No sooner had we all hopped on the free Gen AI train in late 2022 than we started to criticize and shame our fellow travelers for being on the very same ride.
Whether we are in the Middle Ages or the Digital Ages, there has always been a moral asymmetry between what we notice in others and what we permit or conceal in ourselves.
Especially when social norms and economic rules are unsettled, societies often reach for shame to rein in bad behavior and develop new standards. Every purity culture has visible markers of virtue; confession and concealment; accusations of contamination; and gatekeepers who decide what counts as “pure.” New technologies are often dismissed by those whose expertise is threatened. Sometimes the language sounds moral when, underneath, it is economic or psychological.
Today’s debates over AI use, especially in content generation, are often about who gets to belong, who earns respect, and whose contributions are considered legitimate. Of course, there are justified concerns about AI use that many of us share across society and our professions. Undisclosed AI assistance, fabricated citations, hallucinations presented as fact, plagiarism, and deception all undermine trust. But those are questions of transparency and responsibility and should invite scrutiny.
READ: Sreedhar Potarazu and Carin Isabel Knoop | The AI Nocebo Effect: When fear becomes the forecast (July 16, 2026)
AI critics often frame objections in moral terms: authenticity, honesty, fairness. In this column we explore what the emerging shame around AI use reveals about the psychological and social functions being served. We also consider how AI itself is not just enabling “shame at scale” but also invoking shame easier, faster, more articulate, and allegedly more objective by removing some of the friction that previously concealed our desire to judge.
Shame on you
Few expressions accomplish quite so much in three words. They identify a transgression, appoint a judge, deliver a sentence, and remind the accused that belonging is conditional.
Shame is one of humanity’s oldest forms of behavioral rudder. Long before algorithms scored us, institutions evaluated us, or social media counted our likes, communities had ways of signaling who had crossed a line and making sure everybody knew it: through ridicule, exclusion, gossip, and in case of Nathaniel Hawthorne’s novel, brandishing transgressor with a scarlet letter.
Shame is unusual also because it is simultaneously something we feel and something we do to somebody else. Shame can become “there is something bad about me.” Guilt, in contrast, says, roughly, “I did something bad,” and can serve a useful moral function by prompting accountability, apology, or repair. Shame is more likely to make the person and not simply the behavior the object of judgment. And when we shame others, we make that judgment social: you did not merely violate a standard or expectations but your violation tells us something about who you are and perhaps whether you still belong.
That distinction matters enormously in the AI debate. “Clearly this was written by AI” can be not just an observation about provenance but also a social label. The interesting issue is why we need the label and what status it confers on the person applying it. The LinkedIn proclamation that “This post was written without AI” may come even though the same work relied on Google, Grammarly, spell-check, EndNote, published sources partly generated by AI, or countless other tools, including perhaps research assistants, speechwriters, editors, and analysts whose names are not mentioned.
READ: Sreedhar Potarazu and Carin Isabel Knoop | Friction vs fiction: AI automators, validators, and cyborgs (May 22, 2026)
There is an immediate psychological payoff to dismissing. Declaring a boss “toxic,” a colleague “burned out,” or a piece of writing “AI-generated” offers comforting certainty, assuages our need for judgment, and avoids us the hard work of asking follow-up questions or considering alternative explanations. In that sense, dismissal can provide cognitive comfort and a sense of superiority; ultimately, however, it may also reinforce inaccurate predictions and foreclose learning opportunities. The labels we place on others often reveal our own need to define who deserves to belong and who gets to decide.
Shame at scale
AI does not merely give us something new to shame people for; it actually increases our capacity and appetite for doing so. First, AI makes judgment cheap and easy. Shaming used to require some effort: understanding what someone did, forming an argument, perhaps confronting them, spreading rumors, which all used to take at least a bit of time. AI can instantly generate a critique, identify supposed flaws, compare behavior against a norm, or give us authoritative-sounding language for why someone is wrong. It lowers the friction of condemnation.
Educators and publishers use AI-powered tools to try to assess AI “contaminations.” This AI powered judgment brings with it an aura of objectivity. “I think your writing sounds fake” is an opinion. “The AI detector says 87% AI-generated” sounds like evidence even when such detection is unreliable. AI becomes a rationalization machine.
We can outsource a subjective judgment and then treat the machine’s output as validation. Conferences trap their reviewers; faculty trap their students. Both mock their victims online and probably used AI to draft an accusation, and even use AI to write the policy prohibiting AI in the first place.
Gen AI is also exceptionally good at categorization and explanation, which could tempt us to replace curiosity with increasingly sophisticated labels. It can wax eloquent about why it is unethical for a student to use ChatGPT just as it can make an equally impassioned case for why prohibiting ChatGPT is unfair.
Moreover, technology makes shame scalable. Historically, shame was largely bounded by the community and as we noted below, it might take some time and effort to spread. Social media made public shaming global.
READ: Sreedhar Potarazu and Carin Isabel Knoop | The White Rabbit Effect: How AI is changing our relationship with time (June 25, 2026)
Finally, AI makes comparison almost limitless who can amply not just interpersonal shame btu also self-shame. Shame depends partly on standards: I am falling short of what someone like me should be. AI can continuously show us what better writing, better presentations, better résumés, better photographs, better answers and seemingly better people look like. The reference group against which we judge ourselves becomes synthetic and potentially unattainable.
From Shame to Scrutiny
For a long time, we have judged books, speeches, paintings, and business strategies primarily by their quality, not by every tool or invisible human involved in their production. Ironically, people who never felt ashamed about hiring human help for content production may be the ones who most shame those who use AI.
Our educational and professional systems have long relied on effort as evidence of deservingness. Many cultures treat hardship as evidence of character. AI violates one of our deepest social norms: we expect effort to be observable to legitimize achievement. AI makes effort invisible; we cannot tell whether it took six hours to wrestle with an idea to write this column or a few minutes with a clever prompt. If effort is no longer visible, how do we know who deserves the grade, the promotion, or the praise?
If we no longer measure intelligence by how long it takes someone to produce an answer, the question becomes what we should we measure instead. Today someone with average writing skills and excellent AI judgment may outperform someone with exceptional writing skills who refuses to use it. That forces us to reconsider what we actually value: the labor, the product, or the judgment behind it.
Finally, we often assume that AI lowers standards — and perhaps it does and will. But it also lowers barriers and is a remarkable democratizer. Throughout history, many people had ideas worth sharing but lacked the writing skills, time, confidence, language proficiency, or educational opportunities to express them effectively. AI allows people to spend less energy on grammar, syntax, or structure and more on the quality of their thinking. In that sense, AI may broaden participation rather than redistribute status. This should be praised, not shamed.