The prediction of non-ergodic humanity by artificial intelligence

Abstract This article aims to affirm and instantiate the main accounts showing intrinsic limitations of artificial intelligence computing in a real world of organisms, people and speech. It is argued that these limits mainly concern non-ergodic (or non-repeating) phenomena. This paper aims to extend the debate on the limits of AI through a preliminary examination of the dispersion of both regularities and non-ergodic phenomena and processes in both society and human persons. It is argued that regularities and non-ergodic processes are deeply intertwined. Social regularity, for example from the built environment and conformity, is discussed. In society, non-ergodicity is especially found in the lifeworld of speech and intersubjectivity. The human person creates non-ergodicity through numerous routes. Individual regularities are seen in things such as habit and routine. This study asserts that human intersubjective life in the often nonergodic lifeworld and inbuilt non-repeating dimensions of an individual’s living out of the world, should be recognized as extensive areas where AI prediction will be weak. It is hypothesized that the intensity of non-ergodicity in phenomena is a firm indicator of weak AI prediction, and that most successful AI prediction of social phenomena predominantly reflects the sort of social regularities discussed in this article.