Skip to content
Search

Latest Stories

Top Stories

We’ve Been "Preparing" for the Future Since 1991—It Hasn't Worked

Opinion

An illustration of a person standing on a giant robotic hand.

As AI transforms the labor market, the U.S. faces a familiar challenge: preparing workers for new skills. A look at a 1991 Labor Department report reveals striking parallels.

Getty Images, Andriy Onufriyenko

“Today, the demands on business and workers are different. Firms must meet world-class standards, and so must workers. Employers seek adaptability and the ability to learn and work in teams.”

Sound familiar?


It’s the sort of guidance you’ll find on X, in studies issued by nonprofits, and, as I recently dug up, a report by the Department of Labor published in 1991. The familiarity is striking—and not accidental. Periods of economic transition tend to produce the same anxieties, framed in remarkably similar language.

The Labor Secretary spun up a commission to study “the demands of the workplace and whether young people were meeting those demands.” This was an important question at that moment for a couple of reasons. First, the economic prospects of the next generation of Americans did not look bright. Unemployment among young adults stood at 9.6 percent at the start of 1991; it climbed to north of ten percent within a few months.

Second, there was a concern that the economy was transforming at a faster rate than educational curriculums. “[M]ore than half of our young people leave school without the knowledge or foundation required to find and hold a good job,” observed the Secretary. Against that backdrop, the gap between schooling and work felt urgent rather than abstract. The Secretary’s Commission on Achieving Necessary Skills (SCANS) was thus formed and mandated to talk with educators, private sector stakeholders, and government officials to identify a path forward.

We find ourselves in a similar place today. Young adults have an 8.2 percent unemployment rate as of December of 2025. Pundits, researchers, and politicians fear our educational and vocational infrastructure is ill-suited for the labor market shifts being driven by AI. The technology may be new, but the underlying worry—that institutions are lagging behind economic reality—is not.

So far, our response seems to have been the same, too.

Then, there was a lot of talking, information gathering, and stakeholder engagement. These are all practical steps, in moderation, and they often feel like progress. “We have talked to [employers] in their stores, shops, government offices, and manufacturing facilities,” explained the Secretary. “Their message to us was the same across the country and in every kind of job: good jobs depend on people who can put knowledge to work.”

That groundwork was followed by something else that will also feel familiar to modern readers: a flood of broad statements about the skills Americans would need to thrive in a new technological era.

Take it from the Secretary:

New workers must be creative and responsible problem solvers and have the skills and attitudes on which employers can build. Traditional jobs are changing and new jobs are created everyday. High paying but unskilled jobs are disappearing. Employers and employees share the belief that all workplaces must ‘work smarter.’

From there, the conversation moved quickly from diagnosis to prescription—though not always with much specificity.

Then, there were a lot of generic policy recommendations.

The Secretary summarized the three takeaways from the SCANS report:

(1) “All American high school students must develop a new set of competencies and foundation skills if they are to enjoy a productive, full, and satisfying life.” This recommendation even called for equipping students with more “know-how.” Apparently, only one-half of young people had such “know-how.” Of course, a similar shortage of “know-how” is drawing headlines and shaping congressional debates today.

(2) “The qualities of high performance that today characterize our most competitive companies must become the standard for the vast majority of our companies, large and small, local and global.” Specifically, workers must become “comfortable with technology and complex systems, skilled as members of teams, and [passionate] for continuous learning.”

(3) “The nation’s schools must be transformed into high-performance organizations in their own right.” Notably, efforts at transformation were already underway but “a decade of reform efforts” had amounted to “little improvement.”

What there wasn’t a lot of was political prioritization and commitment—I’m talking a decades-long focus on “transforming the nation’s schools into high-performance organizations.” The Secretary's report did not lead to a sustained overhaul of the nation’s educational infrastructure. School as of 1991 looks more or less like school as of 2026. Ambition, it turns out, is easy to articulate and hard to finance, defend, and sustain. Transformation of just about anything—let alone something with as much resistance to change as our educational system—requires incredible amounts of political and financial resources to be expedited over several years.

That’s a lesson we must heed today. Just about every actor in our political system is incentivized to think on two-year time horizons (if that). These conditions are not conducive to initiating and sticking with transformational projects. Such changes are only possible if the public champions these efforts, providing political cover to those who are willing to incur short-term losses for long-term gains.

So, will we update our educational and vocational infrastructure for the Age of AI?

It depends. Specifically, it depends on whether we can collectively muster the focus and persistence that’s inherent to successful political projects—and whether we are willing to treat this challenge as more than another familiar talking point in a long line of reports that warned us, correctly, and were then quietly shelved.


Kevin Frazier is a Senior Fellow at the Abundance Institute, directs the AI Innovation and Law Program at the University of Texas School of Law, and is an Affiliated Research Fellow at the Cato Institute.


Read More

An illustration of a block with the words, "AI," on it, surrounded by slightly smaller caution signs.

Efficient AI may not mean less energy. The Jevons paradox shows why demand can grow, and why no one can say yet where AI’s real limits will be.

Getty Images, J Studios

The People Selling You the Future Don’t Know It Either

Artificial Intelligence is everywhere and can no longer be avoided. Will there ever be a ceiling for the expansion of this technology? AI companies are not just selling software. The story about the inevitability that AI will have in transforming work, education, medicine, art, government, and daily life is much more profitable. People must accept the transformation or be left behind. They are selling behind a mask of certainty.

The court of public opinion on AI has concluded that this technology is too energy-consuming for the benefits it allegedly brings and the ways many people use it. Therefore, companies have shifted their agendas to presenting efficiency as a solution to the technology’s enormous need for power. Smaller, better models and chips, and more efficient data centers may reduce the energy required for a single text-based request or generated image. If those improvements make AI cheaper to use, it will be invited into more daily life right?

Keep ReadingShow less
AI chip
a computer chip with the letter a on top of it
Photo by Igor Omilaev on Unsplash

We Should Regulate AI to Make It Grow Faster

The debate over artificial intelligence has become divided between two powerful ideas: that we need a “moratorium” to slow AI until we can make it safe, and that regulating AI will slow the innovation we need for our economy and national security. Both concerns are legitimate. But “moratorium” and “slowing AI growth” are divisive terms: they reassure those concerned about AI's safety, economic and environmental consequences while alarming those who see AI competition and national security as urgent priorities. We need a different starting point—meaningful regulation that provides the safeguards necessary to protect people, communities and the environment while creating the conditions for AI to continue growing. The experiences of Europe and China challenge the assumption that regulation must slow AI.

China has combined increasingly detailed, technology-specific AI regulation with substantial government support for AI development. Recent studies provide evidence that this approach can promote innovation. One 2026 study of Chinese companies from 2017 through 2023 found that the creation of national AI innovation and development pilot zones significantly increased corporate digital transformation, in part through increased research and development, human capital and reduced transition costs. Another 2026 study, covering Chinese manufacturing companies from 2014 through 2024, found that the same policy significantly promoted the adoption of intelligent technologies.

Keep ReadingShow less
person reading a computer screen
man using computer inside room

Student-Led AI Initiative Aims to Tackle Misinformation

PRINCETON JUNCTION, NJ — As generative artificial intelligence reshapes the digital landscape, a New Jersey student researcher is using the technology to combat media bias. Shaurya Jindal, an AI researcher and student at West Windsor-Plainsboro High School South, has launched Cogito News, an educational platform designed to build modern media literacy skills.

Cogito News was founded in response to growing concerns about partisan framing and selective sourcing in contemporary journalism. Recognizing that cognitive biases often influence how news is packaged and consumed, Jindal sought to build a tool that helps users critically evaluate the information they encounter daily. The platform's real-world impact and timely relevance were highlighted when Jindal was my guest on The Fulcrum Democracy Forum, an interview series dedicated to civic renewal and examining innovative approaches to strengthening democratic systems.

Keep ReadingShow less
An aerial view of a Flock camera

An aerial view of a Flock camera in Burbank, California. U.S. President Donald Trump expressed support for Flock cameras, saying he likes the AI-powered surveillance technology because of its use by law enforcement, despite concerns that it infringes on privacy.

(Photo by Justin Sullivan/Getty Images)

Flock Cameras Are Coming Down – but We Need More To Dismantle the Surveillance State

Chances are, you’ve seen one in your neighborhood. Flock cameras have become a major flashpoint for voters in the leadup to the midterms. The concept sounds straight out of 1984 — a network of government-owned cameras that track your movements — it’s no wonder that Americans across party lines are demanding their states and towns sever ties with the controversial company. Surveillance fears are only getting stronger as we enter the AI era.

But the problem isn’t just Flock. These cameras, Automated License Plate Readers or ALPRs to be exact, are a symptom of a larger “surveil first, ask questions later” attitude that has been adopted by local and federal government for decades. In recent years, the federal government has been dramatically expanding the nation’s surveillance infrastructure. This has taken many forms, from facial recognition technology at the airport, to law enforcement monitoring your mail, to the government watching what you’re posting on your personal social media pages. Since April, many Democrats and Republicans in Congress have united to stop what would effectively be a blank check for surveillance via FISA reauthorization, demanding surveillance reforms such as closing the “data broker loophole”, which allows the government to buy Americans’ personal data without a warrant.

Keep ReadingShow less