A Survey on Methods and Metrics for the Assessment of Explainability Under the Proposed AI Act
Additional information
Authors
Sovrano F.,
Sapienza S.,
Palmirani M.,
Vitali F.
Type
Article in conference proceedings
Year
2021
Language
English
Abstract
This study discusses the interplay between metrics used to measure the explainability of the AI systems and the proposed EU Artificial Intelligence Act. A standardisation process is ongoing: several entities (e.g. ISO) and scholars are discussing how to design systems that are compliant with the forthcoming Act and explainability metrics play a significant role. This study identifies the requirements that such a metric should possess to ease compliance with the AI Act. It does so according to an interdisciplinary approach, i.e. by departing from the philosophical concept of explainability and discussing some metrics proposed by scholars and standardisation entities through the lenses of the explainability obligations set by the proposed AI Act. Our analysis proposes that metrics to measure the kind of explainability endorsed by the proposed AI Act shall be risk-focused, model-agnostic, goal-aware, intelligible & accessible. This is why we discuss the extent to which these requirements are met by the metrics currently under discussion.
Conference proceedings
JURIX'2021
Meeting name
JURIX 2021: The Thirty-fourth Annual Conference,
Meeting place
Vilnius, Lithuania
Meeting date
8–10 December 2021
ISSN
0922-6389, 1879-8314
Diffusion
License
License undefined
Visibility
Private
