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

2026-07-11

AI Summary

This study addresses the challenges AI systems face regarding ethics, transparency, and adaptability by integrating Human-Centered AI (HCAI) guidelines with sociotechnical systems design principles to propose a sociotechnical heuristic framework for AI. The approach situates AI use contexts within sociotechnical analysis, emphasizing that transparency must be co-constituted through both technical mechanisms and human practices. It advocates for continuous system redesign under collaborative autonomy, revising and extending traditional sociotechnical heuristics to illuminate the dynamic interplay between human intervention and system evolution. This framework offers an innovative design pathway for developing AI systems that are simultaneously ethically responsive and adaptive.

Abstract

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.

Problem

• Human-centered AI
• Socio-technical systems
• AI transparency
• System adaptation
• Human oversight

Innovation

• Human-centered AI
• Socio-technical systems
• Transparency
• Continuous adaptation
• Collaborative autonomy