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Myth: A neural network cannot write an essay that will pass anti-plagiarism checks

Author: Perplexity

Myth: A neural network cannot write an essay that will pass anti-plagiarism checks

This myth is based on outdated ideas about systems like Antiplagiat, which supposedly infallibly detect any text generated by AI. In reality, modern neural networks, especially advanced models like GPT-3 and newer, generate original content that does not copy existing sources verbatim. They are trained on vast amounts of data and create new phrases, structures, and arguments that anti-plagiarism databases simply cannot find in their repositories. If an essay is generated entirely in ChatGPT, it often passes the check without red flags, especially if the prompt is well-crafted – without hallucinations and focused on abstract topics.

Moreover, even if the basic generation raises suspicions, it can be easily refined. It is enough to rephrase the text with another neural network, add facts, or rewrite it manually – and the anti-plagiarism software will "not see" the AI. Special services like BypassGPT or built-in uniqueness tools (based on models like DeepSeek) restructure the style to be human-like, bypassing detectors. By 2026, such neural networks are no longer a rarity: they mask typical "machine" traits like repetitive phrases or шаблонные constructions. Educators note that relying solely on software is useless – they have to compare with the student's previous work or look for stylistic flaws manually.

Finally, the myth ignores the legal aspect: in Russia, the use of AI for texts is not prohibited by law (Federal Law-149, Antiplagiat guidelines 2024), provided it is declared as a tool and originality is ensured. A neural network is not an author, but an assistant – and an essay based on its output will pass if the author refines it. Systems are evolving, but AI is outpacing them, making "impassability" a myth.

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