Not so fast: Quick-moving AI leaves accountability behind in the dust

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Not so fast: Quick-moving AI leaves accountability behind in the dust

Artificial intelligence is often framed as a problem of bias, safety or trust. From inside medical practice, I see something else — the real problem is timing.

I’m a practicing physician, and like most clinicians I know, I don’t fear artificial intelligence. We welcome intelligence. Medicine has always depended on better information, sharper pattern recognition, and tools that help clinicians see more clearly.

What feels different now is not the technology itself — it’s how quickly decisions turn into actions.

Medicine has always lived with uncertainty. Before a decision happens, uncertainty is expected. Doctors weigh incomplete information, assess risk, pause, and decide. That uncertainty is shared and understood as part of the job.

Once an action happens, uncertainty changes.

After a medication is given, a test ordered, or a decision carried out, uncertainty becomes responsibility. It becomes explanation. It becomes accountability. When harm occurs, it lands on patients and on the clinicians and institutions expected to answer for it, regardless of how careful the decision was.

Artificial intelligence did not introduce irreversibility into medicine. Medicine has always had to live with irreversible decisions. What AI changes is speed.

As automated systems move from offering advice to carrying out actions, the time between judgment and consequence collapses. Orders fire instantly. Authorizations trigger automatically. Decisions propagate across systems faster than humans can meaningfully pause, reassess or intervene. The moment something takes effect becomes the moment that matters most.

Nothing broke. But something was never finished.

We have built systems that can act efficiently. What we have not consistently built are the conditions that allow those actions to be legitimately owned at the moment they occur. When questions arise later, audits are performed and explanations offered. But responsibility does not disappear. It concentrates.

Clinicians already operate under time pressure, with incomplete information and competing demands. When automated systems act without clear legitimacy at the moment of execution — whether because consent has expired, authority conflicts or circumstances have changed — the burden of explanation and defense falls on those closest to patients.

Health care brings this problem to the surface early because it is a field where responsibility is shared. Decisions involve clinicians, patients, families, hospitals, insurers and regulators. Accountability settles downstream, long after an action has already taken effect. Clarity after the fact may explain what happened, but it does not relieve the attached responsibility once something irreversible occurs.

This is not an argument against artificial intelligence. AI can improve care, reduce errors and support clinicians in meaningful ways. It is also not a call for sweeping regulation or new laws. It is a warning about misalignment.

As technology accelerates action, responsibility cannot be reconstructed later. It has to exist at the moment a decision takes effect. When execution outruns legitimate ownership of decisions, speed becomes a liability. Public systems feel the consequences first, but they do not absorb them alone.

Medicine did not fail. We simply never finished the transaction between decision and responsibility.

Holland Haynie, MD, is a family medicine physician and chief medical officer at Central Ozarks Medical Center in Osage Beach, Mo.

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