In the film WarGames, Matthew Broderick plays a prodigious computer hacker who taps into a military supercomputer. The machine quickly escapes the control of any of its human operators and autonomously initiates an international missile crisis.
When the film came out in 1983, it stirred fear in the hearts of many viewers, including then-President Regan, who signed one of the first presidential directives specifically addressing computer security later that same year.
Four decades later, John Chachas points out that the film represents our present inflection point in the development of artificial intelligence. We’ve already created machines that exceed human abilities. What happens when they evade human control?
As the CEO of Inyo Broadcast Holdings and founder of Methuselah Advisors, Chachas has seen firsthand how technological disruption can reshape, or outright dismantle, entire industries before policymakers even begin to respond. Now, he warns, artificial intelligence is poised to do the same thing to the American workforce, and at a speed that makes previous waves of disruption look gradual by comparison.
“I am quite worried about the inability of man to constrain technology,” Chachas says. “There will come a point when tech is not containable.”
The Jobs Question
The first place Chachas sees humans losing out to superior technology is with employment. The standard tech-industry narrative holds that artificial intelligence, like every major technological shift before it, will destroy some jobs but create more and better ones. Chachas isn’t buying it.
“Anyone arguing that AI is going to open a world of creative genius that presents more options for people—I don’t see that,” he says. “What does this mean for young people and their aspirations for work and progress? It means many fewer real jobs and many more ‘make-work’ jobs—which isn’t a very satisfying future.”
The distinction he draws between “real jobs” and “make-work jobs” is deliberate and pointed. In Chachas’s framework, a real job is one where a human being applies judgment, creativity, or expertise that cannot be replicated by a machine at a lower cost. A make-work job is one that exists because society hasn’t yet figured out what to do with the people displaced by automation. He sees the latter category growing, and he sees a political establishment that is largely ignoring the implications.
This is not, he is quick to note, a regressive argument. Chachas has spent his career facilitating corporate transformations. He advised E.W. Scripps Company on its $2.65 billion acquisition of ION Media and has guided companies through the kind of structural change that AI will accelerate. He understands the efficiency gains. He understands the competitive pressures. What he doesn’t understand is the absence of any serious policy conversation about what happens to the people on the other side of that transformation.
A Proposal for Universal Basic Income
Chachas’s proposed solution is both pragmatic and provocative. He argues for a corporate-funded Universal Basic Income trust, structured so that the companies that benefit most from AI-driven automation bear a proportional share of the social cost.
“If your corporation deploys AI that destroys human employment, you should automatically be liable for payment into a UBI trust fund,” he says.
The logic is straightforward: if corporations reap the productivity gains of replacing human workers with intelligent systems, they should be “compulsory funders” of a mechanism that supports the workers left behind.
It’s a proposal that cuts against the ideological grain of both major parties. Conservatives tend to resist anything that resembles a universal entitlement. Progressives tend to resist framing the solution around corporate liability rather than government redistribution. Chachas, a self-described Republican, still subscribes to a dwindling American ethos: country first, party second. This means adhering to the facts, even when they’re politically grating.
The math, as he sketches it, is daunting. Large-scale automation in white-collar sectors—legal research, financial analysis, content production, customer service, medical diagnostics—will displace millions of skilled workers over the next decade. Many of those workers will be in their thirties and forties, carrying mortgages and college debt, with children approaching college age themselves. They will not be easily retrained. They will not cheerfully pivot to the “creative economy.” And the social contract that promised them a middle-class life in exchange for education and hard work will feel, to them, like a lie.
Has anyone on the Hill started to talk about this concept of UBI and how we could fund it?” Chachas wonders. “If corporations want to reap all the profits that AI can produce, they will have to be compulsory funders of a UBI trust fund to pay for the millions of workers left out of the workforce.”
The Urgency Gap: Can Congress Act Before It’s Too Late
WarGames ends with the computer “learning” the meaning of a no-win situation. If the stakes of the game are mutually assured destruction, the only way to win is to not play. Would our current AI systems come to the same conclusion in a similar situation?
For Chachas, questions like this accentuate the gap between the speed of technological change and the speed of political response. AI capabilities are advancing on a timeline measured in months. Congressional deliberation, when it happens at all, operates on a timeline measured in years. The mismatch, he argues, is not merely unfortunate. It’s structurally dangerous.
He points to the history of other industries he has worked in. When digital platforms decimated local media—a subject he speaks about with particular authority given his broadcasting background—the policy response came too late to save most local newspapers.
The regulatory conversation around platform accountability and content licensing is only now gaining traction, years after the economic damage was done. Chachas sees AI employment displacement following the same pattern: by the time Congress acts, the displacement will already have occurred.
His prescription is characteristically direct. Start the conversation now. Commission serious economic modeling. Bring labor economists, technologists, and corporate leaders into the same room. Design a funding mechanism before the crisis hits, not after. “Maybe it’s time the leaders get ahead of this one,” he says, “instead of showing up after the damage is done.”
Whether Washington is capable of that kind of preemptive action is, of course, another question entirely. Chachas is realistic about the odds. But he is also a dealmaker who has spent a career in rooms where the impossible became merely difficult, then doable. He isn’t asking for a movie-magic happy ending. He’s asking for foresight, pragmatism, and proactive solutions.
