Nicholas Surdel
Papers
2
Total Citations
7
H-Index
2
About
Nicholas Surdel is a rising scholar at the intersection of social cognition and human-robot interaction. His research investigates how people form impressions of robots, specifically focusing on trait attribution and perceived competence. Surdel’s most cited work, “Judging robot ability: How people form implicit and explicit impressions of robot competence” (2024, 5 citations), presents a series of six studies involving over 2,600 participants who played a competitive game with a robot. This work reveals that humans spontaneously judge robot competence through both automatic (implicit) and deliberate (explicit) processes, mirroring how we evaluate human abilities. In his 2023 paper “Trait attribution explains human–robot interactions” (2 citations), Surdel offers a compelling counterargument to critiques of trait attribution models, demonstrating that these frameworks are both parsimonious and powerful for explaining how people anthropomorphize machines. His contributions are significant for the design of effective robotic systems, suggesting that engineers must consider not just what robots can do, but how their capabilities are perceived. As robots become more common in workplaces and homes, Surdel’s work provides crucial insights into the psychological foundations of human trust in autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Trait attribution explains human–robot interactions2 citations · 2023