Logic Programming and Machine Ethics
This work addresses the problem of building trustworthy ethical machines for applications in autonomous systems, but it is incremental as it builds on existing LP methods without introducing new paradigms.
The paper tackles the challenge of ensuring ethical behavior in autonomous agents by emphasizing the need for transparency and explainability beyond mere verification, proposing Logic Programming (LP) as a promising approach due to its human-comprehensible rules and ability to model causality.
Transparency is a key requirement for ethical machines. Verified ethical behavior is not enough to establish justified trust in autonomous intelligent agents: it needs to be supported by the ability to explain decisions. Logic Programming (LP) has a great potential for developing such perspective ethical systems, as in fact logic rules are easily comprehensible by humans. Furthermore, LP is able to model causality, which is crucial for ethical decision making.