Dehumanization by algorithms raises important issues for business and society. Yet, these issues remain poorly understood due to the fragmented nature of the evolving dehumanization literature across disciplines, originating from colonialism, industrialization, post-colonialism studies, contemporary ethics, and technology studies. This article systematically reviews the literature on algorithms and dehumanization (n = 180 articles) and maps existing knowledge across several clusters that reveal its underlying characteristics. Based on the review, we find that algorithmic dehumanization is particularly problematic for human resource management (...) and the future of work, managerial decision-making, consumer ethics, hard- and soft-law regulation, and basic values, including privacy and consumer rights. From the literature synthesis, we also derive the following definition of algorithmic dehumanization: the act of using algorithms and data in a way that results in the intentional or unintentional treatment of individuals and/or groups as less than fully human, thereby violating human rights, including liberty, equality, and dignity. Ultimately, we present a dehumanization avoidance model that serves as a structured research agenda and practical guide to address the challenges raised by algorithmic dehumanization. Thus, the model indicates promising pathways for future research at the intersection of AI and society and facilitates reflection on organizational processes that support improving corporate capabilities and managerial decision-making to avoid algorithmic dehumanization. (shrink)

Research on the legitimacy of multi-stakeholder initiatives (MSIs) continues to thrive, however, the vague distinction between descriptive and normative legitimacy seems to cause growing confusion. In our paper, we identify three problems in the literature on MSI legitimacy: lack of precision regarding which of the two forms is used; blurring of boundaries between them; and ambiguity of assessment when assessing MSI legitimacy with the help of fine-grained criteria. These three problems, we argue, are not only detrimental to construct clarity but (...) they can also lead to an erosion of normativity, by which we mean the increasing lack of normative grounding or (unintentional) deconstruction of the normative elements of legitimacy. We introduce a framework that addresses these three problems, ultimately demonstrating how scholars can use the concept of MSI legitimacy in a manner that enhances construct clarity and avoids erosion of normativity. (shrink)