Atelier: Repurposing Expert Crowdsourcing Tasks as Micro-internships
This addresses career advancement challenges for crowd workers, though it is an incremental application of mentorship to an existing platform.
The paper tackles the problem of skill development barriers for workers on expert crowdsourcing marketplaces by repurposing tasks as mentored micro-internships, resulting in Atelier helping interns maintain progress and absorb best practices in a field experiment.
Expert crowdsourcing marketplaces have untapped potential to empower workers' career and skill development. Currently, many workers cannot afford to invest the time and sacrifice the earnings required to learn a new skill, and a lack of experience makes it difficult to get job offers even if they do. In this paper, we seek to lower the threshold to skill development by repurposing existing tasks on the marketplace as mentored, paid, real-world work experiences, which we refer to as micro-internships. We instantiate this idea in Atelier, a micro-internship platform that connects crowd interns with crowd mentors. Atelier guides mentor-intern pairs to break down expert crowdsourcing tasks into milestones, review intermediate output, and problem-solve together. We conducted a field experiment comparing Atelier's mentorship model to a non-mentored alternative on a real-world programming crowdsourcing task, finding that Atelier helped interns maintain forward progress and absorb best practices.