Agency and legibility for artists through Experiential AI

• URL: http://arxiv.org/abs/2306.02327v1
• Date: Sun, 4 Jun 2023 11:00:07 GMT
• Title: Agency and legibility for artists through Experiential AI
• Authors: Drew Hemment, Matjaz Vidmar, Daga Panas, Dave Murray-Rust, Vaishak Belle and Aylett Ruth
• Abstract summary: Experiential AI is an emerging research field that addresses the challenge of making AI tangible and explicit. We report on an empirical case study of an experiential AI system designed for creative data exploration. We discuss how experiential AI can increase legibility and agency for artists.
• Score: 12.941266914933454
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Experiential AI is an emerging research field that addresses the challenge of making AI tangible and explicit, both to fuel cultural experiences for audiences, and to make AI systems more accessible to human understanding. The central theme is how artists, scientists and other interdisciplinary actors can come together to understand and communicate the functionality of AI, ML and intelligent robots, their limitations, and consequences, through informative and compelling experiences. It provides an approach and methodology for the arts and tangible experiences to mediate between impenetrable computer code and human understanding, making not just AI systems but also their values and implications more transparent, and therefore accountable. In this paper, we report on an empirical case study of an experiential AI system designed for creative data exploration of a user-defined dimension, to enable creators to gain more creative control over the AI process. We discuss how experiential AI can increase legibility and agency for artists, and how the arts can provide creative strategies and methods which can add to the toolbox for human-centred XAI.

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