Exploring Plural Perspectives in Self-Tracking Technologies: Trust and Reflection in Self Tracking Practices
October 16, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Sujay Shalawadi, Rosa van Koningsbruggen, Rikke Hagensby Jensen
arXiv ID
2410.12546
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Contemporary self-tracking technologies (STTs), such as smartwatches and smartphone apps, allow people to become self-aware through the datafication of their everyday lives. However, concerns are emerging over the global north/Western portrayal of the self in the envisionment of STTs. Given the call to diversify participant samples in HCI knowledge building, we see it timely in understanding the influence of ubiquitous STTs in global south societies. We conduct a between-group analysis of 156 and 121 participants from Global North and South through two iterative surveys, respectively. We uncover significant differences in perceived trust with their STTs and reflection practices between the groups. We provide an empirical understanding on advocating for inclusive design strategies that recognize diverse interpretations of STTs and highlight the need to prioritize local values and flexibility in tracking to foster deeper reflection across cultures. Lastly, we discuss our findings in relation to the existing literature and highlight design recommendations for future research.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted