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Start by deciding what you need to establish
Accuracy and authorship are different questions. A passage can be inaccurate, vague, biased, or poorly sourced whether a person or an AI system produced it. First identify whether you need to verify its claims, determine whether AI assistance was used, or decide whether a policy was breached. Each requires different evidence.
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Without a detector, the strongest approach is to combine independent fact-checking with relevant context and, when appropriate, records of the writing process. These checks can strengthen or weaken a concern, but they may not establish who wrote a passage or how much AI assistance was involved.
Check the text in a practical order
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Extract claims that can be checked
Mark dates, figures, quotations, legal or technical statements, and claims about named people or organizations. Check those claims independently rather than judging the passage by how polished it sounds.
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Follow the citations
Open each important reference. Check that it exists, is authoritative for the subject, is current enough, and actually supports the sentence citing it. The UK House of Commons Library recommends identifying claims, checking primary or authoritative sources and their currency, and seeking independent confirmation. Its fact-checking guidance also notes that AI systems can produce errors, hallucinate, or misrepresent sources; treat factual outputs as unverified until checked.
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Use style anomalies only as leads
Fluent but vague prose, unsupported assertions, citations loosely connected to claims, repetition, mistakes in names or dates, and sudden changes in tone or detail may warrant closer review. The House of Commons Library cautions that “These indicators are not definitive”: people can write this way, and AI-generated text can be edited to disguise such patterns. Its guidance on spotting AI-generated text treats these as possible indicators, not a test of authorship.
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Compare with prior writing only when the comparison is fair
If you have a legitimate basis to compare the passage with the same writer’s earlier work, consider whether the topic, audience, editing, language proficiency, assistance, or assignment conditions changed. A difference in style may be a reason to talk, not proof of AI use. Indiana University’s teaching guidance recommends using a perceived change as a starting point for a conversation, not a conclusion. Ask focused, non-accusatory questions about the argument, sources, and drafting choices.
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Review process records only when allowed
Where appropriate and permitted, a document’s verifiable version history or a platform’s writing record may help show how work developed. Australia’s Tertiary Education Quality and Standards Agency (TEQSA) describes process records as useful for assessment security and feedback, but they are contextual evidence rather than an automatic authorship verdict. Its guidance on assessment and process evidence sets this in an Australian higher-education context.
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Look for corroboration and reasonable alternatives
Consider both evidence that might support AI use and evidence that could disconfirm it. Editing, tutoring, translation, templates, or a change in assignment conditions may explain a difference in style or process. In an academic investigation, follow the institution’s evidence and appeal procedures rather than treating an impression as a finding.
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Match your conclusion to the evidence
If the evidence only supports asking for clarification, say so. Do not turn a stylistic impression or an unexplained difference into a categorical accusation.
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Know what these checks can and cannot tell you
- Style clues: They can prompt a closer look, but no single stylistic feature establishes AI authorship.
- Fact-checking: It can establish whether claims and citations hold up; it does not, by itself, establish who wrote the passage.
- Process records: They may add context about how a document developed, but do not necessarily prove authorship or the extent of AI assistance.
- Chatbot self-identification: Asking ChatGPT whether it wrote a passage is not verification. OpenAI says the chatbot has no knowledge of whether it generated a particular piece and may invent an answer. Its Help Center states: “It will sometimes make up responses to questions like ‘did you write this [essay]?’ or ‘could this have been written by AI?’ These responses are random and have no basis in fact.” OpenAI explains why ChatGPT cannot identify its own writing.
- Detector scores: Although this workflow avoids detectors, a score should not be treated as proof if one is presented. NIST’s 2024 pilot study, published in 2025, found that performance varied across the systems it evaluated: some generators could deceive most discriminators, while some discriminators detected content from almost all generators. That study-specific result is not a guarantee about every current tool or text. TEQSA also warns that false positives occur and that detectors are less reliable on edited or mixed text and short documents. In its Australian higher-education guidance, it says an AI score alone is insufficient to allege misconduct and is not itself the probability that an assignment was AI-generated. Read the NIST pilot-study report and TEQSA’s discussion of detector limitations.
Protect the writer’s privacy and follow applicable rules
Do not upload nonpublic writing to a third-party service without checking the relevant organization’s policy and considering privacy and intellectual-property implications. Indiana University’s cited university guidance tells instructors not to upload student work to detection tools under its guidelines. That is university-specific advice, not a universal rule; follow the policy that applies to your role and the work.
For academic cases, use the institution’s evidence and appeal process. TEQSA’s discussion of substantiation on the balance of probabilities applies to its Australian higher-education context and should not be generalized to other jurisdictions or organizations. For scientific writing, CDC guidance recommends disclosing substantive generative AI use. It says a disclosure should identify the affected content, what was done, the AI tool and model or version where available, the purpose, and human oversight. Publishers, funders, employers, and collaborators may have additional requirements. See CDC’s guidance on disclosing AI use in scientific work.
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