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Investigating the accessibility of crowdwork tasks on Mechanical Turk

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Uzor_2022_Investigating_accessibility_CC.pdf (1.105Mb)
Date
06/05/2021
Author
Uzor, Stephen
Jacques, Jason T.
Dudley, John J.
Kristensson, Per Ola
Keywords
Accessibility
Amt
Crowdsourcing
Crowdwork
Disability
MTurk
QA75 Electronic computers. Computer science
QA76 Computer software
Computer Graphics and Computer-Aided Design
Human-Computer Interaction
Software
DAS
NIS
MCC
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Abstract
Crowdwork can enable invaluable opportunities for people with disabilities, not least the work fexibility and the ability to work from home, especially during the current Covid-19 pandemic. This paper investigates how engagement in crowdwork tasks is affected by individual disabilities and the resulting implications for HCI. We first surveyed 1,000 Amazon Mechanical Turk (AMT) workers to identify demographics of crowdworkers who identify as having various disabilities within the AMT ecosystem-including vision, hearing, cognition/mental, mobility, reading and motor impairments. Through a second focused survey and follow-up interviews, we provide insights into how respondents cope with crowdwork tasks. We found that standard task factors, such as task completion time and presentation, often do not account for the needs of users with disabilities, resulting in anxiety and a feeling of depression on occasion. We discuss how to alleviate barriers to enable effective interaction for crowdworkers with disabilities.
Citation
Uzor , S , Jacques , J T , Dudley , J J & Kristensson , P O 2021 , Investigating the accessibility of crowdwork tasks on Mechanical Turk . in P Bjørn & S Drucker (eds) , CHI '21 : proceedings of the 2021 CHI conference on human factors in computing systems . , 381 , Conference on human factors in computing systems - proceedings , Association for Computing Machinery, Inc , 2021 CHI Conference on Human Factors in Computing Systems , Virtual, Online , Japan , 8/05/21 . https://doi.org/10.1145/3411764.3445291
 
conference
 
Publication
CHI '21
DOI
https://doi.org/10.1145/3411764.3445291
ISSN
1062-9432
Type
Conference item
Rights
Copyright © 2021 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License.
Description
Funding: This work was supported by the EPSRC (grants EP/R004471/1 and EP/S027432/1). Supporting data for this publication is available at https://doi.org/10.17863/CAM.62937.
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  • University of St Andrews Research
URL
https://dl.acm.org/doi/proceedings/10.1145/3411764
URI
http://hdl.handle.net/10023/26115

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