In this section
@inproceedings{Leofante:2024,
author = {Leofante, F and Ayoobi, H and Dejl, A and Freedman, G and Gorur, D and Jiang, J and Paulino, Passos G and Rago, A and Rapberger, A and Russo, F and Yin, X and Zhang, D and Toni, F},
publisher = {KR Organization},
title = {Contestable AI needs Computational Argumentation},
url = {http://hdl.handle.net/10044/1/114048},
year = {2024}
}
TY - CPAPER
AB - AI has become pervasive in recent years, but state-of-the-art approaches predominantly neglect the need for AI systems to be contestable. Instead, contestability is advocated by AI guidelines (e.g. by the OECD) and regulation of automated decision-making (e.g. GDPR). In this position paper we explore how contestability can be achieved computationally in and for AI. We argue that contestable AI requires dynamic (human-machine and/or machine-machine) explainability and decision-making processes, whereby machines can (i) interact with humans and/or other machines to progressively explain their outputs and/or their reasoning as well as assess grounds for contestation provided by these humans and/or other machines, and (ii) revise their decision-making processes to redress any issues successfully raised during contestation. Given that much of the current AI landscape is tailored to static AIs, the need to accommodate contestability will require a radical rethinking, that, we argue, computational argumentation is ideally suited to support.
AU - Leofante,F
AU - Ayoobi,H
AU - Dejl,A
AU - Freedman,G
AU - Gorur,D
AU - Jiang,J
AU - Paulino,Passos G
AU - Rago,A
AU - Rapberger,A
AU - Russo,F
AU - Yin,X
AU - Zhang,D
AU - Toni,F
PB - KR Organization
PY - 2024///
TI - Contestable AI needs Computational Argumentation
UR - http://hdl.handle.net/10044/1/114048
ER -
