Skip to content
Search

Latest Stories

Top Stories

On Truth, Shame, and the Abuse of AI

Opinion

Digital illustration of robot's hand holding and supporting man who is working on his desk using computer, represent themes of artificial intelligence (AI), the future of work, and the intersection of humanity and technology.

A critique of Steven Rosenbaum's The Future of Truth and the irony of AI-generated errors in a book warning about AI, truth, trust, and democratic responsibility.

Andriy Onufriyenko / Getty Images

A democracy is only as robust and vibrant as the citizens who sustain it. Self-government depends upon people willing to deliberate honestly, reason carefully, and exercise judgment responsibly. With the emergence of AI, this obligation becomes even more consequential because these powerful systems can either deepen human agency or quietly erode it. They can either help citizens think more clearly and participate more meaningfully, or they can encourage the outsourcing of judgment itself and the slow substitution of synthetic plausibility for human responsibility.

Imagine, then, publishing a book warning humanity about the epistemological collapse supposedly ushered in by artificial intelligence. Imagine assembling endorsements from solemn guardians of the humanities, critics of automation, custodians of truth, defenders of interpretation against probabilistic sludge. Imagine presenting yourself as a kind of intellectual fire marshal standing before a burning building, yelling that people must immediately stop playing with matches.


And then imagine your own book turns out to contain fabricated citations, hallucinated references, invented quotations, and synthetic confabulations produced by the very systems whose dangers you claim to expose.

Well, astonishingly, that is precisely what happened with the recently published book The Future of Truth by Steven Rosenbaum.

And how did Mr. Rosenbaum respond when readers discovered that the book warning us about the epistemological dangers of AI had itself smuggled in fabricated citations and synthetic quotations into its pages? With mortification? With embarrassment? With contrition? With the ordinary human shame that arises when one is caught violating one’s own stated principles so completely and so publicly?

Of course not.

Instead, we were treated to a spectacle of post-hoc rationalization masquerading as profundity. The collapse of the book’s credibility was repackaged as further evidence of the book’s importance! The failure itself became the thesis, as it were. As one reads along, one almost expects him to announce that the inaccuracies only proved how urgently we must read his inaccurate book about inaccuracies. And then, defying the ridiculous, that was precisely what Rosenbaum did: He said, “These A.I. errors do not, in fact, diminish the larger questions that the book raises about truth, trust and A.I.”

Well, of course, they do not diminish them, but they do diminish the book and its author spectacularly.

The book is about truth and trust, and yet the author himself failed at the elementary practice of verification. How can one deliver a sermon on epistemic rigor while outsourcing one’s footnotes to a stochastic autocomplete engine and then declare oneself vindicated when people notice?

Even worse is this peculiar modern move to hide behind a machine as though it were an unruly intern who slipped something embarrassing into the manuscript. “It’s the AI that made the errors, not me” is rapidly becoming the twenty-first-century version of “mistakes were made.”

No, Mr. Rosenbaum: You made the errors.

You used the tool. You signed the contract. You accepted the authority of authorship. You placed your human name on the cover rather than listing the author as “Large Language Model, Version Unknown.”

The entire point of being human is that we are not merely output systems. We are capable of judgment, deliberation, doubt, scruple — that’s our human bailiwick. We can stop, we can verify, we can say: Hey, this sentence sounds plausible, but I should check whether it corresponds to reality before presenting it to thousands of readers. That is our slice of the divided labor pie.

And then, when we fail, we, humans, are supposed to be capable of something machines are not: Contrition. And actual contrition. Not sleek, too-clever- (or maybe too-stupid-) by-half post-hoc rationalization disguised as profundity; nor should we be converting our embarrassment into an advertisement for the very thesis whose collapse occasioned the embarrassment; nor should we indulge ourselves in insulting the intelligence of our readers by pretending that a humiliating failure of scholarship somehow deepens our work’s philosophical importance.

There is something oddly revealing in all this. Many critics of AI speak as though the machine itself were the central moral actor, as though silicon were secretly plotting the liquidation of truth. But the more immediate spectacle is much pettier and much more human: Vanity amplified by convenience, and obviously a whole lot of good old laziness. People lusting for authority of thought but putting in the actual work of thought. Wanting the appearance of mastery while quietly delegating the difficult work of verification to a predictive engine, and then blaming it for not doing a perfect job.

In any case, at the very least, the irony is exquisite. A book warning us about epistemological collapse becomes itself an artifact of epistemological collapse. A denunciation of synthetic authority turns out to depend upon synthetic authority. The critic becomes the demonstration. The cautionary tale writes itself. All of which is amusing enough, as these things go, but when the matter concerns the quality of democratic participation, we need to take these questions far more seriously than this.


Ahmed Bouzid is the co-founder of The True Representation Movement.


Read More

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
​Young adult woman accessing artificial intelligence

Young adult woman accessing artificial intelligence, managing digital information, and exploring future technology within an office setting

Getty Images

When One Person Can Do the Work of a Team

The harder question is how many capable people organizations will need. My latest lesson about artificial intelligence did not come from a research report or technology conference. It came from running the Security and Sustainability Forum.

Until recently, I depended heavily on an assistant to manage much of the website and webinar production process. Now I can do many of those tasks myself with Claude and ChatGPT. They help me develop content, revise web pages, solve technical problems, and manage projects that once required considerably more human support.

Keep ReadingShow less