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

arXiv: https://arxiv.org/abs/2607.10331 · HTML: https://mlsanity.com/paper/2607.10331/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 90 references that are in the map.
- First posted on arXiv 11 Jul 2026.

## Builds on (most cited first, 8 of 8)

- [Human-Centered Tools for Coping with Imperfect Algorithms during Medical Decision-Making](https://mlsanity.com/paper/1902.02960/) (2019)
- [Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation](https://mlsanity.com/paper/2305.02231/) (2023)
- [The future of human-AI collaboration: a taxonomy of design knowledge for hybrid intelligence systems](https://mlsanity.com/paper/2105.03354/) (2021)
- [Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imaging](https://mlsanity.com/paper/2205.09696/) (2022)
- [Toward General Design Principles for Generative AI Applications](https://mlsanity.com/paper/2301.05578/) (2023)
- [AI-Ethics by Design. Evaluating Public Perception on the Importance of Ethical Design Principles of AI](https://mlsanity.com/paper/2106.00326/) (2021)
- [Grasping AI: experiential exercises for designers](https://mlsanity.com/paper/2310.01282/) (2023)
- [When Generative AI Meets Workplace Learning: Creating A Realistic & Motivating Learning Experience With A Generative PCA](https://mlsanity.com/paper/2405.15561/) (2024)

## 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.