AI or Human? Understanding Perceptions of Embodied Robots with LLMs
Lavinia Hriscu, Alberto Sanfeliu, Anais Garrell

TL;DR
This study explores how people perceive intelligence in embodied robots by testing whether they can distinguish between AI- and human-controlled robots during interactive tasks, revealing challenges in differentiating artificial from human intelligence.
Contribution
It introduces a novel Turing Test within a robotic platform to evaluate perceptions of intelligence in embodied robots, highlighting key factors influencing human judgments.
Findings
Participants could not reliably distinguish AI from human control.
Perception of intelligence was influenced by robot behavior and interaction context.
Results inform future design of interactive robots and AI assessment methods.
Abstract
The pursuit of artificial intelligence has long been associated to the the challenge of effectively measuring intelligence. Even if the Turing Test was introduced as a means of assessing a system intelligence, its relevance and application within the field of human-robot interaction remain largely underexplored. This study investigates the perception of intelligence in embodied robots by performing a Turing Test within a robotic platform. A total of 34 participants were tasked with distinguishing between AI- and human-operated robots while engaging in two interactive tasks: an information retrieval and a package handover. These tasks assessed the robot perception and navigation abilities under both static and dynamic conditions. Results indicate that participants were unable to reliably differentiate between AI- and human-controlled robots beyond chance levels. Furthermore, analysis of…
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Taxonomy
TopicsReinforcement Learning in Robotics · Ethics and Social Impacts of AI · Modular Robots and Swarm Intelligence
