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"Why would anybody do this?": Understanding Older Adults' Motivations and Challenges in Crowd Work
Abstract
Diversifying participation in crowd work can benefit the worker and requester. Increasing numbers of older adults are online, but little is known about their awareness of or how they engage in mainstream crowd work. Through an online survey with 505 seniors, we found that most have never heard of crowd work but would be motivated to complete tasks by earning money or working on interesting or stimulating tasks. We follow up results from the survey with interviews and observations of 14 older adults completing crowd work tasks. While our survey data suggests that financial incentives are encouraging, in-depth interviews reveal that a combination of personal and social incentives may be stronger drivers of participation, but only if older adults can overcome accessibility issues and understand the purpose of crowd work. This paper contributes insights into how crowdsourcing sites could better engage seniors and other users.
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“Learning and memory support are often motivating factors for why older adults engage online [5,9,33].”
From Studying Exploration & Long-Term Use of Voice Assistants by Older Adults (2023) · cites this paper as [5]
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Cites
Ryan, R. M., & Deci, E. L. (2000) · American Psychologist · doi:10.1037//0003-066x.55.1.68 · Cited by 54,599
Social disconnectedness, perceived isolation, and health among older adults
Cornwell, E. Y., & Waite, L. J. (2009) · Journal of Health and Social Behavior · doi:10.1177/002214650905000103 · Cited by 2,027
Crowdsourcing user studies with Mechanical Turk
Kittur, A., Ed, H., & Suh, B. (2008) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1357054.1357127 · Cited by 1,941
Lakhani, K. R., & Wolf, R. G. (2003) · doi:10.2139/ssrn.443040 · Cited by 1,531
Lakhani, K. R., & Wolf, R. G. (2005) · Perspectives on Free and Open Source Software · doi:10.7551/mitpress/5326.003.0005 · Cited by 1,530
Watson, W. E., Kumar, K., & Michaelsen, L. K. (1993) · Academy of Management Journal · doi:10.5465/256593 · Cited by 1,454
Kittur, A., Nickerson, J. V., Bernstein, M., Gerber, E., Shaw, A., Zimmerman, J., Lease, M., & Horton, J. (2013) · Proceedings of the 2013 conference on Computer supported cooperative work · doi:10.1145/2441776.2441923 · Cited by 1,034
Who are the crowdworkers?: shifting demographics in mechanical turk
Ross, J., Irani, L., Silberman, M. S., Zaldivar, A., & Tomlinson, B. (2010) · CHI '10 Extended Abstracts on Human Factors in Computing Systems · doi:10.1145/1753846.1753873 · Cited by 1,004
Glass, T. A., de Leon, C. M., Marottoli, R. A., & Berkman, L. F. (1999) · BMJ · doi:10.1136/bmj.319.7208.478 · Cited by 924
Effects of Volunteering on the Well-Being of Older Adults
Morrow-Howell, N., Hinterlong, J., Rozario, P. A., & Tang, F. (2003) · The Journals of Gerontology: Series B · doi:10.1093/geronb/58.3.s137 · Cited by 923
Research works printed but not linked: 4
- Glass Thomas A, 1999, Richard A Marottoli, and Lisa F Berkman.
- Lehtinen Vilma, older adults' understandings of social networking sites. BCS-HCI
- Pink Daniel H., 2009, Drive: The surprising truth about what motivates us
- Yarosh Svetlana, Proceedings of the 28th international conference on Human factors in computing systems CHI '10, 1251
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Turned 70? It is time to start editing WikipediaPreprint
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Miura, T., Arita, S., Hiyama, A., Kobayashi, M., Itoko, T., Sawamura, J., & Hirose, M. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-40250-5_35
AuDi: an Auto-Feedback Display for Crowdsourcing
Tang, X., Zhao, D., Zhang, Y., & Ding, X. (2019) · ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) · doi:10.18420/ecscw2019_ep05
Metadata
- Authors
- Brewer, R., Morris, M. R., & Piper, A. M.
- Affiliations
- Northwestern University (US)
- Microsoft (United States) (US)
- Venue
- Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2016-05-07
- Pages
- 2246-2257
- OpenAlex
- W2405742202
- Cited by
- 111
- References
- 42
- Citations by year
- 2026: 3 · 2025: 8 · 2024: 7 · 2023: 11 · 2022: 10 · 2021: 22 · 2020: 8 · 2019: 14 · 2018: 11 · 2017: 15 · 2016: 2
- FWCI
- 11.17
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference on Human Factors in Computing Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Mobile Crowdsensing and Crowdsourcing
- Health Sciences › Medicine › Geriatrics and Gerontology › Technology Use by Older Adults
- Social Sciences › Business, Management and Accounting › Management Information Systems › FinTech, Crowdfunding, Digital Finance
- Keywords
- crowdwork, older adults, crowdsourcing, participation motivation, financial incentives, social incentives, accessibility, task understanding, crowdsourcing platforms
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