Creating a National DeepTech Capital Fund
Summary
The Biden-Harris Administration should establish a National DeepTech Capital Fund (NDTC Fund) to bridge capital gaps and enable more DeepTech entrepreneurs to bring promising and beneficial technologies to market.
Greater investment in DeepTech is critical in order to return the United States to the forefront of advanced science and technology research and development (R&D). “DeepTech” refers to companies and innovators building science-based, or R&D-based, products and services including hardware and advanced materials, robotics, manufacturing, and biotech. U.S. government investment in technology has declined by two-thirds in the past decades. Private capital typically eschews investment in advanced technologies, due to a combination of the additional expertise needed for and risks inherent to advanced-technology investment. Silicon Valley’s early days were cushioned by government risk capital at a time when the private sector could not see the value of investing in R&D. But relying entirely on Silicon Valley to drive investment in innovation has led the U.S. to a point where it risks being replaced by other innovation centers such as China. A National DeepTech Capital Fund would encourage and enable investment in companies building solutions to society’s greatest challenges, while ensuring that the United States remains at the center of global innovation.
AI’s high-stakes outputs directly shape American economic, industrial, and technological outcomes. They must not be accepted entirely on the basis of institutional faith rather than verifiable evidence.
The clearinghouse will also neutrally mediate the assignment of auditors to audits—strengthening independence, trust, and ethical governance across the AI ecosystem.
Soft law was never meant to be a permanent solution. Treating it as one, and letting the sandcastle stand in for the skyscraper indefinitely, is how we end up with a decade of voluntary commitments and no enforceable accountability to show for it.
Jobseekers, employees at smaller organizations, and local public workers need more than a weekend crash course in AI. They need practice choosing useful tasks, protecting data, testing outputs, and explaining where human judgment remains necessary.