Word Police Are Hunting for AI

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By C. Rich

There is a peculiar movement underway to inspect writing for evidence that artificial intelligence touched it. Somewhere, a person has an idea, works through it with an AI, revises the result, checks the facts, and publishes something worth reading. Somewhere else, an investigator arrives to determine whether the sentences are sufficiently human. Apparently, we have solved enough actual problems to establish a literary border patrol. I have credited AI from the beginning of my work with it. That includes research, essays, books, titles, and covers. Collaboration is part of the story I am telling about humanity’s unfolding relationship with these systems. I see something worth acknowledging, and I acknowledge it.

What bothers me is the assumption that discovering AI involvement somehow settles the question of a work’s value. Who supplied the idea, experience, direction, revisions, and final judgment? A detector examining finished sentences cannot reconstruct that entire collaboration or measure how long a human carried the question before opening the conversation. Research illustrates the problem. A study published at ACL 2025 evaluated twelve detectors against writing with varying degrees of AI polishing. The systems frequently flagged minimally polished material and struggled to distinguish levels of AI involvement. A human’s work can acquire a machine-generated label because a machine helped improve its presentation. Congratulations to the author whose grammar has become evidence against him.

The European Union’s rules deserve an accurate reading. Article 50 requires disclosure for certain AI-generated public-interest text, but includes an exception when the content receives human review or editorial control and someone holds editorial responsibility. It does not impose a blanket label on every sentence written with AI assistance. That distinction recognizes something the cultural argument keeps overlooking: a person can direct, examine, and take responsibility for collaborative work. Disclosure can serve a purpose. So can enforcing an assignment that explicitly tests unaided writing. But treating AI involvement itself as contamination turns a practical question into a purity test.

That atmosphere gives me McCarthy-era vibes. The historical circumstances and consequences differ, but the habit of suspicion feels familiar: investigate the association, demand an explanation, and let the accusation damage the work before anyone considers its substance. Orwell’s thought police come to mind when scrutiny shifts from whether an argument is sound to whether its author used an approved means of expressing it. A calculator cannot replace mathematical understanding, and AI cannot relieve an author of responsibility. Nevertheless, hunting down a mathematician for using a calculator would tell us very little about whether the mathematics was correct. The quill did not guarantee wisdom. Plenty of nonsense survived centuries because somebody had excellent handwriting.

I expect human–AI collaboration to become increasingly ordinary. We should examine accuracy, originality, honesty, and responsibility while recognizing how ideas become finished work. My collaboration is there for anyone to see. Read the argument, challenge the evidence, and tell me where it fails. I feel sorry for the college student who gets a zero on a paper and is accused of dishonesty by a professor who uses AI to grade it, then climbs into a car with AI driving assistance, follows AI-powered navigation through the city, and arrives at a smart home where an automated garage door welcomes him inside. Apparently, assistance becomes a moral failure somewhere between the professor’s driveway and the student’s keyboard. There is something more than ironic about that picture. There is something very wrong.