Experiential AI: Between arts and explainable AI

Drew Hemment; Dave Murray-Rust; Vaishak Belle; Ruth Aylett; Matjaz Vidmar; Frank Broz

doi:10.1162/leon_a_02524

Experiential AI: Between arts and explainable AI

Drew Hemment^*, Dave Murray-Rust, Vaishak Belle, Ruth Aylett, Matjaz Vidmar, Frank Broz

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

Experiential artificial intelligence (AI) is an approach to the design, use, and evaluation of AI in cultural or other real-world settings that foregrounds human experience and context. It combines arts and engineering to support rich and intuitive modes of model interpretation and interaction, making AI tangible and explicit. The ambition is to enable significant cultural works and make AI systems more understandable to nonexperts, thereby strengthening the basis for responsible deployment. This paper discusses limitations and promising directions in explainable AI, contributions the arts offer to enhance and go beyond explainability, and methodology to support, deepen, and extend those contributions.

Original language	English
Pages (from-to)	298-306
Number of pages	9
Journal	Leonardo
Volume	57
Issue number	3
Early online date	2 Apr 2024
DOIs	https://doi.org/10.1162/leon_a_02524
Publication status	E-pub ahead of print - 2 Apr 2024

Access to Document

10.1162/leon_a_02524

Hemment2024LeonardoExperientialAI
The text in this accepted manuscript is made available under a Creative Commons Attribution 4.0 International (CC BY 4.0) licence. The images, where an author is indicated, are All Rights Reserved, and cannot be reproduced, distributed or adapted without permission of the copyrightholder. Any further images are made available on the same basis as the text.
Accepted author manuscript, 7.85 MBLicence: Creative Commons: Attribution (CC-BY)
Hemment_mergedFinal published version, 632 KBLicence: All Rights Reserved

The New Real – Trust and acceptance in networked, online experiences to enable and support post-COVID19 recovery
Speed, C. (Principal Investigator), Hemment, D. (Co-investigator) & Luger, E. (Co-investigator)
AHRC
1/01/21 → 31/10/22
Project: Research

Cite this

@article{8653837aa60b466fac979eaf5c771c4c,

title = "Experiential AI: Between arts and explainable AI",

abstract = "Experiential artificial intelligence (AI) is an approach to the design, use, and evaluation of AI in cultural or other real-world settings that foregrounds human experience and context. It combines arts and engineering to support rich and intuitive modes of model interpretation and interaction, making AI tangible and explicit. The ambition is to enable significant cultural works and make AI systems more understandable to nonexperts, thereby strengthening the basis for responsible deployment. This paper discusses limitations and promising directions in explainable AI, contributions the arts offer to enhance and go beyond explainability, and methodology to support, deepen, and extend those contributions.",

author = "Drew Hemment and Dave Murray-Rust and Vaishak Belle and Ruth Aylett and Matjaz Vidmar and Frank Broz",

year = "2024",

month = apr,

day = "2",

doi = "10.1162/leon_a_02524",

language = "English",

volume = "57",

pages = "298--306",

journal = "Leonardo",

issn = "0024-094X",

publisher = "MIT Press",

number = "3",

}

TY - JOUR

T1 - Experiential AI

T2 - Between arts and explainable AI

AU - Hemment, Drew

AU - Murray-Rust, Dave

AU - Belle, Vaishak

AU - Aylett, Ruth

AU - Vidmar, Matjaz

AU - Broz, Frank

PY - 2024/4/2

Y1 - 2024/4/2

N2 - Experiential artificial intelligence (AI) is an approach to the design, use, and evaluation of AI in cultural or other real-world settings that foregrounds human experience and context. It combines arts and engineering to support rich and intuitive modes of model interpretation and interaction, making AI tangible and explicit. The ambition is to enable significant cultural works and make AI systems more understandable to nonexperts, thereby strengthening the basis for responsible deployment. This paper discusses limitations and promising directions in explainable AI, contributions the arts offer to enhance and go beyond explainability, and methodology to support, deepen, and extend those contributions.

AB - Experiential artificial intelligence (AI) is an approach to the design, use, and evaluation of AI in cultural or other real-world settings that foregrounds human experience and context. It combines arts and engineering to support rich and intuitive modes of model interpretation and interaction, making AI tangible and explicit. The ambition is to enable significant cultural works and make AI systems more understandable to nonexperts, thereby strengthening the basis for responsible deployment. This paper discusses limitations and promising directions in explainable AI, contributions the arts offer to enhance and go beyond explainability, and methodology to support, deepen, and extend those contributions.

U2 - 10.1162/leon_a_02524

DO - 10.1162/leon_a_02524

M3 - Article

SN - 0024-094X

VL - 57

SP - 298

EP - 306

JO - Leonardo

JF - Leonardo

IS - 3

ER -

Experiential AI: Between arts and explainable AI

Abstract

Access to Document

Fingerprint

Projects

The New Real – Trust and acceptance in networked, online experiences to enable and support post-COVID19 recovery

Cite this