Investigating Societal Biases in a Poetry Composition System

Understand

There is a growing collection of work analyzing and mitigating societal biases in language understanding, generation, and retrieval tasks, though examining biases in creative tasks remains underexplored.

• Creative language applications are meant for direct interaction with users, so it is important to quantify and mitigate societal biases in these applications.
• We introduce a novel study on a pipeline to mitigate societal biases when retrieving next verse suggestions in a poetry composition system.
• Our results suggest that data augmentation through sentiment style transfer has potential for mitigating societal biases.