Abstract
The success of crowdsourcing markets is dependent on a
strong foundation of trust between workers and requesters. In current marketplaces, workers and requesters are often unable to trust each other’s quality, and their mental models of tasks are misaligned due to ambiguous instructions or confusing edge cases.
This breakdown of trust typically arises from (1) flawed reputation systems which do not accurately reflect worker and requester quality, and from (2) poorly designed tasks. In this demo, we present how Boomerang and Prototype Tasks, the fundamental building blocks of the Daemo crowdsourcing marketplace, help restore trust between workers and requesters. Daemo’s Boomerang reputation system incentivizes alignment between opinion and ratings by determining the likelihood that workers and requesters will work together in the future based on how they rate each other. Daemo’s Prototype tasks require that new tasks go through a feedback iteration phase with a small number of workers so that requesters can revise their instructions and task designs before launch.
strong foundation of trust between workers and requesters. In current marketplaces, workers and requesters are often unable to trust each other’s quality, and their mental models of tasks are misaligned due to ambiguous instructions or confusing edge cases.
This breakdown of trust typically arises from (1) flawed reputation systems which do not accurately reflect worker and requester quality, and from (2) poorly designed tasks. In this demo, we present how Boomerang and Prototype Tasks, the fundamental building blocks of the Daemo crowdsourcing marketplace, help restore trust between workers and requesters. Daemo’s Boomerang reputation system incentivizes alignment between opinion and ratings by determining the likelihood that workers and requesters will work together in the future based on how they rate each other. Daemo’s Prototype tasks require that new tasks go through a feedback iteration phase with a small number of workers so that requesters can revise their instructions and task designs before launch.
| Original language | English |
|---|---|
| Title of host publication | CSCW '17 Companion: Companion of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing |
| Publisher | Association for Computing Machinery |
| ISBN (Print) | 9781450346887 |
| DOIs | |
| Publication status | Published - Feb 2017 |
Keywords
- Crowdsourcing
- Human computation
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