A sociotechnical systems approach for Artificial Intelligence

This topical collection aims to explore the application of a sociotechnical systems approach to Artificial Intelligence (AI), emphasizing the complex interplay between technical, social, and institutional dimensions that define the usage patterns and ethical concerns of AI systems. Unlike traditional systems, AI introduces artificial agents and technical rules that interact with human actors in dynamic and evolving environments, presenting challenges in predictability, understandability, and governance due to the systems' fuzzy and dynamic borders. This complexity necessitates a closer examination of the design, governance, and ethical implications inherent in AI systems, where the roles of human designers, system rules, values, and practice situations are critically analyzed. Consequently, our topical collection seeks to illuminate the significance of integrating technical, governance, and sociocultural elements in AI's design and operation. Contributions are encouraged to address how the sociotechnical systems approach can enhance AI's design and governance, the embedding of values within AI systems, the role of culture, transparent governance in dynamic settings, informed decision-making by developers and users, and the incorporation of value change. To this end, this topical collection invites a broad range of submissions that critically assess the sociotechnical systems approach to AI, aiming to provide an explication of and guidance on ethical issues and contribute to the informed development and use of AI systems in a rapidly evolving landscape.