@inproceedings{8c7c651ebe9e42f9a1ba572d514623f7,
title = "Human Centered Approaches and Taxonomies for Explainable Artificial Intelligence",
abstract = "Recent interest within the research community related to explainable artificial intelligence (XAI) has led to a profuse amount of literature on the subject. Those who wish to tackle the domain from an HCI focus may be presented with overwhelming material, most of which does not pertain to human aspects of XAI. Taxonomies can serve to categorize a subject into topic areas and distill content into an overview of the field. This late breaking work intends to help those within the HCI community with a focus on XAI to understand relevant aspects of human centered XAI. We also present a taxonomy which can be used when categorizing real world XAI to identify gaps in XAI methods and predict future areas of research. Lastly, we introduce a novel aspect, practical XAI evaluation methods from a human centered perspective allowing for more effective evaluation of the AI – human interaction.",
keywords = "Explainable Artificial Intelligence, Human Centered Explainable Artificial Intelligence, Taxonomies",
author = "Helen Sheridan and Emma Murphy and Dympna O{\textquoteright}Sullivan",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 26th International Conference on Human-Computer Interaction, HCII 2024 ; Conference date: 29-06-2024 Through 04-07-2024",
year = "2024",
doi = "10.1007/978-3-031-76827-9\_9",
language = "English",
isbn = "9783031768262",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "144--163",
editor = "Helmut Degen and Stavroula Ntoa",
booktitle = "HCI International 2024 – Late Breaking Papers - 26th International Conference on Human-Computer Interaction, HCII 2024, Proceedings",
address = "Germany",
}