论人工智能对认知安全的挑战

Ruiyang Huang, Xiaoqing Zheng, Yuting Shang, Xiangyang Xue
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引用次数: 1

摘要

深度学习的最新进展导致了人工智能(AI)的颠覆性突破,推动了类似chatgpt的大型语言模型(llm)的飞跃。与任何新兴技术一样,它是一枚两面硬币,不仅带来了巨大的社会影响,也带来了重大的安全问题,特别是在社会认知领域。在此背景下,本研究从认知域博弈的内在机制分析入手,探讨认知域面临的安全问题,并分析认知免疫系统的形成机制。最后,受生物学中行为模仿的启发,本文将从模拟计算、模拟防御和模拟智能三个方面阐述认知安全的新途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Challenges of AI to Cognitive Security and Safety
Recent advances in deep learning have led to disruptive breakthroughs in artificial intelligence (AI), fueling the jump in ChatGPT-like Large Language Models (LLMs). As with any emerging technology, it is a two-sided coin, bringing not only vast social impacts but also significant security concerns, especially in the socio-cognitive domain. Against this background, this work starts with an inherent mechanism analysis of cognitive domain games, from which it proceeds to explore the security concerns facing the cognitive domain as well as to analyze the formation mechanisms of a cognitive immune system. Finally, inspired by the behavioral mimicry in biology, this work will elaborate on new approaches to cognitive security from three aspects: Mimicry Computing, Mimicry Defense and Mimicry Intelligence.
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