Automation Bias & Clinical Judgment: What’s a ‘Reasonable’ Mistake Now?

Recognizing the Risk in Real-World Scenarios

Automation bias has contributed to real and near-miss incidents in medicine. Consider these common patterns:

Missed Diagnoses

A clinician accepts an AI triage tool’s “non-urgent” flag, only for the patient to suffer a preventable emergency hours later. The clinician is later questioned for not reviewing the symptoms more critically.

Overtreatment

An AI misclassifies a benign finding as malignant, and the provider proceeds with an unnecessary and invasive procedure. The patient sues, and the AI vendor is not named in the suit—only the clinician.

Delayed Intervention

A patient’s condition deteriorates because the AI tool failed to identify subtle risk factors. The provider, having relied on the AI’s recommendation, didn’t intervene soon enough.

In each case, the failure wasn’t solely technical—it was behavioral. The provider deferred to the machine without exercising the judgment expected of a licensed professional.

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What Brokers Should Watch For

While brokers can’t control how clients use AI tools, they can play a key role in limiting exposure through smarter conversations and coverage guidance.

Here are three things brokers should do when advising clients:

1. Ask About Decision Protocols

Encourage clients to describe how AI is used in their clinical workflows. Are providers trained to double-check outputs? Is there a process for overriding AI when appropriate?

2. Review Documentation Practices

Suggest that providers document when and how AI tools were consulted, and what independent clinical reasoning led to the final decision. Clear documentation can be a strong defense.

3. Audit Policy Language

Work with underwriters to ensure malpractice policies explicitly cover AI-influenced decisions and do not contain ambiguous exclusions tied to “automation,” “software error,” or “mechanical devices.”

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Evolving the Standard of Care

The introduction of AI is also redefining what constitutes “reasonable” medical behavior. Courts may eventually view it as negligent to not use AI in certain scenarios—particularly if the technology has been proven to outperform traditional methods.

But that future hasn’t fully arrived. For now, the legal and insurance systems expect providers to:

• Know when to use AI
• Understand how to interpret its results
• Retain ultimate responsibility for patient outcomes

For brokers, that means helping clients balance innovation with caution, and ensuring that as they adopt new tools, they don’t unknowingly increase their exposure.

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Conclusion

Automation bias is not a software flaw—it’s a human tendency. And in the context of AI-assisted care, it’s quickly becoming a risk factor for malpractice.

Brokers who understand this behavioral liability can guide clients toward better documentation, more robust training, and smarter use of their insurance policies. As AI transforms healthcare, clinical judgment remains the deciding factor—and brokers have a role to play in making sure it’s never sidelined by convenience.