Hussain Kazmi

Papers

Total Citations

H-Index

About

Hussain Kazmi is an emerging researcher at the intersection of human-robot interaction and social robotics, with a focus on how people assign moral and punitive judgments to autonomous systems. His most-cited work, "Teaching Robots a Lesson: Determinants of Robot Punishment" (2019, 40 citations), explores the psychological and contextual factors that drive humans to punish robots for perceived transgressions—a novel contribution that bridges ethics, cognitive science, and robotics. This study has been foundational in understanding how social norms extend to non-human agents, influencing debates on robot rights and accountability. Kazmi’s research challenges conventional views of human-robot relationships, revealing that people often treat robots as moral actors, even when they lack intent. His work has been cited in fields ranging from AI ethics to experimental psychology, and he is recognized for pioneering experimental paradigms that quantify human responses to robotic misbehavior. With growing interest in how society integrates intelligent machines, Kazmi’s insights are increasingly vital for designing fairer, more socially aware autonomous systems.