2022
COLING
COLING 2022
Developing a tool for fair and reproducible use of paid crowdsourcing in the digital humanities
Abstract
AbstractThis system demonstration paper describes ongoing work on a tool for fair and reproducible use of paid crowdsourcing in the digital humanities. Paid crowdsourcing is widely used in natural language processing and computer vision, but has been rarely applied in the digital humanities due to ethical concerns. We discuss concerns associated with paid crowdsourcing and describe how we seek to mitigate them in designing the tool and crowdsourcing pipelines. We demonstrate how the tool may be used to create annotations for diagrams, a complex mode of expression whose description requires human input.
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Keyword Pioneer
— paid crowdsourcing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Data Science & Analytics, Deep Learning, Interdisciplinary, Machine Learning, Natural Language Processing, Speech & Audio