"Managing dehumanization? A technology and ethics account on the future of work and consumption"

by Schultz, Mario; Clegg, Melanie; Hofstetter, Reto; Seele, Peter (2022)

Abstract

Literature on dehumanization by algorithms has grown substantially in recent years, making it a highly important topic also for a managerial and business ethics audience as it touches upon several interlinked ethical issues in the business and society nexus. However, scattering across di-verse disciplines makes algorithmic dehumanization challenging to approach. It stretches from his-torical terminological roots from colonialism, industrialization and post-colonialism and today is deeply rooted in technology studies and ethics. We review the literature on algorithms and dehu-manization (n=180 articles) and map existing knowledge across several clusters that reveal its under-lying characteristics. Based on the review, we derive a business-ethics informed definition: Algo-rithmic dehumanization is defined as: organizational actors integrating algorithms and data analytics that result in the intentional or unintentional treatment of individuals and/or groups as less than fully human, thus infringe on human rights and particularly the three foundational principles of liberty, equality and dignity. We find that algorithmic dehumanization applies particularly to employees and the future of work, managerial decision making, consumer ethics, hard- and soft-law regulation and basic values such as privacy or human rights of consumers. Further, from the review, we develop a dehumanization avoidance model, which may help researchers and business practitioners to deal with the ethical challenges raised by algorithmic dehumanization. The three stages of the model show that several research topics remain unaddressed so far. Unraveling these topics, we suggest a set of open questions and how future research and practice can build on the model to reflect about organizational processes and improve corporate capabilities and managerial decision-making to avoid algorithmic dehumanization, thus contributing to outline the emerging concept of Corporate Digital Responsibility.

Links to Reference

• http://dx.doi.org/10.5465/ambpp.2022.11392abstract

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