Whose Ground Truth? Accounting for Individual and Collective Identities Underlying Dataset Annotation

Understand

Human annotations play a crucial role in machine learning (ML) research and development.

• However, the ethical considerations around the processes and decisions that go into building ML datasets has not received nearly enough attention.
• In this paper, we survey an array of literature that provides insights into ethical considerations around crowdsourced dataset annotation.
• We synthesize these insights, and lay out the challenges in this space along two layers: (1) who the annotator is, and how the annotators' lived experiences can impact their annotations, and (2) the relationship between the annotators and the crowdsourcing platforms and what that relationship affords them.