Algorithmic governance and social vulnerability: A value analysis of equality, freedom and trust

Research output: Working paperDiscussion paperScientificpeer-review

Abstract

Amidst the continuous development and implementation of emerging digital technologies across all spheres of life, the public governance sphere is no exception. However, as the instances of algorithmic governance implementation accumulate in a quest to increase efficiency and cut costs, so do the instances of mistakes and downright political scandals. Notably, most of these scandals concern socially vulnerable citizens, whether due to being disproportionally targeted by algorithmic governance, or due to biased algorithm outcomes known to deepen the existing historical inequalities. This chapter presents a value analysis of equality, freedom and trust using cautionary examples of algorithmic governance that threaten these values. The chapter uses experimentation as a conceptual lens to address the antecedents and consequences of the premature implementation of algorithmic governance targeting disproportionally socially vulnerable individuals and communities. The use of algorithmic governance before enough is known about the potential ill effects is tantamount to experimentation, and the potential harms from being targeted for testing such systems are disproportionately consequential for vulnerable populations, in economic and public value terms alike. The chapter concludes with a policy recommendation that strongly advises against the experimentation with algorithmic governance on vulnerable populations, because this deteriorates equality, freedom and trust – values that are already comparatively deprived among the socially vulnerable members of society. Therefore, as a moral obligation, social vulnerability should be considered a counterindication for nascent use of algorithmic governance, particularly in the shape it tends to take currently – that of surveillance and control.
Original languageEnglish
Pages1-16
Number of pages16
Publication statusSubmitted - 31 Jan 2024

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