Canvil: Designerly Adaptation for LLM-Powered User Experiences

要旨

Advancements in large language models (LLMs) are sparking a proliferation of LLM-powered user experiences (UX). In product teams, designers often craft UX to meet user needs, but it is unclear how they engage with LLMs as a novel design material. Through a formative study with 12 designers, we find that designers seek a translational process that enables design requirements to shape and be shaped by LLM behavior, motivating a need for designerly adaptation to facilitate this translation. We then built Canvil, a Figma widget that operationalizes designerly adaptation. We used Canvil as a probe to study designerly adaptation in a group-based design study (N=17), finding that designers constructively iterated on both adaptation approaches and interface designs to enhance end-user interaction with LLMs. Furthermore, designers identified promising collaborative workflows for designerly adaptation. Our work opens new avenues for processes and tools that foreground designers' human-centered expertise when developing LLM-powered applications.

著者
K. J. Kevin Feng
University of Washington, Seattle, Washington, United States
Q. Vera Liao
Microsoft Research, Montreal, Quebec, Canada
Ziang Xiao
Johns Hopkins University, Baltimore, Maryland, United States
Jennifer Wortman Vaughan
Microsoft Research, New York, New York, United States
Amy X.. Zhang
University of Washington, Seattle, Washington, United States
David W.. McDonald
University of Washington, Seattle, Washington, United States
DOI

10.1145/3706598.3713139

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713139

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Shaping Cognitive Processes

G416+G417
7 件の発表
2025-05-01 01:20:00
2025-05-01 02:50:00
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