Talking Back - human input and explanations to interactive AI systems

Alan Dix; Tommaso Turchi; Ben Wilson; Anna Monreale; Matt Roach

Talking Back - human input and explanations to interactive AI systems

Alan Dix, Tommaso Turchi, Ben Wilson, Anna Monreale, Matt Roach

Research output: Contribution to journal › Conference article › peer-review

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Abstract

While XAI focuses on providing AI explanations to humans, can the reverse - humans explaining their judgments to AI - foster richer, synergistic human-AI systems? This paper explores various forms of human inputs to AI and examines how human explanations can guide machine learning models toward automated judgments and explanations that align more closely with human concepts.

Original language	English
Pages (from-to)	30-43
Number of pages	14
Journal	CEUR Workshop Proceedings
Volume	3957
Publication status	Published - 24 Mar 2025
Event	Joint of the ACM Workshops at the International Conference on Intelligent User Interfaces 2025, IUI-WS 2025 - Cagliari, Italy Duration: 24 Mar 2025 → …

Keywords

adaptive interfaces
artificial intelligence
design
explainable AI
human-AI interaction
synergistic human-AI systems
user experience
user interface

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https://dblp.org/db/conf/iui/iui2025w.htmlLicence: CC BY

Cite this

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abstract = "While XAI focuses on providing AI explanations to humans, can the reverse - humans explaining their judgments to AI - foster richer, synergistic human-AI systems? This paper explores various forms of human inputs to AI and examines how human explanations can guide machine learning models toward automated judgments and explanations that align more closely with human concepts.",

keywords = "adaptive interfaces, artificial intelligence, design, explainable AI, human-AI interaction, synergistic human-AI systems, user experience, user interface",

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AU - Dix, Alan

AU - Turchi, Tommaso

AU - Wilson, Ben

AU - Monreale, Anna

AU - Roach, Matt

PY - 2025/3/24

Y1 - 2025/3/24

N2 - While XAI focuses on providing AI explanations to humans, can the reverse - humans explaining their judgments to AI - foster richer, synergistic human-AI systems? This paper explores various forms of human inputs to AI and examines how human explanations can guide machine learning models toward automated judgments and explanations that align more closely with human concepts.

AB - While XAI focuses on providing AI explanations to humans, can the reverse - humans explaining their judgments to AI - foster richer, synergistic human-AI systems? This paper explores various forms of human inputs to AI and examines how human explanations can guide machine learning models toward automated judgments and explanations that align more closely with human concepts.

KW - adaptive interfaces

KW - artificial intelligence

KW - design

KW - explainable AI

KW - human-AI interaction

KW - synergistic human-AI systems

KW - user experience

KW - user interface

UR - https://www.scopus.com/pages/publications/105005143130

M3 - Conference article

AN - SCOPUS:105005143130

SN - 1613-0073

VL - 3957

SP - 30

EP - 43

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - Joint of the ACM Workshops at the International Conference on Intelligent User Interfaces 2025, IUI-WS 2025

Y2 - 24 March 2025

ER -

Talking Back - human input and explanations to interactive AI systems

Abstract

Keywords

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