Towards an Ethical Robot: Internal Models, Consequences and Ethical Action Selection
By Alan Frank Thomas Winfield, Christian Blum, Wenguo Liu. 2014
149 citations recorded by the source corpus.
If robots are to be trusted, especially when interacting with humans, then they will need to be more than just safe. This paper explores the potential of robots capable of modelling and therefore predicting the consequences of both their own actions, and the actions of other dynamic actors in their environment. We show that with the addition of an ‘ethical’ action selection mechanism a robot can sometimes choose actions that compromise its own safety in order to prevent a second robot from coming to harm. An implementation with e-puck mobile robots provides a proof of principle by showing that a simple robot can, in real time, model and act upon the consequences of both its own and another robot’s actions. We argue that this work moves us towards robots that are ethical, as well as safe.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Social Psychology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Stuart J. Russell
- Max Tegmark
- Dan Dewey
- Vaishak Belle
- Albert Bifet
- Stuart Armstrong
- Leandro L. Minku
In Computer Vision and Pattern Recognition
In Social Psychology
Citations in the corpus
- Research Priorities for Robust and Beneficial Artificial Intelligence (2015, background): “Work in adaptive control theory [31], the theory of so-called cyberphysical systems [32], and verification of hybrid or robotic systems [33, 34] is highly relevant but also faces the same difficulties.”