impacts. (4) Researchers from academia, Federal laboratories, and much of the private sector have limited access to many high-quality datasets, computing resources, or real-world testing environments to design and deploy safe and trustworthy artificial intelligence systems. (5) There is a lack of standards and benchmarking for artificial intelligence systems that academia and the public and private sectors can use to evaluate the performance of these systems before and after deployment. (6) Artificial intelligence is increasingly becoming a highly interdisciplinary field with expertise required from a diverse range of scientific and other scholarly disciplines that traditionally work independently and continue to face cultural and institutional barriers to large scale collaboration. (7) Current Federal investments and funding mechanisms are largely insufficient to incentivize and support the large-scale interdisciplinary and public-private collaborations that will be required to advance trustworthy artificial intelligence systems in the United States. (8) The United States education pipeline for artificial intelligence fields faces significant challenges. Not only does the artificial intelligence research field lack the gender and racial diversity of the American population as a whole, but it is failing to both retain researchers and adequately support educators to meet the demands of the next generation of students studying artificial intelligence. (9) In order to help drive forward advances in trustworthy artificial intelligence across all sectors and to the benefit of all Americans, the Federal Government must provide sufficient resources and use its convening power to facilitate the growth of artificial intelligence human capital, research, and innovation capacity in academia and other nonprofit research organizations, companies of all sizes and across all sectors, and within the Federal Government. 3. Definitions In this Act: (1) Advisory Committee The term Advisory Committee means the National Artificial