Abstract
In human-machine communication, people interact with a communication partner that is of a different ontological nature from themselves. This study examines how people conceptualize ontological differences between humans and computers and the implications of these differences for human-machine communication. Findings based on data from qualitative interviews with 73 U.S. adults regarding disembodied artificial intelligence (AI) technologies (voice-based AI assistants, automated-writing software) show that people differentiate between humans and computers based on origin of being, degree of autonomy, status as tool/tool-user, level of intelligence, emotional capabilities, and inherent flaws. In addition, these ontological boundaries are becoming increasingly blurred as technologies emulate more human-like qualities, such as emotion. This study also demonstrates how people's conceptualizations of the human-computer divide inform aspects of their interactions with communicative technologies.
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Guzman, A. L. (2020). Ontological Boundaries Between Humans and Computers and the Implications for Human-Machine Communication. Human-Machine Communication, 1(1), 37–54. https://doi.org/10.30658/hmc.1.3
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