Explanation of black box AI for GDPR related privacy using Isabelle

Conference paper

Kammueller, F. 2022. Explanation of black box AI for GDPR related privacy using Isabelle. Garcia-Alfaro, J., Navarro-Arribas, G. and Dragoni, N. (ed.) 17th DPM International Workshop on Data Privacy Management. Copenhagen, Denmark 29 - 30 Sep 2022 Cham Springer. https://doi.org/10.1007/978-3-031-25734-6_5
TypeConference paper
TitleExplanation of black box AI for GDPR related privacy using Isabelle
AuthorsKammueller, F.
Abstract

In this paper, we present a methodology for constructing explanations for AI classification algorithms. The methodology consists of constructing a model of the context of the application in the Isabelle Infrastructure framework (IIIf) and an algorithm that allows to extract a precise logical rule that specifies the behaviour of the black box algorithm thus allowing to explain it. The explanation is given within the rich logical model of the IIIf. It is thus suitable for human audiences. We illustrate this and validate the methodology on the application example of credit card scoring with special relation to the right of explanation as given by the GDPR.

Middlesex University ThemeSustainability
Conference17th DPM International Workshop on Data Privacy Management
Proceedings TitleData Privacy Management, Cryptocurrencies and Blockchain Technology: ESORICS 2022 International Workshops, DPM 2022 and CBT 2022, Copenhagen, Denmark, September 26–30, 2022, Revised Selected Papers
SeriesLecture Notes in Computer Science
EditorsGarcia-Alfaro, J., Navarro-Arribas, G. and Dragoni, N.
ISSN0302-9743
Electronic1611-3349
ISBN
Paperback9783031257339
Electronic9783031257346
PublisherSpringer
Place of publicationCham
Publication dates
Online23 Feb 2023
Print24 Feb 2023
Publication process dates
Accepted01 Sep 2022
Deposited30 Sep 2022
Output statusPublished
Accepted author manuscript
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-031-25734-6_5
Web address (URL) of conference proceedingshttps://doi.org/10.1007/978-3-031-25734-6
LanguageEnglish
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