Abstract
User-centered design practices are used to develop the social interaction characteristics of intelligent personal assistants and social robots. In this approach, developers establish characteristics favored by the majority of users. However, catering to target users may negate the benefits in user experience and use intention achieved from matching a product’s characteristics to the preferences of individual users. The present study examines differences between target versus individual user based approaches to user-centered design. Specifically, a framework is presented on how to develop a product to meet individual user preferences. Results show that individual user preferences, while similar to the target user preferences, can vary significantly from the baseline. Machine learning and artificial intelligence approaches should be employed to help adjust social interaction approaches from a baseline to individual user preferences.
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