Self-Governing Hybrid Societies and Deception

IF 2.2 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Ștefan Sarkadi
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引用次数: 0

Abstract

Self-governing hybrid societies are multi-agent systems where humans and machines interact by adapting to each other’s behaviour. Advancements in Artificial Intelligence (AI) have brought an increasing hybridisation of our societies, where one particular type of behaviour has become more and more prevalent, namely deception. Deceptive behaviour as the propagation of disinformation can have negative effects on a society’s ability to govern itself. However, self-governing societies have the ability to respond to various phenomena. In this paper we explore how they respond to the phenomenon of deception from an evolutionary perspective considering that agents have limited adaptation skills. Will hybrid societies fail to govern deceptive behaviour and reach a Tragedy of The Digital Commons? Or will they manage to avoid it through cooperation? How resilient are they against large-scale deceptive attacks? We provide a tentative answer to some of these questions through the lens of evolutionary agent-based modelling, based on the scientific literature on deceptive AI and public goods games.

自治的混合社会与欺骗
自我管理的混合社会是人类和机器通过适应彼此的行为进行互动的多代理系统。人工智能(AI)的进步使我们的社会日益混合化,其中一种特殊的行为变得越来越普遍,那就是欺骗。传播虚假信息这种欺骗行为会对社会的自我治理能力产生负面影响。然而,自治社会有能力应对各种现象。考虑到代理人的适应能力有限,本文将从进化的角度探讨他们如何应对欺骗现象。混合社会是否会因为无法控制欺骗行为而陷入 "数字公地悲剧"?还是会通过合作避免悲剧的发生?它们抵御大规模欺骗性攻击的能力如何?我们以欺骗性人工智能和公共物品博弈的科学文献为基础,通过基于进化代理的建模视角,对其中一些问题给出了初步答案。
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来源期刊
ACM Transactions on Autonomous and Adaptive Systems
ACM Transactions on Autonomous and Adaptive Systems 工程技术-计算机:理论方法
CiteScore
4.80
自引率
7.40%
发文量
9
审稿时长
>12 weeks
期刊介绍: TAAS addresses research on autonomous and adaptive systems being undertaken by an increasingly interdisciplinary research community -- and provides a common platform under which this work can be published and disseminated. TAAS encourages contributions aimed at supporting the understanding, development, and control of such systems and of their behaviors. TAAS addresses research on autonomous and adaptive systems being undertaken by an increasingly interdisciplinary research community - and provides a common platform under which this work can be published and disseminated. TAAS encourages contributions aimed at supporting the understanding, development, and control of such systems and of their behaviors. Contributions are expected to be based on sound and innovative theoretical models, algorithms, engineering and programming techniques, infrastructures and systems, or technological and application experiences.
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