  For AI technology to fulfill its full promises, we must have effective means
to ensure Responsible AI behavior and curtail potential irresponsible use,
e.g., in areas of privacy protection, human autonomy, robustness, and
prevention of biases and discrimination in automated decision making. Recent
literature in the field has identified serious shortcomings of narrow
technology focused and formalism-oriented research and has proposed an
interdisciplinary approach that brings the social context into the scope of
study. In this paper, we take a sociotechnical approach to propose a more
expansive framework of thinking about the Responsible AI challenges in both
technical and social context. Effective solutions need to bridge the gap
between 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 of
intervention and propose a decentralized computational infrastructure, or a set
of public utilities, as the computational means to bridge this gap. A
decentralized infrastructure is uniquely suited for meeting this challenge and
enable technical solutions and social institutions in a mutually reinforcing
dynamic to achieve Responsible AI goals. Our approach is novel in its
sociotechnical approach and its aim in tackling the structural issues that
cannot be solved within the narrow confines of AI technical research. We then
explore possible features of the proposed infrastructure and discuss how it may
help solve example problems recently studied in the field.
