research-article

Towards FAIR Explainable AI: a standardized ontology for mapping XAI solutions to use cases, explanations, and AI systems

Authors:

Ajaya Adhikari,

Jasper van der Waa,

Cornelis Bouter,

Ioannis Tolios,

Stephan RaaijmakersAuthors Info & Claims

PETRA '22: Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments

Pages 562 - 568

https://doi.org/10.1145/3529190.3535693

Published: 11 July 2022 Publication History

PETRA '22: Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments

Towards FAIR Explainable AI: a standardized ontology for mapping XAI solutions to use cases, explanations, and AI systems

Pages 562 - 568

Abstract
References

Abstract

Several useful taxonomies have been published that survey the eXplainable AI (XAI) research field. However, these taxonomies typically do not show the relation between XAI solutions and several use case aspects, such as the explanation goal or the task context. In order to better connect the field of XAI research with concrete use cases and user needs, we designed the ASCENT (Ai System use Case Explanation oNTology) framework, which is a new ontology and corresponding metadata standard with three complementary modules for different aspects of an XAI solution: one for aspects of AI systems, another for use case aspects, and yet another for explanation properties. The descriptions of XAI solutions in this framework include whether the XAI solution has a positive, negative, inconclusive or unresearched relation with use case elements. Descriptions in ASCENT thus emphasize the (user) evaluation of XAI solutions in order to support finding validated practices for application in industry, as well as being helpful for identifying research gaps. Describing XAI solutions according to the proposed common metadata standard is an important step towards the FAIR (Findable, Accessible, Interoperable, Reusable) usage of XAI solutions.

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Recki LLawo DKrauß VPins DBoden A(2024)"You Can either Blame Technology or Blame a Person..." --- A Conceptual Model of Users' AI-Risk Perception as a Tool for HCIProceedings of the ACM on Human-Computer Interaction10.1145/36869968:CSCW2(1-25)Online publication date: 8-Nov-2024
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Tsiakas KMurray-Rust D(2024)Unpacking Human-AI interactions: From Interaction Primitives to a Design SpaceACM Transactions on Interactive Intelligent Systems10.1145/366452214:3(1-51)Online publication date: 8-Jun-2024
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Towards FAIR Explainable AI: a standardized ontology for mapping XAI solutions to use cases, explanations, and AI systems

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PETRA '22: Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments

June 2022

704 pages

ISBN:9781450396318

DOI:10.1145/3529190

Conference Chair:
Fillia Makedon

Copyright © 2022 ACM.

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Published: 11 July 2022

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PETRA '22

PETRA '22: The15th International Conference on PErvasive Technologies Related to Assistive Environments

June 29 - July 1, 2022

Corfu, Greece

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Cited By

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https://doi.org/10.1109/OJCOMS.2025.3534626
Recki LLawo DKrauß VPins DBoden A(2024)"You Can either Blame Technology or Blame a Person..." --- A Conceptual Model of Users' AI-Risk Perception as a Tool for HCIProceedings of the ACM on Human-Computer Interaction10.1145/36869968:CSCW2(1-25)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3686996
Tsiakas KMurray-Rust D(2024)Unpacking Human-AI interactions: From Interaction Primitives to a Design SpaceACM Transactions on Interactive Intelligent Systems10.1145/366452214:3(1-51)Online publication date: 8-Jun-2024
https://dl.acm.org/doi/10.1145/3664522
Pawar UO'Shea DO'Reilly RCostello MBeder C(2024)Optimal Neighborhood Contexts in Explainable AI: An Explanandum-Based EvaluationIEEE Open Journal of the Computer Society10.1109/OJCS.2024.33897815(181-194)Online publication date: 2024
https://doi.org/10.1109/OJCS.2024.3389781
Tsolakis NMaga-Nteve CVrochidis SBassiliades NMeditskos G(2024)Enhancing Cardiac AI Explainability Through Ontology-Based Evaluation2024 15th International Conference on Information, Intelligence, Systems & Applications (IISA)10.1109/IISA62523.2024.10786663(1-4)Online publication date: 17-Jul-2024
https://doi.org/10.1109/IISA62523.2024.10786663
Stathis Gvan den Herik J(2024)Ethical and preventive legal technologyAI and Ethics10.1007/s43681-023-00413-2Online publication date: 18-Mar-2024
https://doi.org/10.1007/s43681-023-00413-2
Recki LKroth KKrauß VKlöckner LPakusch CBossauer PBöhm LPeters FStöbitsch ABoden A(2024)Digitale VerantwortungVerbraucherinformatik10.1007/978-3-662-68706-2_5(203-260)Online publication date: 25-Mar-2024
https://doi.org/10.1007/978-3-662-68706-2_5

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