kaal:claim:5095633-018

The centralized frameworks used by the leading annotation companies, including Scale AI, Appen, Hive, V7 Labs, CloudFactory, and Sama, carry theoretical and practical shortcomings around bias, ethical sourcing, and data diversity that undermine the equitability and generalizability of the resulting AI models.

Source quote, verbatim
These challenges involve issues of bias, ethical data sourcing, and data diversity, each of which can undermine the equitability and generalizability of resulting AI models.
From

Wulf A. Kaal, Artificial Intelligence The Final Frontier (2025), 4. Shortcomings of Centralized Data Optimization for AI models, p. 12
https://ssrn.com/abstract=5095633 · source PDF

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

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failuresupport: arguedfailure: centralized annotation shortcomingsfamily: recentralization-driftdecentralization

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