While the possibility of reaching human-like Artificial Intelligence (AI) remains controversial, the likelihood that the future will be characterized by a society with a growing presence of autonomous machines is high. Autonomous AI agents are already deployed and active across several industries and digital environments and alongside human-human and human-machine interactions, machine-machine interactions are poised to become increasingly prevalent. Given these developments, I argue that criminology must begin to address the implications of this transition for crime and social control. Drawing on Actor-Network Theory and Woolgar's decades-old call for a sociology of machines -- frameworks that acquire renewed relevance with the rise of generative AI agents -- I contend that criminologists should move beyond conceiving AI solely as a tool. Instead, AI agents should be recognized as entities with agency encompassing computational, social, and legal dimensions. Building on the literature on AI safety, I thus examine the risks associated with the rise of multi-agent AI systems, proposing a dual taxonomy to characterize the channels through which interactions among AI agents may generate deviant, unlawful, or criminal outcomes. I then advance and discuss four key questions that warrant theoretical and empirical attention: (1) Can we assume that machines will simply mimic humans? (2) Will crime theories developed for humans suffice to explain deviant or criminal behaviors emerging from interactions between autonomous AI agents? (3) What types of criminal behaviors will be affected first? (4) How might this unprecedented societal shift impact policing? These questions underscore the urgent need for criminologists to theoretically and empirically engage with the implications of multi-agent AI systems for the study of crime and play a more active role in debates on AI safety and governance.

翻译：尽管实现类人人工智能（AI）的可能性仍存争议，但未来社会将日益呈现自主机器普遍存在的特征，这一趋势具有高度可能性。自主AI智能体已在多个行业和数字环境中部署并活跃，除了人与人、人与机器的交互外，机器与机器之间的交互预计将变得越来越普遍。鉴于这些发展，我认为犯罪学必须开始探讨这一转变对犯罪与社会控制的影响。借鉴行动者网络理论以及Woolgar数十年前提出的‘机器社会学’主张——这些框架随着生成式AI智能体的兴起而重新获得现实意义——我主张犯罪学家应超越仅将AI视为工具的观念。相反，AI智能体应被理解为具有能动性的实体，其能动性涵盖计算、社会和法律维度。基于AI安全领域的文献，我进而审视了多智能体AI系统兴起所带来的风险，提出了一种双重分类法，用以刻画AI智能体间交互可能产生越轨、违法或犯罪结果的渠道。随后，我提出并讨论了四个值得理论与实证关注的关键问题：（1）我们能否假设机器只会简单模仿人类？（2）为人类开发的犯罪理论是否足以解释自主AI智能体交互中产生的越轨或犯罪行为？（3）哪些类型的犯罪行为将首先受到影响？（4）这种前所未有的社会变革可能如何影响警务工作？这些问题凸显了犯罪学家迫切需要从理论与实证层面关注多智能体AI系统对犯罪研究的影响，并在AI安全与治理的辩论中发挥更积极的作用。