Exposing Ground Truth Illusion in Annotations
β‘ 30-Second TL;DR
What Changed
'ground truth' critiqued as positivistic fallacy ignoring human subjectivity
Why It Matters
ML researchers and data annotators benefit by acknowledging subjectivity, reducing overconfidence in labels. It matters for building fairer AI by challenging Western-centric biases, potentially improving model robustness worldwide. Adoption could shift industry from singular truths to diverse perspectives, enhancing reliability in high-stakes applications.
What To Do Next
Evaluate benchmark claims against your own use cases before adoption.
Key Points
- β’'ground truth' critiqued as positivistic fallacy ignoring human subjectivity
- β’346 papers from top venues analyzed revealing anchoring and geographic hegemony biases
- β’roadmap proposed for pluralistic infrastructures embracing annotation disagreement
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Original source: ArXiv AI β
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