Book contents
- Human-Centered Machine Learning
- Reviews
- Human-Centered Machine Learning
- Copyright page
- Contents
- Contributors
- 1 Introduction
- Part I Human-Centered Machine Learning in the Arts and Humanities
- Part II Doing Human-Centered Machine Learning
- 5 Measuring the User Experience of Human-Centered Machine Learning
- 6 Data for Machine Learning
- 7 REDesigning AI Products and Services
- Part III Humans and Machine Learning
- Part IV Machine Learning in Its Social Context
- Part V Machine Learning and Humanity
- References
5 - Measuring the User Experience of Human-Centered Machine Learning
Trust, Intelligibility, and More
from Part II - Doing Human-Centered Machine Learning
Published online by Cambridge University Press: 11 September 2026
Book contents
- Human-Centered Machine Learning
- Reviews
- Human-Centered Machine Learning
- Copyright page
- Contents
- Contributors
- 1 Introduction
- Part I Human-Centered Machine Learning in the Arts and Humanities
- Part II Doing Human-Centered Machine Learning
- 5 Measuring the User Experience of Human-Centered Machine Learning
- 6 Data for Machine Learning
- 7 REDesigning AI Products and Services
- Part III Humans and Machine Learning
- Part IV Machine Learning in Its Social Context
- Part V Machine Learning and Humanity
- References
Summary
This chapter provides an overview of user experience (UX), particularly focusing on the UX of human-centred machine learning (HCML). In this chapter we will focus on “less standard” measures that are particularly relevant in HCML; other measures such as accuracy are already covered very well in standard ML approaches. Central to our notion of HCML is that the set of people who are users of ML is much broader and also distinctive compared to other domains. For example, these “users” might be people who use the final system in their work or everyday lives, or people who help develop the HCML, or indeed regulators and assessors of these systems. In this chapter, we will outline what aspects to measure for assessing the UX of HCML systems and how to measure them. We conclude by looking at open research areas in measuring the UX of HCML.
Information
- Type
- Chapter
- Information
- Human-Centered Machine Learning , pp. 107 - 122Publisher: Cambridge University PressPrint publication year: 2026
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