| Title | Migratable AI: Effect of identity and information migration on users' perception of conversational AI agents |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Tejwani, Ravi, Moreno, Felipe, Jeong, Sooyeon, Won Park, Hae, Breazeal, Cynthia |
| Conference Name | 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) |
| Date Published | aug |
| Keywords | conversational agents, Human Behavior, Metrics, pubcrawl, Scalability |
| Abstract | 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 validated the system by designing 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 highest trust, competence, likeability and social presence towards the conversational agent when both identity and information were migrated across embodiments. |
| DOI | 10.1109/RO-MAN47096.2020.9223436 |
| Citation Key | tejwani_migratable_2020 |
Migratable AI: Effect of identity and information migration on users' perception of conversational AI agents