AI Detection Is a Poor Substitute for Human Judgment

An AI detector recently told me that two lines I had written resembled AI text and were likely to be flagged as AI-generated.

The words?

“Agenda. September 3, 2026.”

That was it. A heading and a date.

I would have laughed and moved on if I hadn’t recently seen two separate instances of human-written material being flagged after its authors used AI to help edit it. The ideas, experiences and original drafts belonged to the people who wrote them. They used a tool to refine the expression.

Seeing their authorship called into question made that ridiculous little warning about my agenda feel less harmless.

I understand the frustration with AI slop. Publishing generic content without checking its accuracy or contributing anything useful deserves criticism. Fabricated stories and unchecked claims damage credibility. But an accusation of AI use deserves scrutiny, too.

An AI flag deserves a conversation

A detector’s assessment cannot give us a complete account of how a piece was created. It does not tell us who developed the argument, supplied the experience or checked the claims.

Even companies selling detection tools acknowledge limitations. Turnitin warns that its model can misidentify human-written and AI-generated text and advises against using its report as the sole basis for adverse action against a student. Turnitin Guides

That caution should carry into how we treat colleagues, writers and other professionals. A flag can prompt a conversation. It should not become an automatic accusation.

Someone whose writing has been flagged deserves a chance to explain their process. Looking at drafts, notes and sources can help us understand what happened. So can asking the author to explain the reasoning behind an argument.

Treating a score as a verdict gives software authority it has not justified.

Be specific about the use

“They used AI” tells us very little on its own.

A person might use it to brainstorm possible titles, identify repetition in a draft or suggest a clearer sentence. Another person might ask it to produce an entire article and publish the response without checking a word.

Those choices involve different levels of human contribution and responsibility. We need language that describes them accurately.

I care about who supplied the thinking. I care about whether a personal story belongs to the person telling it. I care about whether the writer checked the information and can explain the conclusions.

Editing assistance does not automatically erase authorship. It can still require careful review. A suggested edit may change the meaning, introduce an error or remove something distinctive from the writer’s voice. The person approving that edit remains responsible for it.

That responsibility continues through publication. Putting your name on something means being prepared to answer for what it says.

Make expectations clear before judging people

Leaders, editors and educators need to explain what assistance is acceptable before evaluating someone’s use of it.

A writing assignment designed to assess independent ability may require a different process from a company blog post. A publication may require disclosure of certain AI uses. A client may have restrictions on entering information into an outside tool.

People need those expectations in plain language. Does editing assistance count? Is brainstorming permitted? When is disclosure required? What information must stay out of the tool?

Clear answers give people a way to make responsible decisions. Vague accusations leave them guessing whether a feature they used will later become a reason to doubt their integrity.

We also need to examine the finished piece. Is it accurate? Does it offer something useful? Does it reflect the author’s knowledge and experience? Can the author defend it and correct mistakes?

Human accountability has to remain part of that assessment, regardless of which tools were involved.

I wrote the agenda. I chose the date. A detector’s suspicion changed neither of those facts.

Before we question someone else’s honesty on similarly thin evidence, we owe them the judgment we expect them to bring to their writing.