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Comparing Socio-technical Design Principles with Guidelines for Human-centered AI

arXiv 2607.10331 ↗First posted 11 Jul 2026cs.AI cs.CYcited by 0

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Abstract (arXiv)

Human-centered AI (HCAI) refers to guidelines or principles that aim on ethi-cally oriented design of systems. We compare HCAI- guidelines with princi-ples of socio-technical systems that emerged in the context of conventional in-formation technology. The comparison leads to a revision of socio-technical heuristics by including aspects of AI-usage. The comparison reveals that con-tinuous evolution is a basic characteristic of socio-technical systems, and that human oversight or interventions and the subsequent appropriation of AI-systems lead to continuous adaptation and re-design of the systems, if autono-my is collaboratively exercised. From a socio-technical point of view, the cru-cial requirement of transparency has not only to be fulfilled with technical fea-tures, but also by contributions of the whole system including human actors. It will be promising for using AI, if not only technical features, but organization-al and social practices are socio-technically designed in a way that compen-sates shortcomings of AI.

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8 of 90 references.

References · 8

  1. 2019Human-Centered Tools for Coping with Imperfect Algorithms during Medical Decision-Makingcited by 109
  2. 2023Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulationcited by 60
  3. 2021The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systemscited by 39
  4. 2022Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imagingcited by 32
  5. 2023Toward General Design Principles for Generative AI Applicationscited by 20
  6. 2021AI-Ethics by Design. Evaluating Public Perception on the Importance of Ethical Design Principles of AIcited by 6
  7. 2023Grasping AI: experiential exercises for designerscited by 3
  8. 2024When Generative AI Meets Workplace Learning: Creating A Realistic & Motivating Learning Experience With A Generative PCAcited by 2

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