Patient Autonomy in the Age of AI
Autonomous adults have always sought to conduct their own research to inform their health care decisions, independent of health care professionals’ advice. As mentioned in Part 1 of this series, AI-driven symptom checkers and chatbots are the next evolution of that impulse, helping patients triage, diagnose, and make preventive choices with increasing sophistication and empathy. This should come as no surprise. This is simply taking to the next level what patients have been doing for years—consulting “Dr. Google” to research their medical questions, and, in earlier times, such books as The Modern Home Physician. My mother consulted Baby and Child Care by Dr. Benjamin Spock when I was a child and adolescent in the 1950s and ‘60s.
However, AI empowers patients more than any previous source of medical information. It constantly updates with the latest clinical research on signs, symptoms, and treatments. Unlike books or “old-school” Google searches, AI can ask follow-up questions to clarify symptoms and guide reasoning—much like a human clinician. This frees patients from unnecessary dependence on the medical profession, allowing them to diagnose and manage many problems on their own—a fundamental expression of self-ownership. It also saves time and money by reducing the need for professional visits when patients don’t find them necessary.
Closing the Digital Divide, Without More Bureaucracy
As these technologies advance, some warn of a growing “digital divide”—the concern that people with limited internet access, outdated devices, or less digital literacy will be left behind. These are valid concerns, but they are too often used to justify more government control over how AI develops and who can use it. That would be a mistake.
The digital divide is real, but it’s closing quickly. Private competition has spurred significant gains in connectivity, affordability, and access. Low-cost smartphones, Starlink satellite internet, 5G expansion, and cloud-based AI services are reaching rural and low-income communities much faster than government broadband efforts ever did.
When policymakers frame access to digital tools as an equity issue that requires subsidies or federal oversight, they risk halting innovation at its current level. Once the government starts subsidizing certain technologies or establishing standards, entrepreneurs must design around bureaucratic definitions instead of focusing on consumer needs. Subsidies tend to benefit incumbents, and compliance rules can discourage newcomers. Bureaucracies are slow to adapt, but private markets can adapt quickly.
When Equity Becomes Paternalism
Health care equity is a commendable goal, but in practice, it’s often used to justify paternalism. Regulators claim that patients need “protection” from misinformation or misuse of AI. The Food and Drug Administration has already suggested that some health-related AI tools might require premarket review—treating them as medical devices rather than information resources. However, most of these tools don’t diagnose or treat; they simply help people interpret their own symptoms or lab results. By applying the same bureaucratic process required for a pacemaker or CT scanner, the FDA would stifle innovation and delay access. More importantly, it would deny individuals the freedom to seek and use medical information about their own bodies without government permission.
That kind of oversight may seem harmless, but it’s a recipe for slowing progress. AI systems that assist patients in interpreting their own health data should be viewed as information tools, not controlled technologies. Once regulators begin deciding which algorithms are safe enough for public use, innovation slows to the pace of government approval. Smaller developers—often the most innovative—may refrain from competing if every software update risks triggering a new review. The result isn’t safer patients; it’s fewer options, slower progress, and less freedom to choose how to manage one’s own health.
Voluntary Solutions Work Better
Equity doesn’t need another round of federal programs. The private sector and civil society are already better equipped to close access gaps. Philanthropic groups can provide free or low-cost AI health services. Developers can release open-source models that operate on inexpensive devices. Entrepreneurs can create simpler interfaces for older users. These voluntary efforts evolve rapidly and adapt to feedback—something government programs rarely do.
The Return of Centralized Control
When officials talk about “AI fairness” or “equitable access,” what they often mean is more centralized control. Once Washington starts deciding which algorithms are safe enough to use, innovation slows, costs rise, and smaller developers get pushed out. That’s how entrenched interests and regulators end up protecting each other instead of the public. We’ve seen this before. The FDA’s monopoly over drug and device approval—created to ensure safety—now routinely delays lifesaving treatments and raises prices. Extending that model to AI would repeat the same mistake: prioritizing bureaucratic comfort over patient empowerment.
Freedom, Responsibility, and Self-Ownership
Health information isn’t a controlled substance. People should be free to seek it from any source—human or digital—and decide for themselves how to use it. That freedom stems from self-ownership: the idea that individuals, not bureaucracies, have the ultimate authority over their own bodies and choices. That doesn’t mean guidance is not allowed. Independent rating systems, voluntary certifications, and professional societies can help people find trustworthy tools. Those safeguards should remain voluntary, not mandatory.
Freedom also entails responsibility. Patients who rely on AI for medical decisions must recognize its limitations and use their judgment. That’s not a flaw—it’s part of what it means to own one’s body and mind. The same principle supports the right to read, speak, and think without government permission.
A Libertarian Roadmap for AI in Personal Health Care
That principle should also guide policymakers. If the goal is to make AI both safe and accessible, the path forward isn’t about increasing regulation—it’s about increasing freedom. A truly equitable approach to digital health involves removing barriers that prevent innovators from building and patients from choosing.
The first step is to eliminate rules that treat informational AI as if it were a medical device, subject to premarket approval. Policymakers should promote voluntary certification and transparency instead of government licensing. They can also help bridge the digital divide by encouraging competition in broadband and telecommunications—primarily by removing obstacles and reducing local and federal barriers that hinder infrastructure development. Improving digital literacy is best achieved through private partnerships and education, not new federal initiatives. In short, the most effective way to make AI accessible to everyone is to allow freedom, not bureaucracy, to lead the way.
Equity Through Freedom
AI has the potential to make medical knowledge accessible to everyone. The real challenge is preventing “equity” from becoming a justification for more bureaucracy and control. True equity doesn’t come from regulation or redistribution—it comes from freedom. When individuals are free to choose and innovators are free to serve, technology narrows divides far more effectively than any government program ever could.
You can read Part 1 of this series here.