“Is It Future or Is It Past?”: From Self-contained Microtasks to AI-driven Collaborative Crowdsourcing

Interest in artificial intelligence (AI)-driven crowd work has increased during the last few years as a line of inquiry that expands upon prior research on microtasking to represent a means of scaling up complex tasks through AI mediation. Despite the increasing attention to the macrotask phenomenon in crowdsourcing, there is a need to understand the processes, elements, and constraints underlying the infrastructural and behavioral aspects in such form of crowd work when involving collaboration. To this end, this paper provides a first attempt to characterize some of the research conducted in this direction to identify important paths for an agenda comprising key drivers, challenges, and prospects for integrating human-centered AI in collaborative crowdsourcing environments.

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Published
2025-05-23
DOI
https://doi.org/10.1109/ichora65333.2025.11017036
Primary Topic
Mobile Crowdsensing and Crowdsourcing
Type
article
Field-Weighted Citation Impact
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“Is It Future or Is It Past?”: From Self-contained Microtasks to AI-driven Collaborative Crowdsourcing

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“Is It Future or Is It Past?”: From Self-contained Microtasks to AI-driven Collaborative Crowdsourcing

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article en

Abstract

Interest in artificial intelligence (AI)-driven crowd work has increased during the last few years as a line of inquiry that expands upon prior research on microtasking to represent a means of scaling up complex tasks through AI mediation. Despite the increasing attention to the macrotask phenomenon in crowdsourcing, there is a need to understand the processes, elements, and constraints underlying the infrastructural and behavioral aspects in such form of crowd work when involving collaboration. To this end, this paper provides a first attempt to characterize some of the research conducted in this direction to identify important paths for an agenda comprising key drivers, challenges, and prospects for integrating human-centered AI in collaborative crowdsourcing environments.

Universidade Federal do Rio de Janeiro (BR), University of Trás-os-Montes and Alto Douro (PT), INESC TEC (PT), University of Jyväskylä (FI)
Decent work and economic growth
Openalex Percentile: Top 87%
Mobile Crowdsensing and Crowdsourcing
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