I came across an article called “What Counts As Cheating With Ai?”. Ironically, when I read the first sentence, I suspected that it was written using a large language model (LLM; a kind of artificial intelligence or “AI” application). To confirm my hypothesis, I consulted with my favorite LLM, ChatGPT. Check out my full conversation for details.
In summary, ChatGPT drew its own conclusions and also consulted various external sources, with the ultimate conclusion that there is an 85-95% probability that the article was AI-written. Based on ChatGPT’s assessment, the reasons it provided include:
- Odd word choices / nonnative phrasing
- Inconsistent tense / mismatch / weird connectors
- Repetitive structure, formulaic transitions
- Errors not typical of human edits
- Lack of smooth coherence in some parts
- Metadata / site context
- References / linking style
Those 7 reasons are based on the article that I referenced above, and there are many other criteria that can be used in general to detect AI-authored content. ChatGPT also also compared the text from the article against published criteria from major AI detectors, and it stated:
- GPTZero: Looks at perplexity (predictability of text) and burstiness (variation between sentences). AI text tends to have low burstiness and oddly consistent perplexity. The uniform style and repeated sentence shapes here match GPTZero’s “likely AI” profile.
- CrossPlag AI Detector: Notes that AI often creates unnatural collocations and semantic drift. Examples: “analyzable and confusing” or “students will ne’er ace open” are exactly that.
- Sapling AI Detector: Flags AI when there’s “inflated use of rare words not fitting context”. Words like “erstwhile” and “conscionable” fit this.
In conclusion, if you need help detecting AI-authored content, consider asking AI for help. I found ChatGPT’s reasoning to make a lot of sense, and the AI detectors listed above also seem to have valid criteria for identifying AI-authored content.
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