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Explaining Artificial Intelligence with Tailored Interactive Visualisations

Authors:

Katrien VerbertAuthors Info & Claims

IUI '22 Companion: Companion Proceedings of the 27th International Conference on Intelligent User Interfaces

Pages 120 - 123

https://doi.org/10.1145/3490100.3516481

Published: 22 March 2022 Publication History

Abstract

Artificial intelligence (AI) is becoming ubiquitous in the lives of both researchers and non-researchers, but AI models often lack transparency. To make well-informed and trustworthy decisions based on these models, people require explanations that indicate how to interpret the model outcomes. This paper presents our ongoing research in explainable AI, which investigates how visual analytics interfaces and visual explanations, tailored to the target audience and application domain, can make AI models more transparent and allow interactive steering based on domain expertise. First, we present our research questions and methods, contextualised by related work at the intersection of AI, human-computer interaction, and information visualisation. Then, we discuss our work so far in healthcare, agriculture, and education. Finally, we share our research ideas for additional studies in these domains.

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Cited By

Mehrotra SDegachi CVereschak OJonker CTielman M(2024)A Systematic Review on Fostering Appropriate Trust in Human-AI Interaction: Trends, Opportunities and ChallengesACM Journal on Responsible Computing10.1145/36964491:4(1-45)Online publication date: 21-Sep-2024
https://dl.acm.org/doi/10.1145/3696449
Bhattacharya AOoge JStiglic GVerbert K(2023)Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If ExplorationsProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584075(204-219)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3581641.3584075
Deters HDroste JFechner MKlünder J(2023)Explanations on Demand - a Technique for Eliciting the Actual Need for Explanations2023 IEEE 31st International Requirements Engineering Conference Workshops (REW)10.1109/REW57809.2023.00065(345-351)Online publication date: Sep-2023
https://doi.org/10.1109/REW57809.2023.00065
Show More Cited By

Index Terms

Explaining Artificial Intelligence with Tailored Interactive Visualisations
1. Human-centered computing
  1. Human computer interaction (HCI)

Index terms have been assigned to the content through auto-classification.

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IUI '22 Companion: Companion Proceedings of the 27th International Conference on Intelligent User Interfaces

March 2022

142 pages

ISBN:9781450391450

DOI:10.1145/3490100

Copyright © 2022 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Published: 22 March 2022

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IUI '22: 27th International Conference on Intelligent User Interfaces

March 22 - 25, 2022

Helsinki, Finland

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

Mehrotra SDegachi CVereschak OJonker CTielman M(2024)A Systematic Review on Fostering Appropriate Trust in Human-AI Interaction: Trends, Opportunities and ChallengesACM Journal on Responsible Computing10.1145/36964491:4(1-45)Online publication date: 21-Sep-2024
https://dl.acm.org/doi/10.1145/3696449
Bhattacharya AOoge JStiglic GVerbert K(2023)Directive Explanations for Monitoring the Risk of Diabetes Onset: Introducing Directive Data-Centric Explanations and Combinations to Support What-If ExplorationsProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584075(204-219)Online publication date: 27-Mar-2023
https://dl.acm.org/doi/10.1145/3581641.3584075
Deters HDroste JFechner MKlünder J(2023)Explanations on Demand - a Technique for Eliciting the Actual Need for Explanations2023 IEEE 31st International Requirements Engineering Conference Workshops (REW)10.1109/REW57809.2023.00065(345-351)Online publication date: Sep-2023
https://doi.org/10.1109/REW57809.2023.00065
Ali SAkhlaq FImran AKastrati ZDaudpota SMoosa M(2023)The enlightening role of explainable artificial intelligence in medical & healthcare domains: A systematic literature reviewComputers in Biology and Medicine10.1016/j.compbiomed.2023.107555166(107555)Online publication date: Nov-2023
https://doi.org/10.1016/j.compbiomed.2023.107555
Cabitza FCampagner ARonzio LCameli MMandoli GPastore MSconfienza LFolgado DBarandas MGamboa H(2023)Rams, hounds and white boxesArtificial Intelligence in Medicine10.1016/j.artmed.2023.102506138:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.artmed.2023.102506
Yang WWei YWei HChen YHuang GLi XLi RYao NWang XGu XAmin MKang B(2023)Survey on Explainable AI: From Approaches, Limitations and Applications AspectsHuman-Centric Intelligent Systems10.1007/s44230-023-00038-y3:3(161-188)Online publication date: 10-Aug-2023
https://doi.org/10.1007/s44230-023-00038-y

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