Medicaid Services (CMS) reimbursement that meaningfully improve health outcomes and efficiencies

In addition to exploring the creation of a national data privacy law, the working group recommended that the Congressional committees of jurisdiction should consider if additional standards or clarity around existing standards are needed to hold AI developers and users accountable if AI tools cause hard to consumers.