Accessing active inference theory through its implicit and deliberative practice in human organizations

Stephen Fox (Corresponding Author)

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Active inference theory (AIT) is a corollary of the free-energy principle, which formalizes cognition of living system’s autopoietic organization. AIT comprises specialist terminology and mathematics used in theoretical neurobiology. Yet, active inference is common practice in human organizations, such as private companies, public institutions, and not-for-profits. Active inference encompasses three interrelated types of actions, which are carried out to minimize uncertainty about how organizations will survive. The three types of action are updating work beliefs, shifting work attention, and/or changing how work is performed. Accordingly, an alternative starting point for grasping active inference, rather than trying to understand AIT specialist terminology and mathematics, is to reflect upon lived experience. In other words, grasping active inference through au-toethnographic research. In this short communication paper, accessing AIT through autoethnography is explained in terms of active inference in existing organizational practice (implicit active inference), new organizational methodologies that are informed by AIT (deliberative active inference), and combining implicit and deliberative active inference. In addition, these autoethnographic options for grasping AIT are related to generative learning.

Original languageEnglish
Article number1521
Number of pages10
JournalEntropy
Volume23
Issue number11
DOIs
Publication statusPublished - 15 Nov 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • Active inference
  • Autoethnography
  • Business models
  • Environment
  • Free energy principle
  • Gap analysis
  • Generative learning
  • Joint agent-environment systems
  • Process control
  • Radar charts
  • Survival
  • Variational free energy

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