HMN 2026: How The human gaze speaks to children, who remain insensitive to the gaze of humanoid robots

Very young children (even as young as 3 years old) can read intention and preferences in the eyes of a person, but they do not recognize this type of nonverbal communication in the gaze of a humanoid robot.

This is the finding of a study published in the International Journal of Child-Computer Interaction, coordinated by Antonella Marchetti, Director of the Department of Psychology of Università Cattolica and CERITOM (Research Center on Theory of Mind and Social Competences Across the Lifespan), in collaboration with scholars from Tokyo and Osaka, and colleagues Davide Massaro, Cinzia Di Dio, and Federico Manzi of the Università Cattolica of Milan.

The research involved Italian children ages 3 to 5 years old to explore how people and robots’ gaze can evoke different impressions in children’s minds.

The test consisted of showing to children a person and a humanoid robot while looking at an object, assessing whether they could understand which object was “preferred” by the agent looking at it.

The results show that children interpret the human gaze as a meaningful signal: if an individual looks at an object, children tend to assume that the person likes that object. The same does not happen, however, when a humanoid robot is looking at the object. In that case, the gaze is not enough for children to attribute a true preference to the robot.

In short, children use the human gaze to “read” desires and intentions, while they struggle to do the same with the robot. Furthermore, gaze—human or robotic—does not seem to change children’s personal preferences: it helps them understand what the other person likes, but it does not necessarily change their own preferences.

Professor Marchetti explains, “This does not mean robots cannot play an educational or social role. However, it suggests that simply imitating a single human signal, such as gaze, in a robotic artifact is not enough to make it truly communicative in a child’s eyes. Designing robots and intelligent technologies for children requires richer, more natural, and developmentally appropriate interactions: made up of words, gestures, reciprocity, context, and shared presence. This is reinforced by the fact that even human interactions alone are not sufficient to exert clear transformative effects on children’s preferences. These data are particularly relevant in the debate on artificial intelligence.”

“Many AIs today speak, respond, and make suggestions, but our results highlight that, especially for children, communication is not just about words: presence and shared context also matter. From this perspective, an AI integrated into physical systems—so-called embodied AI, one of the most complete expressions of which is humanoid social robotics—represents a crucial dimension for understanding how children attribute mental states (e.g., intentions, beliefs, preferences) to technologies as well,” she adds.

These findings also have significant implications for applications, particularly in the field of autistic spectrum disorder, where gaze and shared attention represent crucial psychological dimensions of socio-communicative development and can be particularly vulnerable. In this context, humanoid robots are increasingly being studied as support tools for rehabilitation interventions focused on these skills. Understanding how a child interprets a robot’s gaze as an intentional signal can therefore help design more targeted, natural, and developmentally sensitive interventions.

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