Conversational hyperconvergence: an onlife evolution model for conversational AI agency

Abstract

The following document explores a framework for extending the Onlife concept to a specific set of agency interactions: Conversational AI. The aim of this paper is to present a model to advance the study of CHC, to become cognizant of its consequences, and to comprehend the direction society is heading, the means by which it is doing so, and the potential rate at which it will progress. Starting with the introduction of the Conlife concept, which signifies the seamless and indistinguishable fusion of Conversational AI and Human Agency in Life, the document proceeds to explore the concept of Conversational HyperConvergence (CHC), offering initial insights and considering potential implications. The Conversational HyperConvergence Breakeven Point is delineated and assessed across various conversational scopes, including different channels (such as video, voice, chat, SMS, email), topics (for example, booking inquiries, financial information), and levels of query complexity. A replicable model is introduced, primarily focused on average time measurements for recognizing a human or artificial agent. These measurements are conducted using simulations with various AI tools in different interaction scenarios between a human agent and a customer care provider. The author contends that a thorough analysis of these subjects, coupled with their dissemination within the community, will foster increased awareness among current and future generations about the possible ethical and societal repercussions of the technologies in question.