RESEARCH

COMPUTER VISION

Predicting A Creator’s Preferences In, and From, Interactive Generative Art

September 7, 2020

Abstract

As a lay user creates an art piece using an interactive generative art tool, what, if anything, do the choices they make tell us about them and their preferences? Both within the generative art form, and otherwise? As a preliminary study, we collect preferences from 311 subjects, in a specific generative art form and in other walks of life. We train machine learning models to predict a subset of preferences from the rest. We find that preferences in the generative art form cannot predict preferences in other walks of life better than chance (and vice versa). However, preferences within the generative art form are reliably predictive of each other.

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AUTHORS

Written by

Devi Parikh

Publisher

International Conference on Computational Creativity (ICCC)

Research Topics

Computer Vision

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