Epistemology Goes AI: A Study Of GPT-3’s Capacity To Generate Consistent and Coherent Ordered Sets of Propositions on Single-Input-Multiple-Outputs Basis

Abstract

The more we rely on digital assistants, online search engines, and AI systems to revise our system of beliefs and increase our body of knowledge, the less we are able to resort to some independent criterion, unrelated to further digital tools, in order to asses the epistemic quality of the outputs delivered by digital systems. This raises some important questions to epistemology in general, and pressing question to applied to epistemology in particular. In this paper, we propose an experimental method for the assessment of GPT-3’s capacity to generate consistent and, as the case may be, coherent sets of outputs. While much attention has been given to GPT-3’s capacity to produce internally coherent individual outputs, we argue, instead, that more attention should be given to its capacity to produce consistent and coherent outputs generated on a single-input-multiple-outputs basis.

Keywords: Epistemology, Coherence, Consistency, AI (Artificial Intelligence), GPT-3; Truth