Rights statement: © ACM, 2022. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CHI EA '22: Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems http://doi.acm.org/10.1145/3491101.3503725
Accepted author manuscript, 440 KB, PDF document
Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Reimagining Global Crowdsourcing for Better Human-AI Collaboration
AU - Alorwu, Andy
AU - Savage, Saiph
AU - Van Berkel, Neils
AU - Ustalov, Dmitry
AU - Drutsa, Alexey
AU - Oppenlaender, Jonas
AU - Bates, Oliver
AU - Hettiachchi, Danula
AU - Gadiraju, Ujwal
AU - Goncalves, Jorge
AU - Hosio, Simo
N1 - © ACM, 2022. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in CHI EA '22: Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems http://doi.acm.org/10.1145/3491101.3503725
PY - 2022/5/5
Y1 - 2022/5/5
N2 - Crowdworkers silently enable much of today's AI-based products, with several online platforms offering a myriad of data labelling and content moderation tasks through convenient labour marketplaces. The HCI community has been increasingly interested in investigating the worker-centric issues inherent in the current model and seeking for potential improvements that could be implemented in the future. This workshop explores how a reimagined perspective on crowdsourcing platforms could provide a more equitable, fair, and rewarding experience. This includes not only the workers but also the platforms, who could benefit e.g. from better processes for worker onboarding, skills-development, and growth. We invite visionary takes in various formats on this topic to spread awareness of worker-centric research and developments to the CHI community. As a result of interactive ideation work in the workshop, we articulate a future direction roadmap for research centred around crowdsourcing platforms. Finally, as a specific interest area, the workshop seeks to study crowdwork from the context of the Global South, which has been arising as an important but critically understudied crowdsourcing market in recent years.
AB - Crowdworkers silently enable much of today's AI-based products, with several online platforms offering a myriad of data labelling and content moderation tasks through convenient labour marketplaces. The HCI community has been increasingly interested in investigating the worker-centric issues inherent in the current model and seeking for potential improvements that could be implemented in the future. This workshop explores how a reimagined perspective on crowdsourcing platforms could provide a more equitable, fair, and rewarding experience. This includes not only the workers but also the platforms, who could benefit e.g. from better processes for worker onboarding, skills-development, and growth. We invite visionary takes in various formats on this topic to spread awareness of worker-centric research and developments to the CHI community. As a result of interactive ideation work in the workshop, we articulate a future direction roadmap for research centred around crowdsourcing platforms. Finally, as a specific interest area, the workshop seeks to study crowdwork from the context of the Global South, which has been arising as an important but critically understudied crowdsourcing market in recent years.
U2 - 10.1145/3491101.3503725
DO - 10.1145/3491101.3503725
M3 - Conference contribution/Paper
BT - CHI EA '22: Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems
A2 - Barbosa, Simone
A2 - Lampe, Cliff
PB - ACM
CY - New York
ER -