Year: 2026
Type: dissertation
Abstract: AI technology increasingly permeates creative domains. Among AI systems, deep learning models behave like black boxes, concealing the processes behind their outputs. The field of explainable AI (XAI) has emerged in response to this. But what is to be explained as AI enters creative practice? This project takes a critical stance on XAI assumptions as applied to the arts, and investigates the aesthetics and discourse emerging from AI’s inherent opacity, along with the epistemological potential it bears. Through musical instrument design, artistic practice, and user studies, I show how artists leverage AI models’ unknowns as a source of poetic meaning, often converging on artistic reflections around algorithmic presence. Drawing on these findings, I develop a theoretical framework grounded in hauntology theory that reframes AI as a spectral construct. The framework is applied to interviews with artists, offering insights on AI musical interfaces, AI mediation, and current debates around agentic AI.
Source: Opin vísindi (Opin vísindi)
Author: privato, nicola
Language: English
Subfield: Music
Field: Arts and Humanities
Domain: Social Sciences
Open Access status: green
Funder: European Commission
Award: G7257368210
OpenAlex ID: W7223422452