Agency and legibility for artists through Experiential AI
Drew Hemment, Matjaz Vidmar, Daga Panas, Dave Murray-Rust, Vaishak, Belle, Aylett Ruth

TL;DR
This paper explores how experiential AI can enhance artists' understanding and control over AI systems through tangible, creative experiences, promoting transparency and agency in AI interactions.
Contribution
It introduces an empirical case study demonstrating experiential AI's potential to improve AI legibility and artist agency, and discusses its implications for human-centered explainable AI.
Findings
Experiential AI increases transparency of AI systems for artists.
Artists gain greater creative control through experiential AI methods.
Arts can contribute innovative strategies for human-centered XAI.
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…
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Taxonomy
TopicsInnovative Human-Technology Interaction · Data Visualization and Analytics · Aesthetic Perception and Analysis
