A Culturally-Aware AI Tool for Crowdworkers: Leveraging Chronemics to Support Diverse Work Styles

Crowdsourcing markets are expanding worldwide, but often feature standardized interfaces that ignore the cultural diversity of their workers, negatively impacting their well-being and productivity. To transform these workplace dynamics, this paper proposes creating culturally-aware workplace tools, specifically designed to adapt to the cultural dimensions of monochronic and polychronic work styles. We illustrate this approach with "CultureFit," a tool that we engineered based on extensive research in Chronemics and culture theories. To study and evaluate our tool in the real world, we conducted a field experiment with 55 workers from 24 different countries. Our field experiment revealed that CultureFit significantly improved the earnings of workers from cultural backgrounds often overlooked in design. Our study is among the pioneering efforts to examine culturally aware digital labor interventions. It also provides access to a dataset with over two million data points on culture and digital work, which can be leveraged for future research in this emerging field. The paper concludes by discussing the importance and future possibilities of incorporating cultural insights into the design of tools for digital labor.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2024-11-07
DOI
https://doi.org/10.1145/3686899
Citations
6
Primary Topic
Mobile Crowdsensing and Crowdsourcing
Type
article
Field-Weighted Citation Impact
2.47
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article

A Culturally-Aware AI Tool for Crowdworkers: Leveraging Chronemics to Support Diverse Work Styles

Christopher Michael Curtis, Carlos Toxtli, Saiph Savage
6 citations
Proceedings of the ACM on Human-Computer Interaction
Mobile Crowdsensing and Crowdsourcing
2.47
article

A Culturally-Aware AI Tool for Crowdworkers: Leveraging Chronemics to Support Diverse Work Styles

Christopher Michael Curtis, Carlos Toxtli, Saiph Savage
article en
6 citations

Abstract

Crowdsourcing markets are expanding worldwide, but often feature standardized interfaces that ignore the cultural diversity of their workers, negatively impacting their well-being and productivity. To transform these workplace dynamics, this paper proposes creating culturally-aware workplace tools, specifically designed to adapt to the cultural dimensions of monochronic and polychronic work styles. We illustrate this approach with "CultureFit," a tool that we engineered based on extensive research in Chronemics and culture theories. To study and evaluate our tool in the real world, we conducted a field experiment with 55 workers from 24 different countries. Our field experiment revealed that CultureFit significantly improved the earnings of workers from cultural backgrounds often overlooked in design. Our study is among the pioneering efforts to examine culturally aware digital labor interventions. It also provides access to a dataset with over two million data points on culture and digital work, which can be leveraged for future research in this emerging field. The paper concludes by discussing the importance and future possibilities of incorporating cultural insights into the design of tools for digital labor.

Proceedings of the ACM on Human-Computer InteractionVol. 8(CSCW2)
Northeastern University (US), Clemson University (US), Universidad del Noreste (MX), Universidad Nacional Autónoma de México (MX)
Decent work and economic growth
Openalex Percentile: Top 8%
Mobile Crowdsensing and Crowdsourcing
2.47
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