Who’s the Boss? Children Negotiate Robot Control across Role and Context
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3757279.3785548.pdf
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5.21 MB
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Author(s)
Pu, Isabella
Rogers, Kantwon
Dinh, Linh Dieu
Alghowinem, Sharifa
Breazeal, Cynthia
Date Issued
March 16, 2026
Publisher
ACM|Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction
Citation
Isabella Pu, Kantwon Rogers, Linh Dieu Dinh, Sharifa Alghowinem, and Cynthia Breazeal. 2026. Who’s the Boss? Children Negotiate Robot Control across Role and Context. In Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction (HRI '26). Association for Computing Machinery, New York, NY, USA, 395–405.
Version
Final published version
Abstract
Children regularly negotiate questions of authority and control in home and school life, but little is known about how they believe robots should fit into these dynamics. We conducted a 75-minute design session with 17 children (ages 6-9) to examine when robots should take, share, or defer control, and how expectations shift when robots are framed as teachers, classmates, or mentees. Children resisted robot control, particularly in adult-regulated domains and areas tied to personal skill or self-expression. They were more open to robot control in domains where they felt less competent, or where robots, perceived as less legitimate authorities than humans, could substitute for adult control. Role framing further shaped expectations: teacher robots were granted autonomy, classmate robots were expected to act as peers, and mentee robots were expected to defer. These findings show that children apply context- and role-sensitive rules when negotiating control with robots. We conclude with design considerations for robots in children's everyday lives that respect children's agency, calibrate autonomy by domain, and align behavior with children's context-sensitive expectations.
Description
HRI ’26, Edinburgh, Scotland, UK
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Massachusetts Institute of Technology. Personal Robots Group
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1145/3757279.3785548
