This introduction argues that the use of the concept of deliberative democracy in corporate social responsibility (CSR) research needs to be theoretically extended. We review three developments that have recently occurred in deliberative democracy theory within political science and philosophy: 1) the conceptualization of deliberative systems (macro level), 2) the considerations of mini-publics (micro level), and 3) the role of online deliberation. We discuss the challenges and prospects that incorporating these three developments into future CSR-related research creates. We thereby also introduce the articles in this special issue and show how they connect to each of the three developments. On the basis of this discussion, we outline the contours for a more general program of distributed deliberative CSR that enables CSR scholars to incorporate an updated understanding of deliberative democracy theory into their future work.

Responsible innovation in artificial intelligence (AI) calls for public deliberation: well-informed “deep democratic” debate that involves actors from the public, private, and civil society sectors in joint efforts to critically address the goals and means of AI. Adopting such an approach constitutes a challenge, however, due to the opacity of AI and strong knowledge boundaries between experts and citizens. This undermines trust in AI and undercuts key conditions for deliberation. We approach this challenge as a problem of situating the knowledge of actors from the AI industry within a deliberative system. We develop a new framework of responsibilities for AI innovation as well as a deliberative governance approach for enacting these responsibilities. In elucidating this approach, we show how actors from the AI industry can most effectively engage with experts and nonexperts in different social venues to facilitate well-informed judgments on opaque AI systems and thus effectuate their democratic governance.