Why Intros and Conclusions Get Flagged as AI (and What to Do)

Introductions and conclusions are more likely to be flagged as AI than body paragraphs. Turnitin's release notes from May 2023 state: "Since launch, we have observed a higher incidence of false positive detection in the first few or last few sentences of a document. Many times these sentences consist of introduction or conclusion content written in a generic way." The detection logic was updated to reduce these false positives, but the pattern of generic, formulaic writing in intros and conclusions still exists. If your introduction starts with a broad statement and your conclusion restates your thesis in predictable language, those passages can produce word probability profiles that overlap with AI-generated text, even after the 2023 improvement.

The May 2023 release note describes the pattern and the response:

"Since launch, we have observed a higher incidence of false positive detection in the first few or last few sentences of a document. Many times these sentences consist of introduction or conclusion content written in a generic way. As a result, we have changed our detection logic to help reduce these false positives."

The next sentence: "We also worked on making our segment boundaries detection more precise which could lead in some rare cases to change of boundaries compared with a previous version."

This was a 2023 improvement, not a description of a current defect. The detection logic was changed to help reduce false positives in those positions. But the note tells us something important: the first and last sentences of a document were inherently more prone to false positives. The improvement reduced the problem. It did not eliminate it.

The release note points to "introduction or conclusion content written in a generic way." Generic content is the connective tissue here. Introductions often start with broad context: "In recent years, X has become an important topic." Conclusions often restate the thesis: "This paper has shown that X leads to Y." These constructions are predictable, formulaic, and structurally uniform. Turnitin's FAQ lists "content without a lot of structural variation" as a false-positive-prone characteristic. Generic introductions and conclusions are exactly that kind of content. The word probability patterns in these sections tend to be more predictable than in body paragraphs, where the argument is more specific and the language more varied. The general form of this is why AI detectors flag well-written essays.

The detection pipeline works by segmenting text:

"When a paper is submitted to Turnitin, sentences from the submission are extracted and segmented into overlapping sections for prediction analysis. Each segment is classified by the AI detection model and given a value between 0 and 1, denoting the probability of the text being likely human or AI-generated. Each qualifying sentence within these segments inherits the segment's score. Since segments overlap, some sentences may have multiple scores, which are then pooled into a single score."

The release note also mentions "segment boundaries detection." The first and last sentences of a document sit at the edge of the segment structure. Before the 2023 improvement, these positions had a higher false positive rate. The improvement made segment boundary detection more precise, which helped. But the content itself, if written generically, can still produce word probability patterns that trigger classification as AI-like. What those patterns are is the subject of does Turnitin use perplexity and burstiness.

Turnitin's FAQ also notes:

"In shorter documents where there are only a few hundred words, the prediction will be mostly 'all or nothing' because we're predicting on a single segment without the opportunity to overlap."

The next sentence: "This means that some text that is a mix of AI-generated and original content could be flagged as entirely AI-generated."

In a short essay, the introduction and conclusion may be a large proportion of the total text. If both are flagged, the all-or-nothing behavior of short documents means the entire document could be classified as AI-generated. This is an extreme outcome but it helps explain why a short essay with a generic intro and conclusion can receive a surprisingly high score. Why Turnitin says your work is 100% AI walks that extreme case end to end.

To summarize what we have covered:

• Turnitin's release notes from May 2023 describe a pattern of higher false positives in the first and last sentences of documents.
• The detection logic was updated in 2023 to reduce this, but the underlying pattern of generic intro and conclusion writing still exists.
• Generic intros and conclusions share the "low structural variation" characteristic that the FAQ lists as false-positive-prone.
• Short documents amplify the problem because the intro and conclusion are a larger proportion of the total text.
• Making your introduction and conclusion more specific, less formulaic, and more varied in structure can help address the pattern.

If you have a Turnitin report showing which passages were flagged, import the report and work on those specific passages. Eligible passages can be re-run at no charge.