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Leveraging explanations in interactive machine learning: An overview

Teso, Stefano ; Alkan, Öznur ; Stammer, Wolfgang ; Daly, Elizabeth (2023)
Leveraging explanations in interactive machine learning: An overview.
In: Frontiers in Artificial Intelligence, 2023, 6
doi: 10.26083/tuprints-00023357
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Leveraging explanations in interactive machine learning: An overview
Language: English
Date: 11 April 2023
Place of Publication: Darmstadt
Year of primary publication: 2023
Publisher: Frontiers Media S.A.
Journal or Publication Title: Frontiers in Artificial Intelligence
Volume of the journal: 6
Collation: 19 Seiten
DOI: 10.26083/tuprints-00023357
Corresponding Links:
Origin: Secondary publication DeepGreen

Explanations have gained an increasing level of interest in the AI and Machine Learning (ML) communities in order to improve model transparency and allow users to form a mental model of a trained ML model. However, explanations can go beyond this one way communication as a mechanism to elicit user control, because once users understand, they can then provide feedback. The goal of this paper is to present an overview of research where explanations are combined with interactive capabilities as a mean to learn new models from scratch and to edit and debug existing ones. To this end, we draw a conceptual map of the state-of-the-art, grouping relevant approaches based on their intended purpose and on how they structure the interaction, highlighting similarities and differences between them. We also discuss open research issues and outline possible directions forward, with the hope of spurring further research on this blooming research topic.

Uncontrolled Keywords: human-in-the-loop, explainable AI, interactive machine learning, model debugging, model editing
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-233575
Classification DDC: 000 Generalities, computers, information > 004 Computer science
Divisions: 20 Department of Computer Science > Artificial Intelligence and Machine Learning
Date Deposited: 11 Apr 2023 11:57
Last Modified: 14 Nov 2023 19:05
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/23357
PPN: 509032710
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