Stephen S. Killingsworth

Papers

Total Citations

H-Index

About

Stephen S. Killingsworth investigates how people conceptualize the minds of humans, computers, and robots—a core question in cognitive science and AI ethics. His research reveals that adults apply fundamentally different intuitive frameworks to mechanical versus human agents: people assume machines rely on location- and feature-based behaviors, while humans engage in goal- and category-based reasoning. This foundational work, including his most-cited paper “Tests of Concepts About Different Kinds of Minds” (34 citations), demonstrates that our predictions about machine behavior are shaped by deep-seated, distinct concepts about the nature of intelligence. His 2008 study (20 citations) further established that these conceptual differences are systematic and robust, influencing how we interpret and anticipate the actions of computers, robots, and people. By mapping these intuitive distinctions, Killingsworth’s contributions are vital for designing more predictable human-AI interactions and for understanding public perceptions of autonomous systems. His work is essential reading for anyone exploring the psychology of artificial intelligence, human-robot interaction, or the philosophy of mind.