Prototype Tasks: Improving Crowdsourcing Results through Rapid, Iterative Task Design

TL;DR

This paper introduces prototype tasks, a rapid iterative design process for crowdsourcing tasks that improves result quality by enabling requesters to refine task instructions based on worker feedback before full deployment.

Contribution

It presents a novel iterative task design method that involves launching sample tasks and incorporating worker feedback to enhance quality in crowdsourcing.

Findings

Prototype tasks lead to higher-quality results.

Iterative design improves task clarity and worker understanding.

Requester involvement significantly impacts output quality.

Abstract

Low-quality results have been a long-standing problem on microtask crowdsourcing platforms, driving away requesters and justifying low wages for workers. To date, workers have been blamed for low-quality results: they are said to make as little effort as possible, do not pay attention to detail, and lack expertise. In this paper, we hypothesize that requesters may also be responsible for low-quality work: they launch unclear task designs that confuse even earnest workers, under-specify edge cases, and neglect to include examples. We introduce prototype tasks, a crowdsourcing strategy requiring all new task designs to launch a small number of sample tasks. Workers attempt these tasks and leave feedback, enabling the re- quester to iterate on the design before publishing it. We report a field experiment in which tasks that underwent prototype task iteration produced higher-quality work results than the original task designs. With this research, we suggest that a simple and rapid iteration cycle can improve crowd work, and we provide empirical evidence that requester "quality" directly impacts result quality.