One of the challenges artificial intelligence (AI) faces is how a collection of agents coordinate their behaviour to achieve goals that are not reachable by any single agent. In a recent article by Ozmen et al this was framed as one of six grand challenges: That AI needs to respect human cognitive processes at the human-AI interaction frontier. We suggest that this extends to the AI-AI frontier and that it should also reflect human psychology, as it is the only successful framework we have from which to build out. In this extended abstract we first make the case for collective intelligence in a general setting, drawing on recent work from single neuron complexity in neural networks and ant network adaptability in ant colonies. From there we introduce how species relate to one another in an ecological network via niche selection, niche choice, and niche conformity with the aim of forming an analogy with human social network development as new agents join together and coordinate. From there we show how our social structures are influenced by our neuro-physiology, our psychology, and our language. This emphasises how individual people within a social network influence the structure and performance of that network in complex tasks, and that cognitive faculties such as Theory of Mind play a central role. We finish by discussing the current state of the art in AI and where there is potential for further development of a socially embodied collective artificial intelligence that is capable of guiding its own social structures.

翻译：人工智能（AI）面临的核心挑战之一在于：智能体集合如何协调其行为，以实现任何单一智能体均无法达成的目标。在Ozmen等人近期发表的一篇文章中，这被列为六大重大挑战之一：AI需要在人机交互前沿尊重人类的认知过程。我们认为，这一挑战应延伸至AI-AI交互前沿，且AI系统亦应借鉴人类心理机制——因为这是我们目前构建智能体系的唯一成功范式。在本扩展摘要中，我们首先基于神经网络中单个神经元的复杂性研究及蚁群网络的自适应机制，论证通用场景下集体智能的必要性。进而通过生态网络中的生态位选择、生态位抉择与生态位趋同机制，阐释物种间的关联模式，以此类比人类社交网络中新增智能体如何通过协同形成社会联结。随后我们论证社会结构如何受神经生理机制、心理机制及语言系统的共同塑造。这揭示了社会网络中的个体如何通过复杂任务影响网络结构与效能，并强调心智理论等认知能力在此过程中的核心作用。最后，我们探讨当前AI领域的前沿进展，指出开发具备社会具身性、能够自主引导其社会结构的集体人工智能所蕴含的潜在发展空间。