Ink: Increasing Worker Agency to Reduce Friction in Hiring Crowd Workers

摘要

The web affords connections by which end-users can receive paid, expert help-such as programming, design, and writing-to reach their goals. While a number of online marketplaces have emerged to facilitate such connections, most end-users do not approach a market to hire an expert when faced with a challenge. To reduce friction in hiring from peer-to-peer expert crowd work markets, we propose Ink, a system that crowd workers can use to showcase their services by embedding tasks inside web tutorials-a common destination for users with information needs. Workers have agency to define and manage tasks, through which users can request their help to review or execute each step of the tutorial, for example, to give feedback on a paper outline, perform a statistical analysis, or host a practice programming interview. In a public deployment, over 25,000 pageviews led 168 tutorial readers to pay crowd workers for their services, most of whom had not previously hired from crowdsourcing marketplaces. A field experiment showed that users were more likely to hire crowd experts when the task was embedded inside the tutorial rather than when they were redirected to the same worker's Upwork profile to hire them. Qualitative analysis of interviews showed that Ink framed hiring expert crowd workers within users' well-established information seeking habits and gave workers more control over their work.