Abstract
Crowdsourcing is a valuable tool to gather human input which enables the development of reliable artificial intelligence systems. Microtask platforms like Prolific and Amazon's Mechanical Turk have flourished by creating environments where crowd workers can provide such human input in a diverse and representative manner. Such marketplaces have evolved to support several hundreds of workers in earning their primary livelihood through crowd work. Crowd workers, however, often perform these tasks in sub-optimal work environments with poor ergonomics. Additionally, many of the various microtasks require input via the standard method of a mouse and keyboard and are repetitive in nature. As such, crowd workers who primarily earn their livelihoods in microtask marketplaces are at risk of injuries such as carpal tunnel syndrome. By changing the input modality from a mouse and keyboard to gesture-driven input, crowd workers can complete their work while simultaneously improving or safeguarding their physical health. Through three distinct microtasks, we constructed a dataset that enables the exploration of the physical and mental health of crowd workers while using gestures. In this work, we present the process of constructing this dataset, how we applied it, and the future applications we foresee.
Original language | English |
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Title of host publication | IUI 2023 - Companion Proceedings of the 28th International Conference on Intelligent User Interfaces |
Place of Publication | New York |
Publisher | Association for Computing Machinery (ACM) |
Pages | 255-258 |
Number of pages | 4 |
ISBN (Print) | 979-8-4007-0107-8 |
DOIs | |
Publication status | Published - 2023 |
Event | 28th International Conference on Intelligent User Interfaces, IUI 2023 - Sydney, Australia Duration: 27 Mar 2023 → 31 Mar 2023 |
Conference
Conference | 28th International Conference on Intelligent User Interfaces, IUI 2023 |
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Country/Territory | Australia |
City | Sydney |
Period | 27/03/23 → 31/03/23 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- crowdsourcing
- datasets
- microtasks
- neural networks
- pose detection