A Majority of Tennesseans Want AI in Healthcare With Guardrails, Not Bans

By Niklas Kleinworth

Calls for regulating artificial intelligence (AI) have reached a fever pitch, with skeptics, the public, and even the industry itself asking for new government restrictions. We are surrounded by assertions of how AI could be abused—and how government limits would mitigate these challenges. 

But the reality is that new regulations often provide a false sense of security. In healthcare, these limits merely create roadblocks for good actors and harm patients by threatening future cures and eliminating efficiencies for care.

To address concerns and deliver accountability without stifling innovation, policymakers should focus on clarifying how AI fits into existing law. The law should designate who is accountable for the use of the technology for patient care and who is liable when something goes awry.

The clarity approach balances AI use with human accountability in several ways. First, it places accountability for medical decisions on human beings, be it the provider who makes the final call, or the technology vendor offering a decision-support tool. Second, it encourages markets to police the industry, not regulators. Finally, this approach is more legally durable, allowing AI’s innovators to pursue efficiencies and cures that today’s policymakers cannot fathom while still fitting within the current legal context.

Consider recent legislation from North Carolina, where policymakers sought to address upcoding—a practice where medical bills are submitted for more costly services than those actually rendered. The bill would have banned using AI to upcode and would require additional attestation documentation to certify the charges. Not only is this policy difficult to police meaningfully, but it creates inefficiencies that undercut AI’s ability to reduce administrative burdens. 

Since billing for services not delivered is already fraud under current law, a better approach would be to clarify that liability falls on the hospital or clinic submitting the inaccurate bill, whether or not AI was involved. This addresses upcoding and puts the onus on the AI industry to develop higher quality and more reliable products.

Tennesseans have already experienced how selective guardrails and onerous red tape hinder the healthcare system’s ability to meet residents’ needs. Certificate-of-need (CON) laws are an example where the industry lobbies for its own regulation. CON laws create government-imposed market shortages that raise costs, reduce access, and diminish quality for patients. After decades and incremental reforms, Tennessee recently started to roll back CON restrictions.

With this experience in mind, policymakers must be skeptical of the AI industry’s biggest players calling for the government to regulate them. Arbitrary pauses and limits erect barriers to entry in the AI market that will all but guarantee control by just a few large companies—limiting the competition needed for meaningful market accountability.

A majority of Tennesseans want AI in healthcare, with clear accountability, not bans and arbitrary restrictions. For a balanced, durable approach to AI policy in healthcare, policymakers must clarify who is accountable under existing law, giving voters the limits they want without closing the door to healthcare innovation. This technology offers real promise for more affordable and accessible healthcare. Providing clarity in accountability can create a smoother path forward.