Artificial intelligence and communication: A Human–Machine Communication research agenda - Andrea L Guzman, Seth C Lewis,

For more than 70 years, the study of artificial intelligence (AI) and the study of communication have proceeded along separate trajectories. Research regarding AI has focused on how to reproduce aspects of human intelligence, including the ability to communicate, within the machine (Frankish and Ramsey, 2014). In contrast, communication historically has been conceptualized as foremost a human process (e.g. Schramm, 1972), with research within the discipline as a whole focused on how people exchange messages with one another and the implications thereof (see Craig, 1999). Today, this gulf between AI and communication research is narrowing, bridged by AI technologies designed to function as communicators. Recent advances in AI have led to more powerful and consequential AI technologies being integrated across daily life (Campolo et al., 2017). Individuals routinely chat with Amazon's Alexa, Apple's Siri, and other digital assistants (Pew Research Center, 2017), with people's interactions with smart devices expected to grow along with the emerging Internet of Things (Rainie and Anderson, 2017). Within industry, media providers such as the Associated Press are using AI-enabled technologies in the production and distribution of news (Marconi et al., 2017). In response, some communication scholars are advocating for the discipline to devote greater attention to understanding increasingly life-like and communicative AI technologies, people's interactions with them, and their implications (e.g. However, communication researchers studying communicative AI face a substantial hurdle: AI and people's interactions with it do not fit neatly into paradigms of communication theory that for more than a century formed around how people communicate with other people (Gunkel, 2012a).