A Culturally-Aware Tool for Crowdworkers: Leveraging Chronemics to Support Diverse Work Styles
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Abstract (arXiv)
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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References · 15
- 2016Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotationscited by 2,656
- 2024AI-Augmented Brainwriting: Investigating the use of LLMs in group ideationcited by 44
- 2017A Data-Driven Analysis of Workers' Earnings on Amazon Mechanical Turkcited by 39
- 2022Whose AI Dream? In search of the aspiration in data annotationcited by 24
- 2021Quantifying the Invisible Labor in Crowd Workcited by 16
- 2017"Is there anything else I can help you with?": Challenges in Deploying an On-Demand Crowd-Powered Conversational Agentcited by 11
- 2021The Challenge of Variable Effort Crowdsourcing and How Visible Gold Can Helpcited by 6
- 2021In Search of Ambiguity: A Three-Stage Workflow Design to Clarify Annotation Guidelines for Crowd Workerscited by 5
- 2020The Challenges of Crowd Workers in Rural and Urban Americacited by 3
- 2019TurkScanner: Predicting the Hourly Wage of Microtaskscited by 2
- 2019Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platformscited by 2
- 2020Becoming the Super Turker: Increasing Wages via a Strategy from High Earning Workerscited by 2
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