ML-process canvas: A design tool to support the UX design of machine learning-empowered products

Zhibin Zhou, Zheting Qi, Qing Gong, Lingyun Sun

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Machine learning (ML) is now widely used to empower products and services, but there is a lack of research on the tools that involve designers in the entire ML process. Thus, designers who are new to ML technology may struggle to fully understand the capabilities of ML, users, and scenarios when designing ML-empowered products. This paper describes a design tool, ML-Process Canvas (see Fig. 1), which assists designers in considering the specific factors of the user, ML system, and scenario throughout the whole ML process. The Canvas was applied to a design project, and was observed to contribute in the conceptual phase of UX design practice. In the future, we hope that the Canvas will become more practical through continued use in design practice.

Original languageEnglish
Title of host publicationCHI EA 2019 - Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450359719
DOIs
Publication statusPublished - 2 May 2019
Externally publishedYes
Event2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019 - Glasgow, United Kingdom
Duration: 4 May 20199 May 2019

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2019 CHI Conference on Human Factors in Computing Systems, CHI EA 2019
Country/TerritoryUnited Kingdom
CityGlasgow
Period4/05/199/05/19

Keywords

  • Design method
  • Design tool
  • Machine learning
  • User experience

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design

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