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Perfect detection of computer-generated text faces fundamental challenges

Martin Májovský, Martin Černý, David Netuka, Tomáš Mikolov

2024Cell Reports Physical Science16 citationsDOIOpen Access PDF

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.

Topics & Concepts

Complement (music)Arms raceComputer scienceFocus (optics)Race (biology)Point (geometry)PublishingEngineering ethicsData sciencePolitical scienceSociologyEngineeringLawPhenotypePolitical economyBiochemistryGeometryMathematicsOpticsComplementationGender studiesPhysicsChemistryGeneArtificial Intelligence in Healthcare and EducationExplainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI
Perfect detection of computer-generated text faces fundamental challenges | Litcius