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.

翻译：基于他人生成的文本，大型语言模型会调整自身行为。这种能力及其在网络环境中日益普及的趋势，预示着它们将有意或无意地相互"编程"，形成新兴的人工智能主体性、关系与集体。在此，我们呼吁研究界对这些交互式人工智能的"类社会"属性展开研究，以增强其对人类社会及网络环境健康的益处，并降低风险。我们通过一个简单模型及其输出示例，说明这种涌现的、去中心化的人工智能集体如何拓展人类多样性的边界，并减少网络中恶意反社会行为的风险。最后，我们探讨了人工智能自我调节的机遇，并阐述了创建与维护去中心化人工智能集体所涉及的伦理问题及设计挑战。