Two Challenges for CI Trustworthiness and How to Address Them
Abstract
We argue that, to be trustworthy, Computational Intelligence (CI) has to do what it is entrusted to do for permissible reasons and to be able to give rationalizing explanations of its behavior which are accurate and graspable. We support this claim by drawing parallels with trustworthy human persons, and we show what difference this makes in a hypothetical CI hiring system. Finally, we point out two challenges for trustworthy CI and sketch a mechanism which could be used to generate sufficiently accurate as well as graspable rationalizing explanations for CI behavior.
Type
Publication
Proceedings of the 1st Workshop on Explainable Computational Intelligence (XCI 2017). Explainable Computational Intelligence Workshop (XCI-2017), located at INLG 2017, September 4, Santiago de Compostela, Spain
Cite
@inproceedings{baumTwoChallengesForCI2017,
author = {Kevin Baum and Maximilian Köhl and Eva Schmidt},
booktitle = {Proceedings of the 1st Workshop on Explainable Computational Intelligence (XCI 2017). Explainable Computational Intelligence Workshop (XCI-2017), located at INLG 2017, September 4, Santiago de Compostela, Spain},
doi = {10.18653/v1/W17-3701},
editor = {M. Pereira-Fariña and C. Reed},
month = {9},
publisher = {Association for Computational Linguistics},
title = {Two Challenges for CI Trustworthiness and How to Address Them},
url = {https://www.dfki.de/fileadmin/user_upload/import/16852_W17-3701.pdf},
year = {2017}
}