ABSTRACT:
Algorithmic governance is not enough on its own to manage and protect the interests of multiple stakeholders. Therefore, platforms are increasingly seeking to involve stakeholders in their algorithmic governance, synthesizing the domains of algorithmic governance and stakeholder governance. We denote this synthesis as algorithmic stakeholder governance. In this paper, we examine algorithmic stakeholder governance in the context of content platforms focusing on the algorithmically mediated interactions among three key stakeholders—creators, consumers, and advertisers. We explore this topic by conducting an in-depth study of the YouTube platform. Using grounded theory techniques, we generate a model that explains the process by which platform stakeholder interactions are algorithmically governed to address key stakeholder conflicts related to free speech, information diversity, and content safety. Our model suggests that algorithmic stakeholder governance provides a forum for resolving these stakeholder conflicts and theorizes the interplay between the platform’s approach to algorithmic stakeholder governance and stakeholder participation. Our research contributes primarily to the literature on platform governance and algorithmic governance on platforms more specifically, by shifting the focus from centralized control and viewing users as objects of governance towards a more decentralized and balanced perspective where platform users are viewed as active stakeholders.
Key words and phrases: Algorithmic stakeholder governance, platform governance, algorithmic governance, stakeholder governance, case study, grounded theory, online platforms, content platforms