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More than two-thirds of U.S. physicians have changed their mind about generative AI and now view it as beneficial to healthcare. But as AI grows more powerful and prevalent in medicine, apprehensions remain high among medical professionals.

For the last 18 months, I’ve examined the potential uses and misuses of generative AI in medicine; research that culminated in the new book ChatGPT, MD: How AI-Empowered Patients & Doctors Can Take Back Control of American Medicine. Over that time, I’ve seen the concerns of clinicians evolve—from worries about AI’s reliability and, consequently, patient safety to a new set of fears: Who will be held liable when something goes wrong?

From safety to suits: A new AI fear emerges

Technology experts have grown increasingly certain that next-gen AI technologies will prove vastly safer and more reliable for patients, especially under expert human oversight. As evidence, recall that Google’s first medical AI model, Med-PaLM, achieved a mere “passing score” (>60%) on the U.S. medical licensing exam in late 2022. Five months later, its successor, Med-PaLM 2, scored at an “expert” doctor level (85%).

Since then, numerous studies have shown that generative AI increasingly outperforms medical professionals in various tasks. These include diagnosis, treatment decisions, data analysis and even expressing empathy.

Despite these technological advancements, errors in medicine can and will occur, regardless of whether the expertise comes from human clinicians or advanced AI.

Fault lines: Navigating AI’s legal terrain

Legal experts anticipate that as AI tools become more integrated into healthcare, determining liability will come down to whether errors result from AI decisions, human oversight or a combination of both.

For instance, if doctors use a generative AI tool in their offices for diagnosing or treating a patient and something goes wrong, the physician would likely be held liable, especially if it’s deemed that clinical judgement should have overridden the AI’s recommendations.

But the scenarios get more complex when generative AI is used without direct physician oversight. As an example, who is liable when patients rely on generative AI’s medical advice without ever consulting a doctor? Or what if a clinician encourages a patient to use an at-home AI tool for help interpreting wearable device data, and the AI’s advice leads to a serious health issue?

In a working paper, legal scholars from the universities of Michigan, Penn State and Harvard explored these challenges, noting: “Demonstrating the cause of an injury is already often hard in the medical context, where outcomes are frequently probabilistic rather than deterministic. Adding in AI models that are often nonintuitive and sometimes inscrutable will likely make causation even more challenging to demonstrate.”

AI on trial: A legal prognosis from Stanford Law

To get a better handle on the legal risks posed to clinicians when using AI, I spoke with Michelle Mello, professor of law and health policy at Stanford University and lead author of “Understanding Liability Risk from Using Health Care Artificial Intelligence Tools.”

That paper, published earlier this year in the New England Journal of Medicine, is based on hundreds of software-related tort cases and offers insights into the murky waters of AI liability, including how the courts might handle AI-related malpractice cases.

However, Mello pointed out that direct case law on any type of AI model remains “very sparse.” And when it comes to liability implications of using generative AI, specifically, there’s no public record of such cases being litigated.

“At the end of the day, it has almost always been the case that the physician is on the hook when things go wrong in patient care,” she noted but also added, “As long as physicians are using this to inform a decision with other information and not acting like a robot, deciding purely based on the output, I suspect they’ll have a fairly strong defense against most of the claims that might relate to their use of GPTs.”

She emphasized that while AI tools can improve patient care by enhancing diagnostics and treatment options, providers must be vigilant about the liability these tools could introduce. To minimize risk, she recommends four steps.

1. Understand the limits of AI tools: AI should not be seen as a replacement for human judgment. Instead, it should be used as a supportive tool to enhance clinical decisions.
2. Negotiate terms of use: Mello urges healthcare professionals to negotiate terms of service with AI developers like Nvidia, OpenAI, Google and others. This includes pushing back on today’s “incredibly broad” and “irresponsible” disclaimers that deny any liability for medical harm.
3. Apply risk assessment tools: Mello’s team developed a framework that helps providers assess the liability risks associated with AI. It considers factors like the likelihood of errors, the potential severity of harm caused and whether human oversight can effectively mitigate these risks.
4. Stay informed and prepared: “Over time, as AI use penetrates more deeply into clinical practice, customs will start to change,” Mello noted. Clinicians need to stay informed as the legal landscape shifts.

The high cost of hesitation: AI and patient safety

While concerns about the use of generative AI in healthcare are understandable, it’s critical to weigh these fears against the existing flaws in medical practice.

Each year, misdiagnoses lead to 371,000 American deaths while another 424,000 patients suffer permanent disabilities. Meanwhile, more than 250,000 deaths occur due to avoidable medical errors in the United States. Half a million people die annually from poorly managed chronic diseases, leading to preventable heart attacks, strokes, cancers, kidney failures and amputations.

Our nation’s healthcare professionals don’t have the time in their daily practice to address the totality of patient needs. That’s because the demand for medical services is higher than ever at a time when health insurers—with their restrictive policies and bureaucratic requirements—make it harder than ever to provide excellent care. Generative AI can help.

But it is imperative for policymakers, legal experts and healthcare professionals to collaborate on a framework that promotes the safe and effective use of this technology. As part of their work, they’ll need to address concerns over liability. Ultimately, they must recognize that the risks of not using generative AI to improve care will far outweigh the dangers posed by the technology itself. Only then can our nation reduce the enormous human toll resulting from our current medical failures.