Exploring Crowdsourced Work in Low-Resource Settings

Crowdsourcing Task Design & Quality ControlDeveloping Countries & HCI for Development (HCI4D)Micro-Entrepreneurs (Developing Countries)Amazon Mechanical Turk Workers

While researchers have studied the benefits and hazards of crowdsourcing for diverse classes of workers, most work has focused on those having high familiarity with both computers and English. We explore whether paid crowdsourcing can be inclusive of individuals in rural India, who are relatively new to digital devices and literate mainly in local languages. We built an Android application to measure the accuracy with which participants can digitize handwritten Marathi/Hindi words. The tasks were based on the real-world need for digitizing handwritten Devanagari script documents. Results from a two-week, mixed-methods study show that participants achieved 96.7% accuracy in digitizing handwritten words on low-end smartphones. A crowdsourcing platform that employs these users performs comparably to a professional transcription firm. Participants showed overwhelming enthusiasm for completing tasks, so much so that we recommend imposing limits to prevent overuse of the application. We discuss the implications of these results for crowdsourcing in low-resource areas.

Quick Actions

Share

Share this page

ios_share

https://hci.top/en/papers/chi/4767/2019

AdRecommended

Learn AI Coding at CodeNow

At a Glance

Paper Snapshot

fact_check
dataset
Source
CHI
calendar_month
Year
2019
emoji_events
Award
No award tagged
group
Authors
6 authors
sell
Subtopics
Crowdsourcing Task Design & Quality Control, Developing Countries & HCI for Development (HCI4D)
work
Professions
Micro-Entrepreneurs (Developing Countries), Amazon Mechanical Turk Workers
article
Content Status
Abstract only
hub
Related Papers
3 related papers