What Does Explainable AI Really Mean? A New Conceptualization of Perspectives
Artificial Intelligence
2017-10-03 v1
Abstract
We characterize three notions of explainable AI that cut across research fields: opaque systems that offer no insight into its algo- rithmic mechanisms; interpretable systems where users can mathemat- ically analyze its algorithmic mechanisms; and comprehensible systems that emit symbols enabling user-driven explanations of how a conclusion is reached. The paper is motivated by a corpus analysis of NIPS, ACL, COGSCI, and ICCV/ECCV paper titles showing differences in how work on explainable AI is positioned in various fields. We close by introducing a fourth notion: truly explainable systems, where automated reasoning is central to output crafted explanations without requiring human post processing as final step of the generative process.
Keywords
Cite
@article{arxiv.1710.00794,
title = {What Does Explainable AI Really Mean? A New Conceptualization of Perspectives},
author = {Derek Doran and Sarah Schulz and Tarek R. Besold},
journal= {arXiv preprint arXiv:1710.00794},
year = {2017}
}