Picture this: A congressional hearing on “AI policy” makes the evening news. A senator gravely asks whether artificial intelligence might one day “wake up” and take over the world. Cameras flash. Headlines declare: “Lawmakers Confront the Coming Robot Threat.” Meanwhile, outside the Beltway on main streets across the country, everyday Americans worry about whether AI tools will replace them on factory floors, in call centers, or even in classrooms. Those bread-and-butter concerns—job displacement, worker retraining, and community instability—deserve placement at the top of the agenda for policymakers. Yet legislatures too often get distracted, following academic debates that may intrigue scholars but fail to address the challenges that most directly affect people’s lives.
That misalignment is no coincidence. Academic discourse does not merely fill journals; it actively shapes the policy agenda and popular conceptions of AI. Too many scholars dwell on speculative, even trivial, hypotheticals. They debate whether large language models should be treated as co-authors on scientific papers or whether AI could ever develop consciousness. These conversations filter into the media, morph into lawmaker talking points, and eventually dominate legislative hearings. The result is a political environment where sci-fi scenarios crowd out the issues most relevant to ordinary people—like how to safeguard workers, encourage innovation, and ensure fairness in critical industries. When lawmakers turn to scholars for guidance, they often encounter lofty speculation rather than clear-eyed analysis of how AI is already reshaping specific sectors.
The consequences are predictable. Legislatures either do nothing—paralyzed by the enormity of “AI” as a category—or they pass laws so broad as to be meaningless. A favorite move at the state level has been to declare, in effect, that “using AI to commit an illegal act is illegal.” Laws penalizing the use of AI to do already illegal things give the appearance of legislative activity but do little to further the public interest. That approach may win headlines and votes, but it hardly addresses the real disruption workers and businesses face.
Part of the problem is definitional. “AI” is treated as if it were a single, coherent entity, when in reality it encompasses a spectrum—from narrow, task-specific tools to general-purpose models used across industries. Lumping all of this under one heading creates confusion. Should the same rules apply to a start-up using machine learning to improve crop yields and to a tech giant rolling out a massive generative model? Should we regulate a medical imaging tool the same way we regulate a chatbot? The broader the category, the harder it becomes to write rules that are both effective and proportionate.
This definitional sprawl plays into the hands of entrenched players. Large, well-capitalized companies can afford to comply with sweeping “AI regulations” and even lobby to shape them in their favor. Smaller upstarts—who might otherwise deliver disruptive innovations—are less able to bear compliance costs. Overly broad laws risk cementing incumbents’ dominance while stifling competition and experimentation.
Academia’s misdirected focus amplifies these legislative errors. By devoting disproportionate attention to speculative harms, scholars leave a vacuum on the issues that lawmakers urgently need guidance on: workforce transitions, liability in high-risk contexts, and the uneven distribution of benefits across communities. In turn, legislators craft rules based on vibes and headlines rather than hard evidence. The cycle perpetuates popular misunderstandings about AI as a mystical, autonomous force rather than what it really is: advanced computation deployed in diverse and practical ways.
Breaking this cycle requires a shift in academic priorities. Law schools and policy institutes should be producing rigorous, sector-specific research that maps how AI is actually used in hiring, logistics, healthcare, and education. They should be equipping students—not just with critical theory about technology but with practical tools to analyze which harms are novel, which are familiar, and which are overstated. And they should reward faculty who bring that analysis into legislative conversations, even if it means fewer citations in traditional journals and more engagement with policymakers.
For legislators, the lesson is equally clear: resist the temptation to legislate against “AI” in the abstract. Instead, focus on use cases, industries, and contexts. Ask whether existing laws on consumer protection, labor, and competition already cover the concern. And when crafting new rules, ensure they are narrow enough to avoid sweeping in both the start-up and the superpower indiscriminately.
If academics can resist the pull of speculative debates, and if legislators can resist the urge to regulate AI as a monolith, we might finally bring policy into alignment with reality. The public deserves a debate focused less on worst-case scenarios and more on the practical realities of how today’s tools are already shaping daily life. That is where the real challenges—and the real opportunities—lie.
Kevin Frazier is an AI Innovation and Law Fellow at Texas Law and Author of the Appleseed AI substack.
A deep look at how "All in the Family" remains a striking mirror of American politics, class tensions, and cultural manipulation—proving its relevance decades later.
All in This American Family
There are a few shows that have aged as eerily well as All in the Family.
It’s not just that it’s still funny and has the feel not of a sit-com, but of unpretentious, working-class theatre. It’s that, decades later, it remains one of the clearest windows into the American psyche. Archie Bunker’s living room has been, as it were, a small stage on which the country has been working through the same contradictions, anxieties, and unresolved traumas that still shape our politics today. The manipulation of the working class, the pitting of neighbor against neighbor, the scapegoating of the vulnerable, the quiet cruelties baked into everyday life—all of it is still here with us. We like to reassure ourselves that we’ve progressed since the early 1970s, but watching the show now forces an unsettling recognition: The structural forces that shaped Archie’s world have barely budged. The same tactics of distraction and division deployed by elites back then are still deployed now, except more efficiently, more sleekly.
Archie himself is the perfect vessel for this continuity. He is bigoted, blustery, reactive, but he is also wounded, anxious, and constantly misled by forces above and beyond him. Norman Lear created Archie not as a monster to be hated (Lear’s genius was to make Archie lovable despite his loathsome stands), but as a man trapped by the political economy of his era: A union worker who feels his country slipping away, yet cannot see the hands that are actually moving it. His anger leaks sideways, onto immigrants, women, “hippies,” and anyone with less power than he has. The real villains—the wealthy, the connected, the manufacturers of grievance—remain safely and comfortably offscreen. That’s part of the show’s key insight: It reveals how elites thrive by making sure working people turn their frustrations against each other rather than upward.
Edith, often dismissed as naive or scatterbrained, functions as the show’s quiet moral center. Her compassion exposes the emotional void in Archie’s worldview and, in doing so, highlights the costs of the divisions that powerful interests cultivate. Meanwhile, Mike the “Meathead” represents a generation trying to break free from those divisions but often trapped in its own loud self-righteousness. Their clashes are not just family arguments but collisions between competing visions of America’s future. And those visions, tellingly, have yet to resolve themselves.
The political context of the show only sharpens its relevance. Premiering in 1971, All in the Family emerged during the Nixon years, when the “Silent Majority” strategy was weaponizing racial resentment, cultural panic, and working-class anxiety to cement power. Archie was a fictional embodiment of the very demographic Nixon sought to mobilize and manipulate. The show exposed, often bluntly, how economic insecurity was being rerouted into cultural hostility. Watching the show today, it’s impossible to miss how closely that logic mirrors the present, from right-wing media ecosystems to politicians who openly rely on stoking grievances rather than addressing root causes.
What makes the show unsettling today is that its satire feels less like a relic and more like a mirror. The demagogic impulses it spotlighted have simply found new platforms. The working-class anger it dramatized has been harvested by political operatives who, like their 1970s predecessors, depend on division to maintain power. The very cultural debates that fueled Archie’s tirades — about immigration, gender roles, race, and national identity—are still being used as tools to distract from wealth concentration and political manipulation.
If anything, the divisions are sharper now because the mechanisms of manipulation are more sophisticated, for much has been learned by The Machine. The same emotional raw material Lear mined for comedy is now algorithmically optimized for outrage. The same social fractures that played out around Archie’s kitchen table now play out on a scale he couldn’t have imagined. But the underlying dynamics haven’t changed at all.
That is why All in the Family feels so contemporary. The country Lear dissected never healed or meaningfully evolved: It simply changed wardrobe. The tensions, prejudices, and insecurities remain, not because individuals failed to grow but because the economic and political forces that thrive on division have only become more entrenched. Until we confront the political economy that kept Archie and Michael locked in an endless loop of circular bickering, the show will remain painfully relevant for another fifty years.
Ahmed Bouzid is the co-founder of The True Representation Movement.