XAI Desiderata for Trustworthy AI: Insights from the AI Act

Kód výsledku v 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>

Výsledek na webu

<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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Jazyk výsledku

angličtina

Název v původním jazyce

XAI Desiderata for Trustworthy AI: Insights from the AI Act

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

XAI Desiderata for Trustworthy AI: Insights from the AI Act

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of TRUST-AI 2025 – the European Workshop on Trustworthy AI

ISBN

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ISSN

1613-0073

e-ISSN

1613-0073

Počet stran výsledku

8

Strana od-do

180-187

Název nakladatele

CEUR Workshop Proceedings

Místo vydání

Aachen

Místo konání akce

Bologna

Datum konání akce

25. 10. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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