# How do we eliminate bias and discrimination in AI training data?

_Last updated: 2026-07-20_  
_Reviewed by: Jason Burns, Editorial Steward_  
_Published by: AIDirectAnswers.com · Licensed under Citation License 1.0_

## Short answer

You cannot fully eliminate bias — training data reflects the world — but you can reduce and manage it by auditing datasets, balancing representation, documenting data provenance, testing outputs across demographic slices, and building human review into high-stakes decisions. As Fei-Fei Li, put it on the record: "There's nothing artificial about AI. It's inspired by people, it's created by people, and—most importantly—it impacts people."

## Sources

- [undefined](https://hai.stanford.edu/news/nothing-artificial-about-ai)

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_Author: [Jason Burns](https://www.linkedin.com/in/jason-randolph-burns), Editorial Steward_  
_Published: 2026-07-20 · Modified: 2026-07-20_  
_License: [Citation License 1.0](https://aidirectanswers.com/license)_  
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