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Active Inference: Applicability to Different Types of Social Organization Explained through Reference to Industrial Engineering and Quality Management

Year of publication

2021

Authors

Fox, Stephen

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.
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Organizations and authors

Publication type

Publication format

Article

Parent publication type

Journal

Article type

Original article

Audience

Scientific

Peer-reviewed

Peer-Reviewed

MINEDU's publication type classification code

A1 Journal article (refereed), original research

Publication channel information

Journal

Entropy

Volume

23

Issue

2

Article number

198

​Publication forum

55320

​Publication forum level

1

Open access

Open access in the publisher’s service

Yes

Open access of publication channel

Fully open publication channel

License of the publisher’s version

CC BY

Self-archived

No

Article processing fee (EUR)

1333

Year of payment for the open publication fee

2021

Other information

Fields of science

Media and communications

Keywords

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Language

English

International co-publication

No

Co-publication with a company

No

DOI

10.3390/e23020198

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes