Implicit Bias in Crowdsourced Knowledge Graphs
Gianluca Demartini · 2019
Collaborative creation of knowledge is an approach which has been successfully demonstrated by crowdsourcing project like Wikipedia. Similar techniques have recently been adopted for the creation of collaboratively generated Knowledge Graphs like, for example, Wikidata. While such an approach enables the creation of high quality structured content, it also comes with the challenge of introducing contributors’ implicit bias in the generated Knowledge Graph. In this paper, we investigate how paid crowdsourcing can be used to understand contributor bias for controversial facts to be included into collaborative Knowledge Graphs. We propose methods to trace the provenance of crowdsourced fact checking thus enabling bias transparency rather than aiming at eliminating bias from the Knowledge Graph.