Consensus between Epistemic Agents is Difficult

Damian Radosław Sowinski,1, ∗ Jonathan Carroll-Nellenback,2, † Jeremy DeSilva,1 Adam Frank,3 Gourab Ghoshal,3 Marcelo Gleiser,1 and Hari Seldon4 1Dartmouth College, Hanover NH 03755 2University of Rochester, Rochester NY 3University of Rochester, Rochester NY 14627 4Streeling University, Trantor (Dated: January 14, 2022) Abstract We introduce an epistemic information measure between two data streams, that we term influence. Closely related to transfer entropy, the measure must be estimated by epistemic agents with finite memory resources via sampling accessible data streams. We show that even under ideal conditions, epistemic agents using slightly different sampling strategies might not achieve consensus in their conclusions about which data stream is influencing which. As an illustration, we examine a real world data stream where different sampling strategies result in contradictory conclusions, explaining why some politically charged topics might exist due to purely epistemic reasons irrespective of the actual ontology of the world.