AI Is Forcing Us to Rethink Education, And It's About Time

Written By Shawn Collins

David Brooks published a provocative piece in the New York Times last month that should have every educator, policymaker, and parent paying attention. In "Are We Really Willing to Become Dumber?" he called AI in education a "malevolent seduction," a digital devil offering excellence without effort, threatening to turn an entire generation into intellectual zombies who can't think their way out of a paper bag, let alone write their way into one.

The evidence Brooks shared is genuinely unsettling. An MIT study tracked 54 participants writing essays under three conditions: with AI assistance, with search engines, or with nothing but their own gray matter. The AI users produced work that was fact-heavy but soulless, and here's the kicker: 83% couldn't even quote their own essays when asked. Brain scans revealed up to 55% lower neural connectivity among the AI-dependent writers, as if outsourcing cognition had literally rewired their minds for dependency.

Such findings should make us all nervous. But Brooks' prescription (essentially, ban the bots and shame the shortcuts) misses the forest for the trees. AI represents a symptom rather than the disease itself. Treating symptoms while ignoring the underlying pathology explains how we ended up with a $1.81 trillion student debt crisis in the first place.

The Education Industrial Complex We Built

Let's be honest about what we're defending here. American higher education has become a beautifully efficient machine for converting young people's dreams into institutional revenue streams. We've convinced an entire society that a college degree represents the only respectable path to prosperity, then rigged the game to make that path increasingly expensive and decreasingly valuable.

The numbers tell a story of systemic failure that predates any chatbot. As of today, 42.5 million Americans are drowning in student debt, carrying an average federal balance of $39,075. Delinquency rates for seriously overdue loans just hit 12.9%, the highest in 21 years. Nearly 10 million borrowers are teetering on default, and the demographics of distress reveal the ugly truth about who bears the cost of our educational mythology: older borrowers face 18% delinquency rates, Black borrowers carry disproportionate debt loads, and only 38% of all borrowers manage to stay current.

The pandemic pause offered temporary relief, but when payments resumed, the dam burst. Lower-income students, disproportionately students of color, saw their financial lives crater while university endowments swelled to record highs. This represents a wealth transfer mechanism disguised as social mobility, operating in plain sight for decades.

Meanwhile, the promised land keeps receding. Entry-level jobs for college graduates are down 15%. Graduate unemployment sits at 5.8-6%, higher than the national average. Nearly half of Gen Z questions whether their degrees have any practical value, a reasonable position when you consider that the fastest-growing careers often require skills that weren't taught when their curricula were designed.

This context becomes crucial when Brooks frames AI as education's primary threat. The house was already on fire; AI just made the smoke visible.

Cognitive Debt and the Thinking Crisis

Brooks' core argument deserves serious consideration, not dismissal. The MIT findings suggest that heavy AI reliance creates a kind of cognitive outsourcing that weakens our capacity for independent thought. When students produce essays they can't recall or defend, when their neural networks show measurably less connectivity, we're witnessing something genuinely alarming: the potential atrophy of human reasoning itself.

The anecdotes Brooks collected paint an equally troubling picture. Students admitting that AI handles "any type of writing in life," including personal communications. Professors reporting more fear of artificial intelligence than political interference. Academic integrity officers watching cheating rates triple since 2022, with one in five students now admitting to substantial AI assistance on assignments.

This transcends simple shortcuts or laziness. We're examining the fundamental relationship between effort and understanding, struggle and strength. Every educator knows that learning requires friction, that wrestling with difficult concepts, making mistakes, and working through confusion are essential elements of intellectual development. If AI eliminates that friction entirely, we risk creating a generation of surface-level thinkers who mistake information access for understanding.

The social media response to AI in education reflects this anxiety viscerally. On X, sentiment runs 46% negative and only 1% positive, with teachers and parents expressing fears that "kids won't learn anything anymore" and that "AI is turning brains to mush." The concern represents authentic recognition that something fundamental about human development might be at stake, rather than manufactured moral panic.

Here's where the analysis gets complicated: the very fragility Brooks exposes may reveal how artificial our "natural" learning environment already was. When students struggle to think without AI assistance, we might ask whether they were really thinking independently before, or simply following algorithmic pathways we called "education."

The Catalyst We Didn't Know We Needed

“AI reveals which parts of education were already dead and creates space for new approaches to emerge.”

What if, instead of viewing AI as education's destroyer, we saw it as the disruptor that finally forces us to confront decades of accumulated dysfunction? AI's rise coincides with and arguably accelerates a broader questioning of higher education's value proposition that was already underway.

The data suggests we're witnessing a fundamental shift in how people think about learning and careers. AI tools can accelerate skill development in exposed fields by up to 66%, making traditional four-year programs seem like expensive detours. Students are increasingly gravitating toward "skill stacks," combinations of targeted coursework, professional certifications, and hands-on experience that can be assembled without accumulating crippling debt.

Consider the revolution happening in personalized learning. AI adaptive systems can tailor educational experiences to individual students' needs, learning styles, and pace in ways that traditional classrooms never could. In rural districts where teacher shortages create chronic gaps, AI tutoring systems are providing high-quality instruction that would otherwise be impossible. One program I've been tracking helped students leap two grade levels in mathematics by complementing human instruction with round-the-clock personalized support.

The apprenticeship renaissance is equally telling. States are expanding programs that blend academic learning with practical application, creating pathways to middle-class careers that bypass the debt trap entirely. These programs extend far beyond blue-collar alternatives: tech companies, health care systems, and financial services firms are all embracing apprenticeship models that emphasize competency over credentials.

AI reveals which parts of education were already dead and creates space for new approaches to emerge.

Equity in the Age of Algorithms

The equity implications of AI in education cut both ways, and acknowledging this complexity is essential for crafting effective policy responses. AI tools can democratize access to high-quality educational resources. A student in rural Mississippi can access the same AI tutoring capabilities as someone in Manhattan, potentially leveling playing fields that have been tilted for generations.

But the digital divide remains stubbornly real. Students without reliable broadband, appropriate devices, or tech-literate support systems will fall further behind as AI becomes more central to educational success. There's also the bias problem: AI systems trained on datasets that reflect historical inequities can perpetuate and amplify those same biases in new contexts.

The solution involves ensuring equitable access to AI rather than banning it. This means treating broadband as essential infrastructure, funding device programs for low-income students, and training educators to recognize and counteract algorithmic bias. We need AI systems that are transparent about their limitations and curricula that teach students to be critical consumers of AI-generated content.

Most importantly, we must recognize that the equity crisis in education didn't start with AI and won't end by restricting it. The students being left behind by AI tools are often the same ones being failed by traditional educational approaches. Addressing the underlying inequities requires systemic change, not technological prohibition.

“We need policies that harness AI’s potential while mitigating its risks, that expand educational opportunity while maintaining intellectual rigor.”

Beyond Restriction: A Policy Framework for the AI Era

The path forward requires nuance, not knee-jerk reactions. We need policies that harness AI's potential while mitigating its risks, that expand educational opportunity while maintaining intellectual rigor.

This starts with reimagining assessment and credentialing. Instead of trying to AI-proof our existing testing systems, we should develop new forms of evaluation that emphasize process over product, creativity over conformity. Portfolio-based assessments, collaborative projects, and real-world problem-solving can showcase student capabilities in ways that traditional exams never could.

We need federal investment in AI literacy education that goes beyond basic digital skills to include critical thinking about algorithmic systems, data privacy, and the ethical implications of artificial intelligence. This preparation extends beyond AI-adjacent careers to encompass citizenship in an AI-integrated society.

The student debt crisis requires immediate policy attention that acknowledges AI's role in reshaping career pathways. This means expanding income-driven repayment options, increasing Pell Grant funding, and creating new financial aid models that support alternative credentialing pathways. We must also hold institutions accountable for employment outcomes and debt-to-income ratios among graduates.

For workforce development, we should embrace the apprenticeship model that AI makes more viable than ever. Combining traditional academic instruction with AI-enhanced skill development and real-world application can create career pathways that are both intellectually rigorous and economically practical.

The Future We're Actually Building

Brooks is right to worry about cognitive atrophy, but wrong to think restriction provides the answer. The students who will thrive in an AI-integrated world won't be those who avoid these tools, but those who learn to use them thoughtfully, who understand both their power and their limitations, who can collaborate with artificial intelligence without losing their own capacity for independent thought.

This requires a fundamental shift in how we think about education itself. Instead of treating it as a four-year rite of passage that ends with a degree, we need to embrace lifelong learning models that evolve with technological change. Instead of prioritizing memorization and recall, we should emphasize creativity, critical thinking, and the uniquely human skills that AI can't replicate.

The $1.81 trillion debt crisis won't solve itself, and neither will the equity gaps that AI threatens to widen. But restriction won't provide the solution; transformation will. We need educational policies that acknowledge the reality of technological change while preserving the essential human elements of learning and growth.

AI reveals how much of what we called "smart" was really just expensive memorization. The question becomes whether we're willing to become genuinely smarter rather than whether we're willing to become dumber. The answer will determine not just the future of education, but the kind of society we're building for the next generation.

The choice, as always, remains ours to make. But the window for making it wisely is closing fast.

Sources, Resources, and Suggested Reading:

Sources

Suggested Reading

Shawn Collins

Shawn Collins is one of the country’s foremost experts in cannabis policy. He is sought after to opine and consult on not just policy creation and development, but program implementation as well. He is widely recognized for his creative mind as well as his thoughtful and successful leadership of both startup and bureaucratic organizations. In addition to cannabis, he has a well-documented expertise in health care and complex financial matters as well.

Shawn was unanimously appointed as the inaugural Executive Director of the Massachusetts Cannabis Control Commission in 2017. In that role, he helped establish Massachusetts as a model for the implementation of safe, effective, and equitable cannabis policy, while simultaneously building out and overseeing the operations of the East Coast’s first adult-use marijuana regulatory agency.

Under Shawn’s leadership, Massachusetts’ adult-use Marijuana Retailers successfully opened in 2018 with a fully regulated supply chain unparalleled by their peers, complete with quality control testing and seed-to-sale tracking. Since then, the legal marketplace has grown at a rapid pace and generated more than $5 billion in revenue across more than 300 retail stores, including $1.56 billion in 2023 alone. He also oversaw the successful migration and integration of the Medical Use of Marijuana Program from the stewardship of the Department of Public Health to the Cannabis Control Commission in 2018. The program has since more than doubled in size and continues to support nearly 100,000 patients due to thoughtful programmatic and regulatory enhancements.

Shawn is an original founder of the Cannabis Regulators Association and also helped formalize networks that provide policymakers with unbiased information from the front lines of cannabis legalization, even as federal prohibition persists. At the height of the COVID-19 pandemic, Collins was recognized by Boston Magazine as one of Boston’s 100 most influential people for his work to shape the emerging cannabis industry in Massachusetts.

Before joining the Commission, Shawn served as Assistant Treasurer and Director of Policy and Legislative Affairs to Treasurer Deborah B. Goldberg and Chief of Staff and General Counsel to former Sen. Richard T. Moore (D-Uxbridge). He currently lives in Webster, Massachusetts with his growing family. Shawn is a graduate of Suffolk University and Suffolk University Law School, and is admitted to practice law in Massachusetts.

Shawn has since founded THC Group in order to leverage his experience on behalf of clients, and to do so with a personalized approach.

https://homegrown-group.com
Previous

Labor Day’s Rulebook for the Future
Next

The Beautiful Baby and the Faustian Bargain: Unpacking Trump's AI Action Plan