Addressing Repetition in Crowdsourcing: A Concept for Fast-Form Entry

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Abstract

This workshop paper outlines a conceptual browser plugin that enables crowdworkers to store and later rapidly provide personal information frequently requested in crowdsourcing tasks. Personal data, including demographic data such as age and ethnicity, as well as responses to commonly used personality-related survey instruments, is often critical to collect in crowdsourcing tasks but results in a repetitive experience for crowdworkers. From a requesters perspective, this repetition can result in reduced data quality or the decision to abstain from collecting extensive information on the workers completing a given task. Moreover, given the extensive role of crowdworkers in labelling training data for artificial intelligence applications, ensuring awareness of the workers’ characteristics can help alleviate future biases. In this work, we present the motivation and design requirements for this (hypothetical) plugin and seek input from the community towards its future development.
Original languageEnglish
Title of host publicationAdjunct Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI’22 EA)
Number of pages6
PublisherAssociation for Computing Machinery
Publication date2 Mar 2022
Publication statusPublished - 2 Mar 2022
EventCHI'22 - New Orleans, United States
Duration: 30 Apr 20225 May 2022
Conference number: 40
https://chi2022.acm.org/

Conference

ConferenceCHI'22
Number40
Country/TerritoryUnited States
CityNew Orleans
Period30/04/202205/05/2022
Internet address

Keywords

  • Crowdsourcing
  • fast-fill
  • autocomplete
  • survey
  • demographics
  • questionnaire

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