Who Did It? How User Agency is Influenced by Visual Properties of Generated Images

UIST 2024

Johanna K. Didion^1,2 Krzysztof Wolski² Dennis Wittchen^2,3 David Coyle¹ Thomas Leimkühler² Paul Strohmeier²

¹University College Dublin ²MPI Informatik ³University of Applied Sciences Dresden

Abstract

The increasing proliferation of AI and GenAI requires new interfaces tailored to how their specific affordances and human requirements meet. As GenAI is capable of taking over tasks from users on an unprecedented scale, designing the experience of agency – if and how users experience control over the process and attribution of the outcome – is crucial. As an initial step towards design guidelines for shaping agency, we present a study that explores how properties of AI-generated images influence users’ experience of agency. We use two measures; temporal binding to implicitly estimate pre-reflective agency and magnitude estimation to assess user judgments of agency. We observe that abstract images lead to more temporal binding than images with semantic meaning. In contrast, the closer an image aligns with what a user might expect, the higher the agency judgment. When comparing the experiment results with objective metrics of image differences, we find that temporal binding results correlate with semantic differences, while agency judgments are better explained by local differences between images. This work contributes towards a future where agency is considered an important design dimension for GenAI interfaces.

Materials

BibTeX

@inproceedings{didion2024whodidit,
title = {Who Did It? {H}ow User Agency is Influenced by Visual Properties of Generated Images},
author = {Didion, Johanna K. and Wolski, Krzysztof and Wittchen, Dennis and Coyle, David and Leimk{\"u}hler, Thomas and Strohmeier, Paul},
booktitle = {UIST},
year = {2024}
}