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Maintaining Coherence in Explainable AI: Strategies for Consistency Across Time and Interaction

Alan Dix Orcid Logo, Tommaso Turchi Orcid Logo, Ben Wilson Orcid Logo, Alessio Malizia Orcid Logo, Anna Monreale Orcid Logo, Matt Roach Orcid Logo

SYNERGY 2025 – Designing and Building Hybrid Human–AI Systems

Swansea University Authors: Ben Wilson Orcid Logo, Matt Roach Orcid Logo

Abstract

Can we create explanations of artificial intelligence and machine learning that have some level of consistency over time as we might expect of a human explanation? This paper explores this issue, and offers several strategies for either maintaining a level of consistency or highlighting when and why...

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Published in: SYNERGY 2025 – Designing and Building Hybrid Human–AI Systems
Published: CEUR-WS.org 2025
Online Access: https://ceur-ws.org/Vol-4074/short9-5.pdf
URI: https://cronfa.swan.ac.uk/Record/cronfa71398
first_indexed 2026-02-10T13:11:25Z
last_indexed 2026-02-11T05:34:01Z
id cronfa71398
recordtype SURis
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spelling 2026-02-10T13:11:23.2237667 v2 71398 2026-02-10 Maintaining Coherence in Explainable AI: Strategies for Consistency Across Time and Interaction a854728f3952ca0b74a49f9286a9b0e2 0009-0004-5663-5854 Ben Wilson Ben Wilson true false 9722c301d5bbdc96e967cdc629290fec 0000-0002-1486-5537 Matt Roach Matt Roach true false 2026-02-10 MACS Can we create explanations of artificial intelligence and machine learning that have some level of consistency over time as we might expect of a human explanation? This paper explores this issue, and offers several strategies for either maintaining a level of consistency or highlighting when and why past explanations might appear inconsistent with current decisions. Conference Paper/Proceeding/Abstract SYNERGY 2025 – Designing and Building Hybrid Human–AI Systems CEUR-WS.org human-AI interaction, explainable AI, synergistic human-AI systems, user interface, artificial intelligence, design, adaptive interfaces, user experience 16 6 2025 2025-06-16 https://ceur-ws.org/Vol-4074/short9-5.pdf COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University Not Required Tango Project EU Grant Agreement no. 101120763 - TANGO 2026-02-10T13:11:23.2237667 2026-02-10T12:56:53.9026773 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Alan Dix 0000-0002-5242-7693 1 Tommaso Turchi 0000-0001-6826-9688 2 Ben Wilson 0009-0004-5663-5854 3 Alessio Malizia 0000-0002-2601-7009 4 Anna Monreale 0000-0001-8541-0284 5 Matt Roach 0000-0002-1486-5537 6
title Maintaining Coherence in Explainable AI: Strategies for Consistency Across Time and Interaction
spellingShingle Maintaining Coherence in Explainable AI: Strategies for Consistency Across Time and Interaction
Ben Wilson
Matt Roach
title_short Maintaining Coherence in Explainable AI: Strategies for Consistency Across Time and Interaction
title_full Maintaining Coherence in Explainable AI: Strategies for Consistency Across Time and Interaction
title_fullStr Maintaining Coherence in Explainable AI: Strategies for Consistency Across Time and Interaction
title_full_unstemmed Maintaining Coherence in Explainable AI: Strategies for Consistency Across Time and Interaction
title_sort Maintaining Coherence in Explainable AI: Strategies for Consistency Across Time and Interaction
author_id_str_mv a854728f3952ca0b74a49f9286a9b0e2
9722c301d5bbdc96e967cdc629290fec
author_id_fullname_str_mv a854728f3952ca0b74a49f9286a9b0e2_***_Ben Wilson
9722c301d5bbdc96e967cdc629290fec_***_Matt Roach
author Ben Wilson
Matt Roach
author2 Alan Dix
Tommaso Turchi
Ben Wilson
Alessio Malizia
Anna Monreale
Matt Roach
format Conference Paper/Proceeding/Abstract
container_title SYNERGY 2025 – Designing and Building Hybrid Human–AI Systems
publishDate 2025
institution Swansea University
publisher CEUR-WS.org
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
url https://ceur-ws.org/Vol-4074/short9-5.pdf
document_store_str 0
active_str 0
description Can we create explanations of artificial intelligence and machine learning that have some level of consistency over time as we might expect of a human explanation? This paper explores this issue, and offers several strategies for either maintaining a level of consistency or highlighting when and why past explanations might appear inconsistent with current decisions.
published_date 2025-06-16T05:35:22Z
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score 11.096068

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