This article addresses the influence of algorithms on social communication. The central problem is the increasing attribution of human and institutional meaning to non-human digital forms, such as social networks, games, virtual assistants and chatbots, which influence our way of dealing with contingencies during communication. The objective of this article is, based on the effects of the transformation of contingency conditions in social communication, to analyze how algorithmic forms influence our communicative interactions. I employ a conceptual analysis based on Niklas Luhmann’s theory of social systems and Elena Esposito’s approach to artificial communication, examining the problem with the concepts of communication, attribution, meaning and contingency. This article criticizes the concept of “techno-animism” mainly because this approach does not adequately consider that these interactions with intelligent machines result from the advanced production of goods, commodifying human attention and interaction. The result of the discussion indicates that algorithmic forms produce an asymmetry in social communication, on the one hand using large amounts of data (never used by any agency, human or otherwise), at the same time as they lack a differentiated understanding of human behavior. This change alters the dynamics of learning and consequent social interaction, leading to a state in which coping with contingency is increasingly mediated by algorithms instead of representing a constant decisive element for the development of social organization.