Migratable AI: Effect of identity and information migration on users' perception of conversational AI agents
| Autor: | Ravi Tejwani, Felipe Moreno, Cynthia Breazeal, Hae Won Park, Sooyeon Jeong |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology media_common.quotation_subject Computer Science - Human-Computer Interaction Identity (social science) 02 engineering and technology computer.software_genre 050105 experimental psychology Task (project management) Human-Computer Interaction (cs.HC) Computer Science - Computers and Society Computer Science - Robotics 020901 industrial engineering & automation Human–computer interaction AI effect Perception Computers and Society (cs.CY) 0501 psychology and cognitive sciences Dialog system Competence (human resources) media_common 05 social sciences User perception Psychology computer Robotics (cs.RO) |
| Zdroj: | MIT web domain RO-MAN |
| Popis: | Conversational AI agents are proliferating, embodying a range of devices such as smart speakers, smart displays, robots, cars, and more. We can envision a future where a personal conversational agent could migrate across different form factors and environments to always accompany and assist its user to support a far more continuous, personalized, and collaborative experience. This opens the question of what properties of a conversational AI agent migrates across forms, and how it would impact user perception. To explore this, we developed a Migratable AI system where a user's information and/or the agent's identity can be preserved as it migrates across form factors to help its user with a task. We designed a 2x2 between-subjects study to explore the effects of information migration and identity migration on user perceptions of trust, competence, likeability, and social presence. Our results suggest that identity migration had a positive effect on trust, competence, and social presence, while information migration had a positive effect on trust, competence, and likeability. Overall, users report the highest trust, competence, likeability, and social presence towards the conversational agent when both identity and information were migrated across embodiments. Accepted to RO-MAN 2020 |
| Databáze: | OpenAIRE |
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