UC San Diego

Facial actions are key elements of non-verbal behavior. Perceivers' reactions to others' facial expressions often represent a match or mirroring (e.g., they smile to a smile). However, the information conveyed by an expression depends on context. Thus, when shown by an opponent, a smile conveys bad news and evokes frowning. The availability of anthropomorphic agents capable of facial actions raises the question of how people respond to such agents in social context. We explored this issue in a study where participants played a strategic game with or against a facially expressive android. Electromyography (EMG) recorded participants' reactions over zygomaticus muscle (smiling) and corrugator muscle (frowning). We found that participants' facial responses to android's expressions reflect their informational value, rather than a direct match. Overall, participants smiled more, and frowned less, when winning than losing. Critically, participants' responses to the game outcome were similar regardless of whether it was conveyed via the android's smile or frown. Furthermore, the outcome had greater impact on people's facial reactions when it was conveyed through android's face than a computer screen. These findings demonstrate that facial actions of artificial agents impact human facial responding. They also suggest a sophistication in human-robot communication that highlights the signaling value of facial expressions.