This essay highlights a fundamental hesitation in the democratic space of contemporary societies and organizations. It focuses on the powerful role of the hemicycle and its right-left continuum in French practices of political representation. Over the last thirty years, this spatial commonality has obviously been challenged both in society and in organizations. And digital technologies have reinforced this trend. But what could be the alternative topology for democratic debates in legislative assemblies and organizational decision-making processes?
This article proposes a both re'exive and critical analysis of OpenJustice.be, a Belgian community that emerged in April 2020. !is community aimed to address the longstanding strugles with judicial modernization in Belgium, particularly the online access to law and justice. How did the OpenJustice.be initiative emerge and develop into a cognitive community, before suddenly fading away? To answer this question, the authors first depict the genesis of this citizen-led project, emphasizing the “openness discourse” and the open devices developed by this growing community. !e analysis then looks at the type of community formed by its members, before discussing the practical critique addressed by OpenJustice.be, and highlighting the fading away of the community. As the three co-authors of this article were also involved in the life of OpenJustice.be, this paper provides a grounded, re'exive, and critical analysis of a project driven by openness and digital commons.
This paper introduces the concept of "Explaining to AI" (X2AI) in the context of organizational and work environments, contrasting it with traditional "Explainable AI" (XAI). While XAI focuses on making AI systems transparent to human users, X2AI emphasizes the interactions where humans explain themselves to AI, specifically through representational practices of training, prompting, and feeding AI models. This shift highlights the political dimensions of representation and recognition within AI systems, stressing the need for AI to understand human contexts and identities. We discuss the implications of these representational practices for work and organizational studies, proposing future research avenues to address the sociotechnical dynamics of AI integration in workplaces in a way that goes beyond traditional emphases on transparency as an antidote to opacity.
