Algorithmic Personalized Wages

Abstract

This article explores algorithmically created personalized wages: what they are, what they mean, and what we can do about them. First, it establishes a taxonomy of five different forms of algorithmic wage differentiation: productivity-based wage adjustments, wages shifted through incentive bonuses and demerits, behavioral wages, dynamic wages, and wages shifted to conduct an experiment. It argues that these techniques are likely to spread from gig work to the formal employment context. Second, it argues that the spread of these techniques has democratic implications. They will increase economic and racial inequality. They will harm labor solidarity. Perhaps most importantly, they put workers in a profoundly humiliating position in relationship to their boss, one where speech and autonomy are discouraged because they can lead to lowered pay. Finally, it argues that we should understand these developments as innovations in power and domination and use old antimonopoly strategies as ways to limit the democratic downsides of these tools. We should explore bans or limits on first-degree labor pricing discrimination and enhanced antitrust enforcement.