kaal:claim:5095633-010

When a training dataset disproportionately represents one region or demographic group, the resulting model produces skewed and sometimes inappropriate outputs once deployed in unfamiliar settings.

For instance, if a dataset disproportionately represents a particular region or demographic group, the model may offer skewed performance, demonstrating suboptimal or inappropriate outputs when deployed in unfamiliar settings.

Wulf A. Kaal, Artificial Intelligence The Final Frontier (2025), 2.1.1. Data Quality and Bias, p. 3
https://ssrn.com/abstract=5095633 · source PDF

Wulf A. Kaal, Artificial Intelligence The Final Frontier (2025). SSRN: https://ssrn.com/abstract=5095633

• deployment context differs from the demographic composition of the training data

mechanismsupport: arguedfailure: representation skewfamily: ai-model-and-training-failureempirical-evidenceresearch-methods

• specializes kaal:claim:4855607-004 Deep learning models adapt to changes in data distribution far less readily than human learning does, which li...

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