Relational, Flexible, Everyday: Learning from Ethics in Dementia Research

Hodge, James; Foley, Sarah; Brankaert, Rens; Kenning, Gail; Lazar, Amanda; Boger, Jennifer; Morrissey, Kellie

doi:10.1145/3313831.3376627

Cited by 24 publications

(20 citation statements)

References 98 publications

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“…As suggested by [17], we monitored consent during each session with the residents: we checked in verbally if they wanted to play activities and whether they wanted to swap games. It was important to us to ensure that participants were comfortable during the activities and to lexibly respond to the engagement of participants [32], so there were days where we had to divert from the research activities to other activities or to recommend resting instead of continuing the session. he research project received ethics approval through Swinburne University's Human Research Ethics Commitee.…”

Section: Ethicsmentioning

confidence: 99%

Evaluating Engagement in Technology-Supported Social Interaction by People Living with Dementia in Residential Care

Muñoz

Pedell

Sterling

2022

ACM Trans. Comput.-Hum. Interact.

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Technologies can support the wellbeing of people living with dementia in residential care by fostering meaningful interactions through multimodal and playful features. This article presents the evaluation of A Better Visit, an app that aims to engage residents and visitors in shared activities. We define engagement in terms of dyadic interactions with the interface of the device, and interactions within the social context of the care home. We generated two Motivational Models that describe different perspectives of how people engaged with the system: the first was built with the design team, and the second was built using the first Motivational Model as sensitising concept for the analysis of data from four care homes that used the app for periods of three months. Our findings show that the facilitation of activities plays a relevant role for engaging in social interaction. We discuss how technologies can contribute to engaging people living with dementia in social interaction: firstly, facilitation can be understood as a concept that is supported by people and technology. Secondly, we discuss the influence of the social context of the setting and the understandings of the individual in how people assess engagement of the residents in social interaction.

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Section: Ethicsmentioning

confidence: 99%

Evaluating Engagement in Technology-Supported Social Interaction by People Living with Dementia in Residential Care

Muñoz

Pedell

Sterling

2022

ACM Trans. Comput.-Hum. Interact.

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“…With the changes in balance that people with dementia experience [38], this opens up new opportunities for voice enabled smart speakers to facilitate everyday tasks such as turning on and off devices without having to stand up, which could put someone in jeopardy of falling and hurting themselves. However, this brings up debates over agency vs safety in dementia technology design [27,54,55,65,113], which are of critical importance for technology designers in this space to consider.…”

Section: Interacting With Technology Using the Sensesmentioning

confidence: 99%

Understanding How Sensory Changes Experienced by Individuals with a Range of Age-Related Cognitive Changes Can Affect Technology Use

Dixon

Anderson

Lazar

2022

ACM Trans. Access. Comput.

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Clinical researchers have identified sensory changes people with age-related cognitive changes, such as dementia and mild cognitive impairment, experience which are different from typical age-related sensory changes. Technology designers and researchers do not yet have an understanding of how these unique sensory changes affect technology use. This work begins to bridge the gap between the clinical knowledge of sensory changes and technology research and design through interviews with people with mild to moderate dementia, mild cognitive impairment, subjective cognitive decline, and healthcare professionals. This extended version of our ASSETS conference paper includes people with a range of age-related cognitive changes describing changes in vision, hearing, speech, dexterity, proprioception, and smell. We discuss each of these sensory changes and ways to leverage optimal modes of sensory interaction for accessible technology use with existing and emerging technologies. Finally, we discuss how accessible sensory stimulation may change across the spectrum of age-related cognitive changes.

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“…Dataset authors should consider the context of compensation, in terms of what is most valued by annotators; money or gift cards may not be the most appropriate compensation for all contexts. For example, Hodge et al found that money was not useful to their participants who live in care homes [56]. Further, if the authors expect to make a profit from their dataset, they should consider what fair compensation would be to their subjects and authors given that profit necessitates their data and labor.…”

Section: Recommendations For Incorporating the Value Of Carementioning

confidence: 99%

Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development

Scheuerman

Hanna

Denton

2021

Proc. ACM Hum.-Comput. Interact.

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Data is a crucial component of machine learning. The field is reliant on data to train, validate, and test models. With increased technical capabilities, machine learning research has boomed in both academic and industry settings, and one major focus has been on computer vision. Computer vision is a popular domain of machine learning increasingly pertinent to real-world applications, from facial recognition in policing to object detection for autonomous vehicles. Given computer vision's propensity to shape machine learning research and impact human life, we seek to understand disciplinary practices around dataset documentation-how data is collected, curated, annotated, and packaged into datasets for computer vision researchers and practitioners to use for model tuning and development. Specifically, we examine what dataset documentation communicates about the underlying values of vision data and the larger practices and goals of computer vision as a field. To conduct this study, we collected a corpus of about 500 computer vision datasets, from which we sampled 114 dataset publications across different vision tasks. Through both a structured and thematic content analysis, we document a number of values around accepted data practices, what makes desirable data, and the treatment of humans in the dataset construction process. We discuss how computer vision datasets authors value efficiency at the expense of care; universality at the expense of contextuality; impartiality at the expense of positionality; and model work at the expense of data work. Many of the silenced values we identify sit in opposition with social computing practices. We conclude with suggestions on how to better incorporate silenced values into the dataset creation and curation process. CCS Concepts: • Human-centered computing → Collaborative and social computing; • Computing methodologies → Artificial intelligence.

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Relational, Flexible, Everyday: Learning from Ethics in Dementia Research

Cited by 24 publications

References 98 publications

Evaluating Engagement in Technology-Supported Social Interaction by People Living with Dementia in Residential Care

Evaluating Engagement in Technology-Supported Social Interaction by People Living with Dementia in Residential Care

Understanding How Sensory Changes Experienced by Individuals with a Range of Age-Related Cognitive Changes Can Affect Technology Use

Do Datasets Have Politics? Disciplinary Values in Computer Vision Dataset Development

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