XAI for U 2025: 2$nd$ International Workshop on Explainable AI for Ubiquitous, Pervasive and Wearable Computing

The workshop XAI for U aims to address the critical need for transparency in Artificial Intelligence (AI) systems that are increasingly integrated into our daily lives through mobile systems, wearables, and smart environments. Despite rapid advances in AI and machine learning, many of these systems remain opaque, making it difficult for users, designers, developers, and stakeholders to verify their reliability, fairness, and correctness. This lack of transparency can hinder trust, informed decision-making, and broader adoption. This workshop focuses on the pressing need to enable Explainable AI (XAI) tools tailored for ubiquitous, pervasive, and wearable computing, and highlights the unique challenges associated with this domain, such as generating explanations for time-series and multimodal data, interpreting interconnected machine learning components, and delivering user-centered explanations. It aims to foster interdisciplinary collaboration among researchers across related domains, share recent advancements, address open challenges, and propose future research directions to improve the development and applicability of XAI in ubiquitous, pervasive, and wearable computing. Ultimately, the workshop seeks to enhance user trust, understanding, interaction, and adoption, ensuring that AI-driven solutions are not only more explainable but also better aligned with ethical standards and user expectations.

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Publication Details

Published
2025-10-12
DOI
https://doi.org/10.1145/3714394.3750557
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
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article

XAI for U 2025: 2$nd$ International Workshop on Explainable AI for Ubiquitous, Pervasive and Wearable Computing

Mandani Ntekouli, Sang Won Bae, Teena Hassan, Martin Gjoreski et al.
Explainable Artificial Intelligence (XAI)
article

XAI for U 2025: 2$nd$ International Workshop on Explainable AI for Ubiquitous, Pervasive and Wearable Computing

Mandani Ntekouli, Sang Won Bae, Teena Hassan, Martin Gjoreski, Mor Vered
article en

Abstract

The workshop XAI for U aims to address the critical need for transparency in Artificial Intelligence (AI) systems that are increasingly integrated into our daily lives through mobile systems, wearables, and smart environments. Despite rapid advances in AI and machine learning, many of these systems remain opaque, making it difficult for users, designers, developers, and stakeholders to verify their reliability, fairness, and correctness. This lack of transparency can hinder trust, informed decision-making, and broader adoption. This workshop focuses on the pressing need to enable Explainable AI (XAI) tools tailored for ubiquitous, pervasive, and wearable computing, and highlights the unique challenges associated with this domain, such as generating explanations for time-series and multimodal data, interpreting interconnected machine learning components, and delivering user-centered explanations. It aims to foster interdisciplinary collaboration among researchers across related domains, share recent advancements, address open challenges, and propose future research directions to improve the development and applicability of XAI in ubiquitous, pervasive, and wearable computing. Ultimately, the workshop seeks to enhance user trust, understanding, interaction, and adoption, ensuring that AI-driven solutions are not only more explainable but also better aligned with ethical standards and user expectations.

Stevens Institute of Technology (US), Hochschule Bonn-Rhein-Sieg (DE), Maastricht University (NL), Monash University (AU), Università della Svizzera italiana (CH)
Peace, Justice and strong institutions
Openalex Percentile: Top 18%
Explainable Artificial Intelligence (XAI)
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