Transforming Workforce Training Through Federal Leadership in XR Technology
Summary
Today’s unprecedented health and economic challenges demand a transformative approach to workforce training. Already, technology that immerses a person in a digital space (virtual reality) or that enhances reality with digital features (augmented reality) is making it possible to prepare workers faster and better for high-quality, high-demand jobs. Government investment in augmented and virtual reality (together known as “XR” technology) will supercharge workforce training, helping Americans across the country get into jobs that benefit them and our society.
The Federal Government should partner with industry to identify and implement “shovel-ready” applications of XR technology. Initial efforts should focus on demonstrating proof of concept by deploying XR technology towards two goals; namely:
- Work through the Department of Health and Human Services (HHS) to train 50,000 nurses over the next four years.
- Work through the Department of Labor (DOL) and Department of Energy (DOE) to train 50,000 solar-energy installers over the next four years.
These goals are readily achievable thanks to existing programmatic infrastructure at agencies with explicit workforce-development missions. Follow-on work could expand applications of XR technology to workforce training in other domains and/or through other agencies.
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.