Investigating how experienced UX designers effectively work with machine learning - Robotics Institute Carnegie Mellon University

Investigating how experienced UX designers effectively work with machine learning

Qian Yang, Alex Sciuto, John Zimmerman, Jodi Forlizzi, and Aaron Steinfeld
Conference Paper, Proceedings of ACM Designing Interactive Systems Conference (DIS '18), pp. 585 - 596, June, 2018

Abstract

Machine learning (ML) plays an increasingly important role in improving a user's experience. However, most UX practitioners face challenges in understanding ML's capabilities or envisioning what it might be. We interviewed 13 designers who had many years of experience designing the UX of ML-enhanced products and services. We probed them to characterize their practices. They shared they do not view themselves as ML experts, nor do they think learning more about ML would make them better designers. Instead, our participants appeared to be the most successful when they engaged in ongoing collaboration with data scientists to help envision what to make and when they embraced a data-centric culture. We discuss the implications of these findings in terms of UX education and as opportunities for additional design research in support of UX designers working with ML.

BibTeX

@conference{Yang-2018-121255,
author = {Qian Yang and Alex Sciuto and John Zimmerman and Jodi Forlizzi and Aaron Steinfeld},
title = {Investigating how experienced UX designers effectively work with machine learning},
booktitle = {Proceedings of ACM Designing Interactive Systems Conference (DIS '18)},
year = {2018},
month = {June},
pages = {585 - 596},
}