To sustain America’s leadership in AI innovation, accelerate adoption across the economy, and guarantee that AI systems remain secure and trustworthy, we offer a set of policy recommendations.
Current scientific understanding shows that so-called “anonymization” methods that have been widely used in the past are inadequate for protecting privacy in the era of big data and artificial intelligence.
To fully harness the benefits of AI, the public must have confidence that these systems are deployed responsibly and enhance their lives and livelihoods.
The first Trump Administration’s E.O. 13859 commitment laid the foundation for increasing government accountability in AI use; this should continue
As new waves of AI technologies continue to enter the public sector, touching a breadth of services critical to the welfare of the American people, this center of excellence will help maintain high standards for responsible public sector AI for decades to come.
By creating a reliable, user-friendly framework for surfacing provenance, NIST would empower readers to better discern the trustworthiness of the text they encounter, thereby helping to counteract the risks posed by deceptive AI-generated content.
While healthcare institutions are embracing decarbonization and waste reduction plans, they cannot do this effectively without addressing the enormous impact of single-use devices.
The United States has multiple policy tools that could be used to prevent U.S. reliance on Chinese made semiconductors.
We can address the issue of international semiconductor competition along three major axes: increasing production outside of China, containing an oversupply of Chinese semiconductors, and mitigating the risks of remaining Chinese chips in the U.S. market.
In an industry with such high fixed costs, the Chinese state’s subsidization gives such firms a great advantage and imperils U.S. competitiveness and national security. To curtail Chinese legacy chip dominance, the United States should weaponize its monopoly on electronic design automation software.
The technical advances fueled by leading-edge nodes are vital to our long-term competitiveness, but they too rely on legacy devices.
To tackle AI risks in grant spending, grant-making agencies should adopt trustworthy AI practices in their grant competitions and start enforcing them against reckless grantees.