Matthew J. Scalia
Papers
1
Total Citations
7
H-Index
1
About
Matthew J. Scalia investigates the psychological foundations of human-robot interaction, with a particular focus on trust dynamics in collaborative teams. His research bridges dispositional, perceptual, and behavioral dimensions of trust, revealing how individual differences shape human responses to robotic teammates. In his highly cited 2023 work, Scalia demonstrated that anthropomorphism—the tendency to attribute human-like qualities to robots—moderates the relationships between these trust components. This finding has significant implications for designing more effective human-robot teams (HRTs), as it suggests that perceived humanness can either enhance or complicate trust-building depending on context. With 7 citations to date, this paper has quickly become a reference point for scholars studying trust calibration in autonomous systems. Scalia’s contributions are particularly valuable for students and researchers in human-robot interaction, social robotics, and team cognition, offering a nuanced framework for understanding how people come to trust—or distrust—their non-human collaborators.
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