A Case Study Investigating a User-Centred and Expert Informed 'Companion Guide' for a Complex Sensor-based Platform

2022. Rachel Eardley, Sue Mackinnon, Emma Tonkin, Ewan Soubutts, Amid Ayobi, Jess Linington, Gregory Tourte, Zoe Gross, David Bailey, Russell Knights, Rachael Gooberman-Hill, Ian Craddock & Aisling O'Kane
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies.

Abstract

We present a case study that informs the creation of a 'companion guide' providing transparency to potential non-expert users of a ubiquitous machine learning (ML) platform during the initial onboarding. Ubiquitous platforms (e.g., smart home systems, including smart meters and conversational agents) are increasingly commonplace and increasingly apply complex ML methods. Understanding how non-ML experts comprehend these platforms is important in supporting participants in making an informed choice about if and how they adopt these platforms. To aid this decision-making process, we created a companion guide for a home health platform through an iterative user-centred-design process, seeking additional input from platform experts at all stages of the process to ensure the accuracy of explanations. This user-centred and expert informed design process highlights the need to present the platform's entire ecosystem at an appropriate level for those with differing backgrounds to understand, in order to support informed consent and decision making.

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Citation

Eardley, R., Mackinnon, S., Tonkin, E. L., Soubutts, E., Ayobi, A., Linington, J., … O'Kane, A. A. (2022 , jul). A case study investigating a user-centred and expert informed 'companion guide' for a complex sensor-based platform. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 6(2). URL: https://doi.org/10.1145/3534625, doi:10.1145/3534625

BibTeX

@article{10.1145/3534625,
author = {Eardley, Rachel and Mackinnon, Sue and Tonkin, Emma L. and Soubutts, Ewan and Ayobi, Amid and Linington, Jess and Tourte, Gregory J. L. and Gross, Zoe Banks and Bailey, David J. and Knights, Russell and Gooberman-Hill, Rachael and Craddock, Ian and O'Kane, Aisling Ann},
title = {A Case Study Investigating a User-Centred and Expert Informed 'Companion Guide' for a Complex Sensor-based Platform},
year = {2022},
issue_date = {July 2022},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {6},
number = {2},
url = {https://doi.org/10.1145/3534625},
doi = {10.1145/3534625},
abstract = {We present a case study that informs the creation of a 'companion guide' providing transparency to potential non-expert users of a ubiquitous machine learning (ML) platform during the initial onboarding. Ubiquitous platforms (e.g., smart home systems, including smart meters and conversational agents) are increasingly commonplace and increasingly apply complex ML methods. Understanding how non-ML experts comprehend these platforms is important in supporting participants in making an informed choice about if and how they adopt these platforms. To aid this decision-making process, we created a companion guide for a home health platform through an iterative user-centred-design process, seeking additional input from platform experts at all stages of the process to ensure the accuracy of explanations. This user-centred and expert informed design process highlights the need to present the platform's entire ecosystem at an appropriate level for those with differing backgrounds to understand, in order to support informed consent and decision making.},
journal = {Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.},
month = {jul},
articleno = {93},
numpages = {23},
keywords = {Smart home, Onboarding, Machine Learning, Health, Design process, Case study}
}