Robot Mindreading and the Problem of Trust
Andrés Páez
- Year
- 2020
- Access
- Open access
Abstract
This paper raises three questions regarding the attribution of beliefs, desires, and intentions to robots. The first one is whether humans in fact engage in robot mindreading. If they do, this raises a second question: does robot mindreading foster trust towards robots? Both of these questions are empirical, and I show that the available evidence is insufficient to answer them. Now, if we assume that the answer to both questions is affirmative, a third and more important question arises: should developers and engineers promote robot mindreading in view of their stated goal of enhancing transparency? My worry here is that by attempting to make robots more mind-readable, they are abandoning the project of understanding automatic decision processes. Features that enhance mind-readability are prone to make the factors that determine automatic decisions even more opaque than they already are. And current strategies to eliminate opacity do not enhance mind-readability. The last part of the paper discusses different ways to analyze this apparent trade-off and suggests that a possible solution must adopt tolerable degrees of opacity that depend on pragmatic factors connected to the level of trust required for the intended uses of the robot.
Keywords
Related papers
A dual-loop framework for manufacturability-aware topology optimization of electric vehicle structures via wire arc additive manufacturing
Qiang Cui, Chuan Yu, Daoqian Yang +2 more
Robotics and Computer-Integrated Manufacturing · 2026
Geometric digital twin: A digital and intelligent model for aero-engine assembly accuracy prediction
Ke Shang, Xin Jin, Teli Xu +4 more
Robotics and Computer-Integrated Manufacturing · 2026
Revolutionizing Industries Through AI-Driven Robotics
Aryan Chaudhary
Recent Advances in Computer Science and Communications · 2026
Design and dynamic performance prediction of a novel large-aperture offset-feed deployable antenna
Chuang Shi, Tianming Liu, Ning Xue +6 more
Aerospace Science and Technology · 2026