The Commodification of Attention, Distrust & Resentment: a Threat to (Rawlsian) Justice

Abstract

There is a growing body of scholarship on how AI technology can undermine democratic institutions. I present a novel contribution to this literature, by accounting for how and why recommendation algorithms for engagement optimisation undermine the necessary conditions for Rawlsian justice. For Rawls’s political theory, the ability to form bonds of trust with fellow citizens is a necessary condition for citizens to develop their sense of justice; and their sense of justice is a necessary condition for the attainment of justice. Recommendation algorithms amplify the space given to hateful, violent, extremist, false, and discriminatory content, I argue. This content undermines the development of mutual trust between citizens necessary for a sense of justice. If citizens can only trust their like-minded members and have a distrust of their fellow citizens, then the possibility for Rawlsian reciprocity in liberal society to be realised is not possible. Without reciprocity, liberal political systems will be inherently unstable, as citizens would not have formed the adequate affectionate ties needed for mutual cooperation, which is a precondition for a just society.