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Investigating the Accessibility of Crowdwork Tasks on Mechanical Turk

Authors:

Jason T. Jacques,

Per Ola KristenssonAuthors Info & Claims

CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Article No.: 381, Pages 1 - 14

https://doi.org/10.1145/3411764.3445291

Published: 07 May 2021 Publication History

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Abstract

Crowdwork can enable invaluable opportunities for people with disabilities, not least the work flexibility 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.

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Index Terms

Investigating the Accessibility of Crowdwork Tasks on Mechanical Turk
1. Human-centered computing
  1. Accessibility
    1. Empirical studies in accessibility
  2. Human computer interaction (HCI)

Index terms have been assigned to the content through auto-classification.

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cover image ACM Conferences

CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

May 2021

10862 pages

ISBN:9781450380966

DOI:10.1145/3411764

General Chairs:
Yoshifumi Kitamura
Tohoku University, Japan
,
Aaron Quigley
University of New South Wales, Australia
,
Program Chairs:
Katherine Isbister
University of California Santa Cruz, USA
,
Takeo Igarashi
The University of Tokyo, Japan
,
Publications Chairs:
Pernille Bjørn
University of Copenhagen, Denmark
,
Steven Drucker
Microsoft Research, USA

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Published: 07 May 2021

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May 8 - 13, 2021

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https://dl.acm.org/doi/10.1145/3641023
Xiao LBandukda MAngerbauer KLin WBhatnagar TSedlmair MHolloway C(2024)A Systematic Review of Ability-diverse Collaboration through Ability-based Lens in HCIProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3641930(1-21)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3641930
Paulino DFerreira JNetto ACorreia ARibeiro JGuimarães DBarroso JParedes H(2024)Probing into the Usage of Task Fingerprinting in Web Games to Enhance Cognitive Personalization: A Pilot Gamified Experience with Neurodivergent Participants2024 IEEE 12th International Conference on Serious Games and Applications for Health (SeGAH)10.1109/SeGAH61285.2024.10639597(1-8)Online publication date: 7-Aug-2024
https://doi.org/10.1109/SeGAH61285.2024.10639597
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Harris C(2023)Evaluating Mitigation Approaches for Adversarial Attacks in Crowdwork2023 IEEE International Conference on Big Data and Smart Computing (BigComp)10.1109/BigComp57234.2023.00026(113-119)Online publication date: Feb-2023
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Vishwarupe VJoshi PMaheshwari SKuklani PShingote PPande MPawar VDeshmukh A(2023)Exploring Human Computer Interaction in Industry 4.0AI, IoT, Big Data and Cloud Computing for Industry 4.010.1007/978-3-031-29713-7_2(21-38)Online publication date: 1-Aug-2023
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Ding YYou JMachulla TJacobs JSen PHöllerer T(2022)Impact of Annotator Demographics on Sentiment Dataset LabelingProceedings of the ACM on Human-Computer Interaction10.1145/35556326:CSCW2(1-22)Online publication date: 11-Nov-2022
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Rechkemmer AYin M(2022)Understanding the Microtask Crowdsourcing Experience for Workers with Disabilities: A Comparative ViewProceedings of the ACM on Human-Computer Interaction10.1145/35551376:CSCW2(1-30)Online publication date: 11-Nov-2022
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