Go Gig or Go Home: Enabling Social Sensing to Share Personal Data with Intimate Partner for the Health and Wellbeing of Long-Hour workers

You, Chuang-Wen; Yuan, Chien Wen (Tina); Bi, Nanyi; Hung, Min-Wei; Huang, Po‐Yu; Wang, Hao-Chuan

doi:10.1145/3411764.3445278

Cited by 13 publications

(2 citation statements)

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous work has proposed that marginalized workers' well-being is more likely to be undermined. For example, You found that gig workers may incline towards long-hour work due to low hourly wages [91]. This result is strongly correlated with our findings: As their physical condition declines, ageing job seekers may become more vulnerable to severe inequalities, which can lead to difficulties in their employability and even survival.…”

Section: The Well Being Of Ageing Workers and Jobsupporting

confidence: 85%

“There is a Job Prepared for Me Here”: Understanding How Short Video and Live-streaming Platforms Empower Ageing Job Seekers in China

Wang,

Hu,

Wen

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

In recent years, the global unemployment rate has remained persistently high. Compounding this issue, the ageing population in China often encounters additional challenges in finding employment due to prevalent age discrimination in daily life. However, with the advent of social media, there has been a rise in the popularity of short videos and live-streams for recruiting ageing workers. To better understand the motivations of ageing job seekers to engage with these video-based recruitment methods and to explore the extent to which such platforms can empower them, we conducted an interview-based study with ageing job seekers who have had exposure to these short recruitment videos and live-streaming channels. Our findings reveal that these platforms can provide a job-seeking choice that is particularly friendly to ageing job seekers, effectively improving their disadvantaged situation. CCS CONCEPTS• Human-centered computing → Empirical studies in collaborative and social computing.

show abstract

Section: The Well Being Of Ageing Workers and Jobsupporting

confidence: 85%

“There is a Job Prepared for Me Here”: Understanding How Short Video and Live-streaming Platforms Empower Ageing Job Seekers in China

Wang,

Hu,

Wen

et al. 2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

show abstract

“…Significant research has sought to assist individuals in the latter two stages-reflection and action-when bridging the gap between users' goals and data [17,19,20,54]: these papers emphasize the importance of care in messaging taken between 'positive' and 'negative' nudges, and ongoing reflective support to create the ability for equally nuanced and personal reflections for users. You et al [86] explored these two stages with drivers and their partners, finding that the combination of technology-sensing probes (wearables) with social sense-making (having drivers and their partners share reflections about the drivers' behaviors) was promising for encouraging work-life balance for drivers. They facilitated drivers in reflection through summary tables of tracked data and diary entries, suggesting future work for increasing the granularity of data analysis for drivers.…”

Section: Personal Informatics and The Gig Economymentioning

confidence: 99%

Stakeholder-Centered AI Design: Co-Designing Worker Tools with Gig Workers through Data Probes

Zhang

Boltz

Lynn

et al. 2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

View full text Add to dashboard Cite

AI technologies continue to advance from digital assistants to assisted decision-making. However, designing AI remains a challenge given its unknown outcomes and uses. One way to expand AI design is by centering stakeholders in the design process. We conduct co-design sessions with gig workers to explore the design of gig worker-centered tools as informed by their driving patterns, decisions, and personal contexts. Using workers' own data as well as city-level data, we create probes-interactive data visuals-that participants explore to surface the well-being and positionalities that shape their work strategies. We describe participant insights and corresponding AI design considerations surfaced from data probes about: 1) workers' well-being trade-offs and positionality constraints, 2) factors that impact well-being beyond those in the data probes, and 3) instances of unfair algorithmic management. We discuss the implications for designing data probes and using them to elevate worker-centered AI design as well as for worker advocacy. CCS CONCEPTS• Human-centered computing → Human computer interaction (HCI).

show abstract

Aristotle's Phronesis as a Philosophical Foundation in Designing the Algorithmic Motivator-Driven Insulating Model (AMOI)

Costello,

Lee

2023

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Go Gig or Go Home: Enabling Social Sensing to Share Personal Data with Intimate Partner for the Health and Wellbeing of Long-Hour workers

Cited by 13 publications

References 68 publications

“There is a Job Prepared for Me Here”: Understanding How Short Video and Live-streaming Platforms Empower Ageing Job Seekers in China

“There is a Job Prepared for Me Here”: Understanding How Short Video and Live-streaming Platforms Empower Ageing Job Seekers in China

Stakeholder-Centered AI Design: Co-Designing Worker Tools with Gig Workers through Data Probes

Aristotle's Phronesis as a Philosophical Foundation in Designing the Algorithmic Motivator-Driven Insulating Model (AMOI)

Contact Info

Product

Resources

About