"in the future.” 
                                Satya Nadella, CEO, Microsoft

In the early hours of an April morning, a twenty-year-old threw a firebomb at the San Francisco home of OpenAI's chief executive Sam Altman, then made his way to the company's headquarters with a chair in hand and threats on his lips. Two more young men were arrested just days later for firing a gun near the same home. A month later, at commencement ceremonies across the country, members of the graduating Class of 2026 booed real estate executive Gloria Caulfield at the University of Central Florida the moment she described artificial intelligence as "the next industrial revolution." They also booed Eric Schmidt, the former chief executive of Google, repeatedly at the University of Arizona. Lastly, to further drive mistrust into AI, they jeered at a community college president in Arizona when an AI-enabled name-reading system mangled the names of graduating students, including some that were not read at all.
 

The boos are not random demonstrations of adolescent rebellion; they are the surface manifestation of something deeper that we in healthcare AI must take very seriously. According to the latest Axios Harris poll, 42% of Generation Z believed that AI will harm their job opportunities and wages- higher than every other cohort, including the baby boomers our industry usually worries about most. According to the 2025 Pew Research global survey of twenty-five countries, only thirty-seven percent of respondents worldwide trust the United States to regulate AI responsibly, against fifty-three percent for the European Union. In addition, the 2025 KPMG–University of Melbourne study of forty-seven countries found a clean and disturbing pattern: every country with a GDP per capita below roughly $36,000 expects AI to deliver more benefits than drawbacks, while the wealthy economies of the United States, Switzerland, the Netherlands, and Norway are the most skeptical. Singapore is the lone wealthy outlier in the direction of optimism, although China and India are very positive about AI as well. The poorer the country, the warmer the embrace; the richer the country, the colder the reception. And among the wealthy nations, the United States is the most frigid of all.

 
Why is America different? Three structural reasons are worth naming before we connect any of this to healthcare. The first is that the United States is the country where the AI is actually being built, and the visible billionaires building it have made their wealth grotesquely public during a period when ordinary Americans cannot afford a house, a starter job, or in many cases a single specialist copay. The bold promise Sam Altman has made of "universal basic compute," of a future in which work becomes optional and friction disappears, is being uttered in a country where Gen Z is entering what one observer called a "starter economy" without the starter jobs. The gap between the rhetoric of abundance and the reality of stagnation has become a wound, and AI is perceived by some as the dagger that has caused that injury. The second reason is that the United States is the country where AI capability is being deployed fastest into the labor market with hardly any guardrails: no European-style worker protections, no Japanese-style lifetime employment norms, no Nordic safety nets. When the technology arrives, it arrives uncushioned. The third reason, and the one that should worry healthcare most, is that the United States has been losing institutional trust across the board- in government, in media, in academia, and increasingly in healthcare itself.
 

This is the inheritance that healthcare AI is about to walk into. Worth pausing on one detail that I think matters more than it first appears: when Jensen Huang, the chief executive of Nvidia, spoke to engineering graduates at Carnegie Mellon and told them that AI would change every industry, he drew no audible pushback. The same week, the same kinds of statements drew boos at Arizona, at UCF, at Middle Tennessee. The difference was not what was said. The difference was who the audience believed had skin in the game alongside them. Engineering graduates at Carnegie Mellon were entering the field building the technology; the humanities and arts graduates at UCF were entering a field that AI is actively subsuming. Healthcare is going to splinter along precisely the same fault line.
 

Some thoughts for we clinicians who still believe AI is much more positive than negative. First, the rhetorical posture of inevitability has to die. Every time a healthcare leader echoes Altman's "this is the next industrial revolution, deal with it," they import into our hospitals the same contempt that is getting tech executives booed at graduation and firebombed at home. We are clinicians. We do not get to be contemptuous of the people whose trust we are asking for, and the way we talk about this technology in our keynotes and our journals is now part of the patient experience whether we want it to be or not. Second, transparency in clinical AI deployment is going to have to dramatically exceed what regulators require. Disclose every AI touchpoint in the patient journey, not just the FDA-cleared ones — the ambient scribes, the scheduling agents, the prior-auth bots, the triage models. Patients have earned the right to know, and the trust deficit means we no longer get the benefit of the doubt. Third, the indispensable human in the loop must be visible, not just present. Wisdom, as I have written before, is knowing what not to delegate. In a country where Gen Z is booing the very idea that AI will reshape their working lives, the visible presence of clinical judgment is no longer a courtesy but the consent mechanism that allows the technology to be deployed at all. So in short, kill rhetoric of inevitability, exceed regulatory transparency, and make the human in the loop visible
 

The good news, and there is good news, is that healthcare still enjoys higher institutional trust than tech, government, or media. We are walking into the trust crisis with a credit balance that other sectors do not have. The Mythos moment, the compute ceiling, and the trust deficit are three faces of the same Mercury-phase reality, and healthcare is in a position to grow up faster than the sectors that got us into this. The boos at graduation are not the end of AI. They are a warning that the public, especially the young public, is paying attention. We should be grateful for the warning.

•    The Mythos / compute ceiling / trust deficit triptych at the close is a deliberate hook to whichever piece runs next. If you are publishing these in sequence, this essay should run third — Mythos sets up the capability problem, compute sets up the supply problem, and trust closes the loop on the social problem. The "three faces of the same Mercury-phase reality" line ties the trilogy together.