In 1929, optimism outpaced judgment. The exuberance of an unregulated market collapsed under its own weight, leaving investors frightened and society disillusioned. What restored faith in capitalism were not slogans about innovation but the patient construction of guardrails — the Securities and Exchange Commission, the FDIC, and disclosure laws that insisted confidence be earned, not assumed.
Regulation did not choke the market; it made the market believable again. Trust, once measured in lost fortunes, became the currency that rebuilt prosperity.
Nearly a century later, healthcare stands at a moment of speculation. The promise of artificial intelligence dazzles. Algorithms diagnose, predict, and document with astonishing speed, while nearly two-thirds of physicians already use some form of AI in their daily practice (American Medical Association, 2024). Yet, as the World Economic Forum (2025) notes, the moment when technology shows its potential is also when societies must decide whether to govern it or be governed by it. The lesson of the 1929 market crash still applies: innovation without accountability breeds collapse.
Rapid Innovation Without Trust
AI’s rise in healthcare has been breathtaking — and uneven. Hospitals adopt tools faster than oversight can mature. Vendors, pressed by investors, rush products to market. Meanwhile, regulators struggle to evaluate systems that can change themselves overnight. The Joint Commission’s recent guidance on AI safety calls for governance, privacy protection, continuous monitoring, and bias assessment—a prudent start within each organization—but the responsibility remains fragmented. Each hospital is left to build its own miniature regulatory apparatus, each vendor to certify its own creation. What results is not malice but entropy: a system too complex for any single actor to manage alone.
The consequences resemble those of the late 1920s, when banks and brokers worked independently without rules until their freedom became their weakness. AI now faces a similar paradox. Unbounded innovation invites uncertainty, and uncertainty erodes trust — the one element that healthcare cannot lose.
Public and Private, Together
The Healthcare AI Review and Transparency (HART) initiative offers a different path: a public–private partnership that turns guardrails into collaboration. Rather than add a new layer of bureaucracy, HART would connect what already exists — regulators, vendors, clinicians, and patients — in a single transparent network of evaluation and surveillance. Its goal is not to slow innovation but to steady it.
In practical terms, HART would evaluate AI tools for clinical reliability and bias before deployment, maintain a public registry of validated systems, and monitor real-world performance after release. This is what the WEF (2025) describes as the “collaborative governance model,” where accountability is distributed among those who build, deploy, and use AI. When vendors and clinicians share the same standards, innovation no longer feels risky; it feels credible. The very existence of guardrails becomes a form of trust.
Economically, this approach honors capitalism’s core strength — its ability to reward excellence through competition — while recognizing that competition requires rules to remain fair. Just as financial disclosure restored markets in the 1930s, transparent evaluation can provide confidence in healthcare AI today. Vendors gain credibility; hospitals reduce liability; patients benefit from tools whose safety is verified rather than assumed. Trust and profit no longer compete; they converge.
Human Oversight and Moral Continuity
Technology may transform practice, but it cannot inherit responsibility. That remains with the medical community. Clinicians bring to AI what no algorithm can learn — judgment, humility, and an instinct for human context. They are the living guardrails that ensure innovation serves patients rather than markets alone. For this reason, HART must be built around the medical profession, not beside it. The Joint Commission’s principles on AI governance — policy, monitoring, and education — belong at the heart of this national partnership. They translate ethics into practice and turn oversight into a shared virtue.
When a clinician opens a decision-support tool and knows it was independently evaluated for safety, trust is not a hope; it is an expectation. That is what patients deserve — not assurance from a press release but confidence built on collaboration. The HART model does more than align economics and ethics; it reconciles them, reminding us that markets and morality can prosper together when guardrails are strong and shared.
Building the Next Safety Net
Healthcare does not need more rules; it needs more responsibility — distributed, transparent, and trusted. A public–private partnership such as HART can achieve that balance, uniting the efficiency of markets with the moral clarity of medicine. We can protect patients without paralyzing innovation, and we can sustain innovation without abandoning safety. If we choose to build these guardrails together, the result will not be constraint but confidence — the same confidence that once saved capitalism and can now save healthcare AI.
Trust is what keeps healthcare moving forward.
References
American Medical Association. (2024, May 30). 2 in 3 physicians are using health AI — up 78% from 2023. American Medical Association. https://www.ama-assn.org/practice-management/digital-health/2-3-physicians-are-using-health-ai-78-2023
World Economic Forum. (2025). The future of AI-enabled health 2025. World Economic Forum. https://reports.weforum.org/docs/WEF_The_Future_of_AI_Enabled_Health_2025.pdf
Joint Commission & Coalition for Health AI. (2025). The responsible use of AI in healthcare (RUAIH): Guidance document. Joint Commission.
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