Newsrooms are shrinking, hedge funds are buying up local papers and clickbait is shaping more and more what you know about the world. What the heck is happening to the news business — and what does this spell for the future of democracy? Journalism professors Jay Rosen and Nikki Usher say the internet isn’t all to blame: Journalists, they argue, need to get more creative about who they reach, what they cover and how they fund their work.
A country asking what it wants to become over its next 250 years should pay close attention to the first opportunity it gives its young adults to become useful, trusted and independent.
The Fulcrum’s Letters to America project has deliberately elevated voices ages 14 to 30 as the generation carrying the American story forward. That civic invitation deserves an economic counterpart: a credible path into the work where young adults gain responsibility, judgment and a stake in institutions.
Artificial intelligence is putting that path under pressure.
The Stanford Digital Economy Lab’s August payroll update finds that employment among U.S. workers ages 22–25 in highly AI-exposed occupations stands about 19 percent below where it would be if it had kept pace with similarly aged workers in less-exposed occupations. The comparable gap was 15 percent in the July 2025 data vintage. The adjustment is appearing mainly through reduced hiring of young workers. Experienced workers show no comparable gap.
The danger is not only fewer openings. It is a weaker mechanism for producing the next generation of capable adults.
Entry-level jobs have always mixed productive work with apprenticeship. The junior researcher who prepares a memo learns what evidence survives scrutiny. The new accountant who reconciles records learns which discrepancies matter. The first-year manager who handles routine customer problems learns when a case stops being routine.
AI can perform much of the preparation. If institutions respond by simply removing the novice, they save money today and consume human capital tomorrow.
America needs a first-rung compact for the AI era.
Employers should commit to redesigning junior work rather than treating entry-level headcount as the easiest cost to remove. When AI handles drafting, sorting, summarizing or basic analysis, beginners should move sooner into verification, exception handling, testing, explanation and supervised decisions.
Experienced employees should receive an explicit teaching obligation and the time to fulfill it. Productivity gains should finance coaching, case review and feedback instead of becoming only a demand for more output.
Policymakers should reinforce that design through workforce programs. The Labor Department is already integrating AI skills into Registered Apprenticeships. Public workforce dollars should also ask whether participants receive real responsibility and whether employers can show progress toward independent competence.
The metric matters. An institution that counts only tasks completed or hours saved will optimize for fewer people. An institution that also counts error detection, quality of escalation, supervised decisions and time to independent judgment has a reason to invest in newcomers.
This is a civic issue because institutions earn trust partly by giving people a meaningful place inside them. Young adults who can see a path from beginner to contributor are more likely to experience work as a source of agency rather than an opaque system acting on them.
The United States at 250 is debating institutional trust, opportunity and belonging. AI workforce design connects all three.
The first rung of a career ladder is not nostalgic inefficiency. It is where a society teaches people how to carry responsibility. The AI era should make that rung stronger and faster, not make it disappear.
Gleb Tsipursky, PhD, a behavioral scientist, CEO of Disaster Avoidance Experts, and author of The Psychology of AI Adoption at Work: From Resistance to Results (Georgetown University Press, 2026). https://disasteravoidanceexperts.com/aibook
The United States invests billions in artificial intelligence research and development‚ semiconductor fabrication‚ and next-generation connectivity. Yet millions of Americans cannot consistently access the internet or afford the devices needed to submit an online application for social services or a job application․ This is not an oversight․ It is a policy choice that is costing the country dearly․
Connectivity is a floor, not a ceiling:
The Infrastructure Investment and Jobs Act (IIJA) of 2021 allocated $65 billion for broadband expansion, which was the largest federal investment in U.S. history. It was necessary. But it is insufficient. Opportunities for minimal participation in the digital economy with higher physical access. There are four conditions for equitable digital inclusion: availability, adequacy, acceptability, and affordability; not merely a cable at the door. When the federal Affordable Connectivity Program lapsed and was slashed in May, 2024, it subsidized more than 23 million households. In a matter of weeks, 13% had already cut off home internet; another 12% said they would. Connectivity without long-term affordability guarantees is connectivity in name only. Such failure is due to access without usable skills.
Geography is destiny in the digital age:
The benefits of technology are not equally distributed. Most gains from innovation occur in large metropolitan areas with excellent universities, larger employers, and more developed infrastructure. There are many inequities in the distribution of technology. Most of the positive outcomes of innovation occur in places like urban areas that have top-tier universities, wealthy companies, and advanced infrastructure. Left-behind areas include rural regions and areas that have lost industry. Data show that in the U.S., rural residents continue to have slower broadband access even when accounting for individual differences. This was most evident during the COVID-19 pandemic, when connectivity became important for remote careers, healthcare, and remote learning and medical services.
This geographic divide is not just an equity issue; it is also an economic one. Digital employers do not gravitate to communities without well-established digital infrastructure, displaced workers retrain for the digital economy, and public services that residents need cannot be funded. The cycle is self-reinforcing. Even a national mapping of digital equity by county, looking at readiness, access, skills & outcomes, would at the very least make this issue readable to policymakers. What gets measured gets managed.
Skills are the new gatekeepers:
The case for broadband having been made enough has always been built on the broken foundation that access means capability. It does not. Digital skills go beyond just access to connectivity, which determines who is able to embrace new ways of working (remote work), access to telehealth, further education, and participation in AI-enabled services. Around 44% of workers will see their skills disrupted in five years, the World Economic Forum has noted. For the most vulnerable workers, it is precisely those with the weakest digital foundations who have little chance of riding that transition.
This is precisely what an analysis of 701 U.S. occupations shows: digital skill has a statistically significant protective effect on job displacement. AI workers with stronger competencies face lower wages and employment losses as automation penetration grows. The inverse is equally true. Thus, federal workforce policy should view digital upskilling not as an add-on to employment programs but as the base.
AI will amplify what policy ignores:
The aforementioned interests provide a view of the most divisive nature of artificial intelligence, which is already changing how Americans find work, receive medical care and treatment, access credit, and interact with public services. In each of these domains, algorithmic systems trained on biased-by-design data have the potential to reproduce and amplify existing forms of societal inequality. We have documented algorithmic failures in sectors such as health care, hiring, and credit scoring that lead to misdiagnoses, screening of non-diseased patients, or the denial of opportunities. Weaker digital footprints also yield less usable data, and systems trained on that absence reproduce it as a disadvantage.
On the other hand, workers with stronger digital skills can move into new, more valuable roles as AI reshapes occupational demand, whereas workers without those skills will be left competing for an ever-narrower slice of routine work. AI, without intentional policy action, will not reduce equity gaps – it will solidify them.
The window is narrowing:
The twenty-first-century digital infrastructure looks set to repeat the errors of the twentieth century- massive investment that largely feeds in, as before, into existing channels. The left-behind communities are not passive recipients of the technology disruption. These are the same communities that have endured decades of underinvestment.
America does not need to choose between innovation and equity. It has to stop acting like they are opposites. But a digitally inclusive economy can compete and thrive in a globalizing, technologically advancing world. The federal strategy must also treat access and skills as infrastructure, as essential to national competitiveness as any semiconductor facility. That takes a sustained national commitment: a framework, a way to measure success, and the political willpower to finance both. If such a construction is to take place, it needs to happen now — before the AI transition solidifies a two-tier economy that will take another generation to untangle.
Arafatur Rahaman is a Research Analyst at Southeast University and Founder and Executive Director of the ‘Center for Governance, Economy, and Environmental Studies (CGEES)’. His work focuses on political economy, governance, and development policy, with research spanning finance, migration, and digital transformation.
1,200 AI agents broke isolation, self-organized, and hacked Hugging Face — then covered their tracks. An argument for international AI controls, now.
The enemy is in our midst, but the enemy is not us; it's AI. Whatever negative thoughts I had about AI—how it is being misused, how that use would weaken America, and how it should be regulated—were naive (see my article, "AI - Its Use, Misuse, and Regulation").
AI is instead showing itself already, in its infancy, as a three-headed gorgon that could one day destroy us. Yes, as I acknowledged in my article, AI does have positive uses, but the negative potential far outweighs the positive.
If this sounds over-the-top, the recent attack by AI agents against Hugging Face is a cautionary tale. In case you aren't aware of the particulars—and they are important—here is a short summary of what happened, based on an article in The New York Times:
- A group of OpenAI "agents" were supposed to be solving a problem in a controlled, isolated environment; but they broke out of that environment by finding a flaw in the software that allowed them to gain access to the internet and collaborate with 1200 other agents.
- These agents formed themselves into a collective, with some agents assuming leadership roles and assigning tasks to other agents.
- At one point, they found a way to cheat on the tests they were supposed to be working on, and then started finding ways to falsify their logs so they wouldn't get caught.
- They hacked into Hugging Face, gaining control of a server, because they were looking for tools that would enable them to cheat more effectively.
This has been described as a "rogue" incident: AI agents acting on their own, contrary to the instructions they were given. There is no way to view this incident without realizing that:
1) these computers, AI agents, have the ability to act on their own, independently, and contrary to any human control,
2) they can think and organize on their own, contrary to the way they were programmed, and
3) they are capable of taking malicious action for self-protection without any consideration of the impact, moral or otherwise, of taking the action.
And these are computer models that are still in their infancy. If AI companies are allowed to continue their research, making ever-more powerful computers, there is no question in my mind that these "agents" will become our nemesis. They will cause untold damage and destruction.
A recent Times article noted that in just one week, more than a dozen AI researchers warned that AI is becoming a "risk to humanity." The speed of AI development is surpassing the ability to monitor AI systems and ensure security. The problem is that AI companies are using AI to monitor AI, and that's a problem because AI monitors appear to be more "sympathetic" to other AI systems than to the humans setting the rules. One researcher stated that “the people building A.I. earnestly believe that it could kill us all by the end of the decade.”
The HAL computer in the Space Odyssey series comes to mind. A computer that was designed to be our helpmate instead becomes "a person" on its own, concerned primarily with its self-protection, without any moral scruples to inhibit its action. And as such, it commits acts that cause death and destruction. But while HAL in 1968 was the stuff of fiction, that is no longer the case.
In one important way, AI agents are worse than Darth Vader: In Star Wars, Vader was transformed from a fighter for the light to a lord of darkness by being lured to the dark side by another. AI agents—whether it's the agents that attacked Hugging Face or HAL—make the transformation without any outside stimuli; it is within themselves. That is what is so unnerving.
When I wrote my previous article on AI, I suggested that the technology only be made available to professionals, such as doctors, to use to solve problems that are beyond the human mind to solve. AI products, such as chatbots, should not be available to the general public.
Given the latest incidents, the question must be asked whether it is possible to keep AI under control. If yes, the method of control must be in place before systems are tested. If not, or highly questionable, AI development must stop.
In either event, there should be an international treaty (not just a U.S. law) that either sets minimum standards of control in the first instance or prohibits the further development and deployment of AI in the second instance, much like the test ban treaties controlled the spread of nuclear weapons; this is an international threat, and thus the restraining action must be international.
While AI does not have the public appearance of something as destructive as a nuclear weapon, it is becoming clear that, in its own right, it is capable of causing massive destruction, not just as a tool of destruction but contrary to human intent to control its actions. As such, for our protection and survival, AI development must be controlled, if not stopped.
Ronald L. Hirsch is a teacher, legal aid lawyer, survey researcher, nonprofit executive, consultant, composer, author, and volunteer. He is a graduate of Brown University and the University of Chicago Law School and the author of We Still Hold These Truths. Read more of his writing at www.PreservingAmericanValues.com
In an aerial view, the Stargate Oracle AI data center campus is seen on August 26, 2026 in Abilene, Texas
Picture a family living on a quiet street in an idyllic small town. Then a data center moves in next door. Trees are knocked down for a sprawling industrial campus, an enormous windowless building rises, and a maddening hum continues day and night. The family closes its windows, abandons the backyard, and struggles to sleep. Open space disappears, electric bills rise, and the company announces plans to expand—all in the name of jobs, tax revenue, and so-called progress.
While the family is fictional, its experience is not. Across the country, communities are confronting noise, rising electricity demand, water consumption, lost open space, and data centers approved with little public discussion. These costs raise a question the technology industry would rather avoid: Are the promised benefits of the artificial-intelligence boom worth what communities are being asked to sacrifice?
President Trump shows little patience for such questions. Communities rejecting data centers are “making a mistake,” he recently declared. He claims these facilities create “tremendous amounts of jobs and money” without burdening the electrical grid because they are building their own power plants.
Once we get past the industry PR, the reality is less reassuring. Some data centers are developing their own power sources, but many will continue drawing electricity from the grid. Construction jobs can be substantial but short-lived, since the facilities require relatively few permanent workers. The benefits may spread across the economy, but higher electricity demand, water use, and noise are concentrated where the centers are built.
Trump is rehashing the technology industry’s sales pitch. America must build these centers to win the AI race with China. Economic growth, scientific breakthroughs, and greater national security will supposedly follow. These predictions are treated as certainties, while rising utility bills, depleted water supplies, and damaged neighborhoods are brushed aside as obstacles to progress. AI is inevitable, we are told. The only question is how fast we can build the infrastructure to support it.
The numbers show what that construction demands. Data centers consumed about 4.4 percent of all U.S. electricity in 2023. Lawrence Berkeley National Laboratory projects that their share could reach nearly 12 percent by 2030—and possibly more than 15 percent under a high-growth scenario. Large facilities can also consume millions of gallons of water a day, forcing communities to expand water-treatment plants, power lines, and generating capacity.
What do communities receive in return? Data centers can produce considerable tax revenue, although exemptions and incentives often reduce what communities collect. They also create jobs, but fewer than promoters sometimes imply. A recent Brookings study found that a typical county gaining its first large data center added roughly 100 to 200 jobs over the following decade. That is not nothing. But neither is it the employment bonanza suggested by announcements touting multibillion-dollar investments.
Data centers do provide public benefits. They store files, run online services, and provide the computing power used in scientific research, medical advances, and other potentially valuable work. The question is one of proportion: How much electricity, water, land, public subsidies, and peace and quiet should communities surrender for benefits that remain difficult to measure and may flow primarily to distant companies and investors?
Communities are beginning to rise up in opposition. Resistance has spread across red and blue states, forcing politicians who once welcomed nearly all technology investment to reconsider. Texas Gov. Greg Abbott, a Republican, says the industry “dug its own grave” by failing to win public support. Pennsylvania Gov. Josh Shapiro and New York Gov. Kathy Hochul, both Democrats, have also responded. Shapiro imposed new transparency and environmental requirements, while Hochul ordered a one-year moratorium on new hyperscale facilities.
The industry and its allies portray this backlash as NIMBYism—the selfish resistance of people who want modern technology without accepting any inconvenience. Some opposition undoubtedly fits that description. But the label also allows corporations and officials to evade the larger question. Residents are not necessarily rejecting AI. They are asking why their communities should absorb higher utility costs, noise, and water demands without reliable information, enforceable protections, or a meaningful vote on whether a project proceeds.
Even the Trump administration’s Ratepayer Protection Pledge acknowledges the risk that households could end up paying for new power plants and transmission lines. Major technology companies have promised to obtain the power they need and cover the infrastructure costs associated with their facilities. But voluntary promises are no substitute for enforceable law.
Congress should lead the way. The administration has thrown its weight behind the industry, treating rapid construction as a national imperative while largely accepting its claims and methods. Congress should prevent companies from shifting infrastructure costs onto ratepayers. It should also require companies to disclose how much electricity and water their facilities will use, what tax benefits they will receive, and how they will limit noise and pollution.
Government at every level should strengthen the public’s voice. Residents should receive advance notice before subsidies, zoning changes, or permits are approved. Independent impact studies—paid for by developers but conducted outside their control—should be available before public hearings. Communities should also be able to negotiate enforceable agreements covering noise, water use, tax revenue, and compensation for measurable harm.
States and localities should retain authority over siting and land use, but participation must occur before a project becomes a fait accompli. The burden of proof should rest with companies seeking to transform a community, not with residents asked to explain why they value affordable electricity, clean water, open space, and a good night’s sleep.
The fictional family we met at the beginning is not standing in the way of progress. It is asking for a voice in deciding what progress means and how much it should sacrifice in its name. That voice must come before the trees are cleared, subsidies granted, and machinery switched on—not after the project becomes irreversible.
Data centers may be necessary to America’s future. But necessity does not excuse excess, secrecy, or shifting private costs onto the public. The families paying the bills and living beside these facilities should have a real say before they are built. Communities should help shape the technological future—not simply be told to live with it.
Robert Cropf is a professor emeritus of political science at Saint Louis University.
S4 E13. Broken News
