XAI Desiderata for Trustworthy AI: Insights from the AI Act
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00387468" target="_blank" >RIV/68407700:21230/25:00387468 - isvavai.cz</a>
Result on the web
<a href="https://ceur-ws.org/Vol-4132/short12.pdf" target="_blank" >https://ceur-ws.org/Vol-4132/short12.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
XAI Desiderata for Trustworthy AI: Insights from the AI Act
Original language description
Explainable AI (XAI) is an actively growing field. When choosing a suitable XAI method, one can get overwhelmed by the number of existing approaches, their properties, and taxonomies. In this paper, we approach the problem of navigating the XAI landscape from a practical perspective of emerging regulatory needs. Particularly, the recently approved AI Act gives users of AI applications classified as “high-risk” the right to explanation. We propose a practical framework to navigate between these high-risk domains and the diverse perspectives of different explainees’ roles via six core XAI desiderata. The introduced desiderata can then be used by stakeholders with different backgrounds to make informed decisions about which explainability technique is more appropriate for their use case. By supporting context-sensitive assessment of explanation techniques, our framework contributes to the development of more trustworthy AI systems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of TRUST-AI 2025 – the European Workshop on Trustworthy AI
ISBN
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ISSN
1613-0073
e-ISSN
1613-0073
Number of pages
8
Pages from-to
180-187
Publisher name
CEUR Workshop Proceedings
Place of publication
Aachen
Event location
Bologna
Event date
Oct 25, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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