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For AI technology to fulfill its full promises, we must have effective meansto ensure Responsible AI behavior and curtail potential irresponsible use,e.g., in areas of privacy protection, human autonomy, robustness, andprevention of biases and discrimination in automated decision making. Recentliterature in the field has identified serious shortcomings of narrowtechnology focused and formalism-oriented research and has proposed aninterdisciplinary approach that brings the social context into the scope ofstudy. In this paper, we take a sociotechnical approach to propose a moreexpansive framework of thinking about the Responsible AI challenges in bothtechnical and social context. Effective solutions need to bridge the gapbetween a technical system with the social system that it will be deployed to.To this end, we propose human agency and regulation as main mechanisms ofintervention and propose a decentralized computational infrastructure, or a setof public utilities, as the computational means to bridge this gap. Adecentralized infrastructure is uniquely suited for meeting this challenge andenable technical solutions and social institutions in a mutually reinforcingdynamic to achieve Responsible AI goals. Our approach is novel in itssociotechnical approach and its aim in tackling the structural issues thatcannot be solved within the narrow confines of AI technical research. We thenexplore possible features of the proposed infrastructure and discuss how it mayhelp solve example problems recently studied in the field.

A Decentralized Approach towards Responsible AI in Social Ecosystems