Fox Stephen
VTT Technical Research Centre of Finland, VTT, FI-02044 Espoo, Finland.
Entropy (Basel). 2021 Feb 5;23(2):198. doi: 10.3390/e23020198.
Active inference is a physics of life process theory of perception, action and learning that is applicable to natural and artificial agents. In this paper, active inference theory is related to different types of practice in social organization. Here, the term social organization is used to clarify that this paper does not encompass organization in biological systems. Rather, the paper addresses active inference in social organization that utilizes industrial engineering, quality management, and artificial intelligence alongside human intelligence. Social organization referred to in this paper can be in private companies, public institutions, other for-profit or not-for-profit organizations, and any combination of them. The relevance of active inference theory is explained in terms of variational free energy, prediction errors, generative models, and Markov blankets. Active inference theory is most relevant to the social organization of work that is highly repetitive. By contrast, there are more challenges involved in applying active inference theory for social organization of less repetitive endeavors such as one-of-a-kind projects. These challenges need to be addressed in order for active inference to provide a unifying framework for different types of social organization employing human and artificial intelligence.
主动推理是一种适用于自然和人工主体的关于感知、行动和学习的生命过程物理学理论。在本文中,主动推理理论与社会组织中的不同类型实践相关。这里,使用“社会组织”一词是为了明确本文不涵盖生物系统中的组织。相反,本文探讨的是社会组织中的主动推理,它将工业工程、质量管理以及人工智能与人类智能结合起来运用。本文所提及的社会组织可以存在于私营公司、公共机构、其他营利性或非营利性组织,以及它们的任何组合之中。主动推理理论的相关性是根据变分自由能、预测误差、生成模型和马尔可夫毯来解释的。主动推理理论与高度重复性的工作社会组织最为相关。相比之下,将主动推理理论应用于重复性较低的工作社会组织(如一次性项目)则涉及更多挑战。为了使主动推理为采用人类和人工智能的不同类型社会组织提供一个统一框架,需要应对这些挑战。