| Literature DB >> 33562847 |
Abstract
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.Entities:
Keywords: Markov blankets; active inference; artificial intelligence; industrial engineering; information-theoretic entropy; organization; prediction error; quality management; social; statistical process control; thermodynamic entropy; variational free energy
Year: 2021 PMID: 33562847 PMCID: PMC7916013 DOI: 10.3390/e23020198
Source DB: PubMed Journal: Entropy (Basel) ISSN: 1099-4300 Impact factor: 2.524