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Kai Spiekermann: Epistemic Network Injustice

Colloquium lecture organized by the Centre for Philosophy, Politics and Economics

To find out what is in one’s own best interest, it is helpful to ask one’s epistemic peers. However, identifying one’s epistemic peers is not a trivial task. I consider a stylized political setting, an electoral competition of ‘Masses’ and ‘Elites’. To succeed, the Masses need to know which alternative on offer is truly in their interest. To find out, the Masses can pool their privately held information in a pre-election ballot, provided that they can reliably find out with whom they should pool information.

I investigate the process of finding the relevant peer group for information pooling by modeling this group formation process as dynamic network change. The simulations show that the Masses can succeed in finding the right peers, but they also suggest reasons why the Elites may often be more successful. This phenomenon generalizes to the notion of epistemic network injustice. Such injustice arises when a subset of citizens is systematically deprived of connections to helpful epistemic peers, leading to their reduced political influence. Epistemic network injustice is a new form of epistemic injustice, related to but distinct from the notion introduced by Miranda Fricker.

Dr Kai Spiekermann is Associate Professor of Political Philosophy and the Doctoral Programme  Director in the Department of Government at the London School of Economics. Among his research  interests are normative and positive political theory, philosophy of the social sciences, social  epistemology and environmental change. He is particularly interested in applying formal methods,  computational simulations, and experiments to problems in political philosophy. His recent  publications have focused on mechanisms of norm avoidance, strategic ignorance and moral  knowledge, on information aggregation, jury theorems and epistemic democracy, and on reductionism  and holism in the social sciences.

Last modified:17 September 2020 5.27 p.m.