Fitting Humor: Age-Based Personalization for Shaping Relatable Child-Robot Interactions

Abstract

In this paper, we present a participatory design approach to age-based personalization for child-robot interaction. This is an important step towards social robots being effective across age groups. As a testbed for our approach, we used humor. Personalized humor is a powerful social motivator and is uniquely suited to build relatable and sustained child-robot interactions. Through a series of co-design workshops (n = 102 children), we identified humor concepts that fit the specific sense of humor for each of the four age groups (8–9, 9–10, 10–11, 11–12 y.o.), as well as humor concepts that resonated across these age groups. A user study showed that, overall, children found the interaction more amusing and a better fit for both their own sense of humor and that of their peer group when the robot used age-personalized humor compared to age-agnostic humor. The strength of the effects varied by age group, with the oldest group consistently scoring lower on the outcome measures, indicating that the design was not equally effective for all groups.