Perfect detection of computer-generated text faces fundamental challenges

IF 7.9 2区 综合性期刊 Q1 CHEMISTRY, MULTIDISCIPLINARY
Martin Májovský, Martin Černý, David Netuka, Tomáš Mikolov
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引用次数: 0

Abstract

Recent advancements in large language models (LLMs) have sparked a debate on the detection of artificial intelligence (AI)-generated text, a concern especially prevalent among academic institutions and publishers. While current detection tools claim high accuracy rates, some studies point to their unreliability. This paper contends that efforts to detect AI writing are fundamentally flawed because improved detection capabilities could inadvertently refine AI writing tools, leading to a technological arms race. Moreover, the rapid evolution of LLMs means detection methods may quickly become obsolete. We propose a focus on ethical guidelines rather than outright prohibitions, emphasizing that technological solutions should complement, not replace, the core ethical principles of scientific publishing.

完美检测计算机生成的文本面临根本性挑战
大型语言模型(LLMs)的最新进展引发了一场关于人工智能(AI)生成文本检测的讨论,这一问题在学术机构和出版商中尤为普遍。虽然目前的检测工具声称准确率很高,但一些研究指出它们并不可靠。本文认为,检测人工智能写作的努力存在根本性缺陷,因为检测能力的提高可能会无意中完善人工智能写作工具,从而导致技术军备竞赛。此外,LLM 的快速发展意味着检测方法可能很快就会过时。我们建议将重点放在伦理准则上,而不是直接禁止,强调技术解决方案应该补充而不是取代科学出版的核心伦理原则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cell Reports Physical Science
Cell Reports Physical Science Energy-Energy (all)
CiteScore
11.40
自引率
2.20%
发文量
388
审稿时长
62 days
期刊介绍: Cell Reports Physical Science, a premium open-access journal from Cell Press, features high-quality, cutting-edge research spanning the physical sciences. It serves as an open forum fostering collaboration among physical scientists while championing open science principles. Published works must signify significant advancements in fundamental insight or technological applications within fields such as chemistry, physics, materials science, energy science, engineering, and related interdisciplinary studies. In addition to longer articles, the journal considers impactful short-form reports and short reviews covering recent literature in emerging fields. Continually adapting to the evolving open science landscape, the journal reviews its policies to align with community consensus and best practices.
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