Developing a scale for human-likeness perceptions of conversational technologies

Abstract

Conversational technologies are often implementing social or conversational cues. While these cues are used to mimic human behavior and make conversational agents appear as human-like as possible, consumers’ perceptions of the human-likeness of conversational technologies from a communication science perspective are not yet fully understood. To address this shortcoming, in this project we develop a field-specific conceptualization of human-likeness of conversational technologies, and develop a reliable and valid multidimensional measure based on existing theories and related scales