Flatpack ML: How to support designers in creating a new generation of customizable machine learning applications

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNpeer-review


This paper examines how designers can be supported in creating a new genera-tion of interactive machine learning (ML) applications that run locally on con-sumer-level hardware and can be trained and customized by end-users for their specific context and use case. It delineates the proposed applications against re-search into Interactive Machine Learning and Machine Teaching, examines the challenges designers face in these contexts and their relevance for designing the proposed new applications, and reports on the findings of a survey exploring de-signers' interest in ML, their understanding of ML capabilities and concepts, and their preferences for learning about ML. Based on findings from the literature and the survey, the paper identifies three overlapping research challenges in supporting designers to ideate, design and prototype the proposed ML applications.
Original languageEnglish
Title of host publicationDesign, User Experience, and Usability. Design for Contemporary Interactive Environments - 9th International Conference, DUXU 2020, Held as Part of the 22nd HCI International Conference, HCII 2020, Proceedings
Subtitle of host publicationDesign for Contemporary Interactive Environments
EditorsAaron Marcus, Elizabeth Rosenzweig
Place of PublicationCham
PublisherSpringer LNCS
Number of pages19
ISBN (Electronic)9783030497606
ISBN (Print)9783030497590
Publication statusPublished - 10 Jul 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12201 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


  • machine learning
  • customisation
  • user experience
  • design
  • HCI
  • Design
  • Customization
  • User experience
  • Machine Learning


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