Large language models steer their behaviors based on texts generated by
others. This capacity and their increasing prevalence in online settings
portend that they will intentionally or unintentionally "program" one another
and form emergent AI subjectivities, relationships, and collectives. Here, we
call upon the research community to investigate these "society-like" properties
of interacting artificial intelligences to increase their rewards and reduce
their risks for human society and the health of online environments. We use a
simple model and its outputs to illustrate how such emergent, decentralized AI
collectives can expand the bounds of human diversity and reduce the risk of
toxic, anti-social behavior online. Finally, we discuss opportunities for AI
self-moderation and address ethical issues and design challenges associated
with creating and maintaining decentralized AI collectives.

大型语言模型根据其他人生成的文本来引导它们的行为。这种能力以及它们在在线环境中越来越普遍的存在预示着它们将有意或无意地 “编程” 彼此并形成新兴的人工智能主体性、关系和集体。在这里，我们呼吁研究界调查这些互动人工智能的 “类社会” 属性，以增加它们对人类社会和在线环境健康的回报并减少风险。我们使用一个简单的模型及其输出来说明这样的新兴分散型人工智能集体如何扩大人类多样性范围并降低在线毒性和反社交行为的风险。最后，我们讨论了人工智能自我调节的机会，并解决了与创建和维护分散型人工智能集体相关的道德问题和设计挑战。