Organizational Practices and Socio-Technical Design of Human-Centered AI

Fuente: arXiv
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Main Author: Herrmann, Thomas
Format: Preprint
Published: 2026
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author Herrmann, Thomas
author_facet Herrmann, Thomas
contents This contribution explores how the integration of Artificial Intelligence (AI) into organizational practices can be effectively framed through a socio-technical perspective to comply with the requirements of Human-centered AI (HCAI). Instead of viewing AI merely as a technical tool, the analysis emphasizes the importance of embedding AI into communication, collaboration, and decision-making processes within organizations from a human-centered perspective. Ten case-based patterns illustrate how AI support of predictive maintenance can be organized to address quality assurance and continuous improvement and to provide different types of sup-port for HCAI. The analysis shows that AI adoption often requires and enables new forms of organizational learning, where specialists jointly interpret AI output, adapt workflows, and refine rules for system improve-ment. Different dimensions and levels of socio-technical integration of AI are considered to reflect the effort and benefits of keeping the organization in the loop.
format Preprint
id arxiv_https___arxiv_org_abs_2601_21492
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Organizational Practices and Socio-Technical Design of Human-Centered AI
Herrmann, Thomas
Human-Computer Interaction
This contribution explores how the integration of Artificial Intelligence (AI) into organizational practices can be effectively framed through a socio-technical perspective to comply with the requirements of Human-centered AI (HCAI). Instead of viewing AI merely as a technical tool, the analysis emphasizes the importance of embedding AI into communication, collaboration, and decision-making processes within organizations from a human-centered perspective. Ten case-based patterns illustrate how AI support of predictive maintenance can be organized to address quality assurance and continuous improvement and to provide different types of sup-port for HCAI. The analysis shows that AI adoption often requires and enables new forms of organizational learning, where specialists jointly interpret AI output, adapt workflows, and refine rules for system improve-ment. Different dimensions and levels of socio-technical integration of AI are considered to reflect the effort and benefits of keeping the organization in the loop.
title Organizational Practices and Socio-Technical Design of Human-Centered AI
topic Human-Computer Interaction
url https://arxiv.org/abs/2601.21492