When neuro-robots go wrong: A review

Neuro-robots are a class of autonomous machines that, in their architecture, mimic aspects of the human brain and cognition. As such, they represent unique artifacts created by humans based on human understanding of healthy human brains. European Union's Convention on Roboethics 2025 states tha...

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Bibliographic Details
Published in:Frontiers in neurorobotics 2023-02, Vol.17, p.1112839-1112839
Main Authors: Khan, Muhammad Salar, Olds, James L
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Automation
Brain
Cognition
Decision making
Design
Ethics
explainability
explainable AI (X-AI)
explainable neuro-robots
neuro-robotic failures
neuro-robotic models
neuro-robotic systems
Neuroscience
Neurosciences
Robotics
Robots
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Summary:Neuro-robots are a class of autonomous machines that, in their architecture, mimic aspects of the human brain and cognition. As such, they represent unique artifacts created by humans based on human understanding of healthy human brains. European Union's Convention on Roboethics 2025 states that the design of all robots (including neuro-robots) must include provisions for the complete traceability of the robots' actions, analogous to an aircraft's flight data recorder. At the same time, one can anticipate rising instances of neuro-robotic failure, as they operate on imperfect data in real environments, and the underlying AI behind such neuro-robots has yet to achieve explainability. This paper reviews the trajectory of the technology used in neuro-robots and accompanying failures. The failures demand an explanation. While drawing on existing explainable AI research, we argue explainability in AI limits the same in neuro-robots. In order to make robots more explainable, we suggest potential pathways for future research.
ISSN:1662-5218
1662-5218
DOI:10.3389/fnbot.2023.1112839