Exploring Crowdworkers' Perceptions, Current Practices, and Desired Practices Regarding Using Non-Workstation Devices for Crowdwork
<|reference_start|>Exploring Crowdworkers' Perceptions, Current Practices, and Desired Practices Regarding Using Non-Workstation Devices for Crowdwork: Despite a plethora of research dedicated to designing HITs for non-workstations, there is a lack of research looking specifically into workers' perceptions of the suitability of these devices for managing and completing work. In this work, we fill this research gap by conducting an online survey of 148 workers on Amazon Mechanical Turk to explore 1. how crowdworkers currently use their non-workstation devices to complete and manage crowdwork, 2. what challenges they face using those devices, and 3. to what extent they wish they could use those devices if their concerns were addressed. Our results show that workers unanimously favor using a desktop to complete and manage crowdwork. While workers occasionally use smartphones or tablets, they find their suitability marginal at best and have little interest in smart speakers and smartwatches, viewing them as unsuitable for crowdwork. When investigating the reason for these views, we find that the key issue is that non workstation devices lack the tooling necessary to automatically find and accept HITs, tooling that workers view as essential in their efforts to compete with bots in accepting high paying work. To address this problem, we propose a new paradigm for finding, accepting, and completing crowdwork that puts crowdworkers on equal footing with bots in these tasks. We also describe future research directions for tailoring HITs to non workstation devices and definitely answering whether smart speakers and smartwatches have a place in crowdwork.<|reference_end|>
@article{dutta2024exploring,
    title={Exploring Crowdworkers' Perceptions, Current Practices, and Desired
  Practices Regarding Using Non-Workstation Devices for Crowdwork},
    author={Senjuti Dutta, Scott Ruoti, Rhema Linder, Alex C. Williams, Anastasia
  Kuzminykh},
    journal={arXiv preprint arXiv:2409.04676},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.04676},
    primaryClass={cs.HC}
}