AI engineering glossary · AI ethics law product
What is representation bias?
Representation bias: A form of unfairness that arises when some groups are under-represented or poorly covered in the training data, so the model learns their patterns badly and performs worse for them. It is a data-collection problem, fixed by gathering more representative examples rather than by tuning the model alone.
Representation bias: an example
A speech recogniser trained mostly on urban Hindi speakers makes far more errors on Bhojpuri-accented speech because it saw few such recordings.
Related terms
- Algorithmic bias
- Sampling bias
- Historical bias
- Intersectional fairness
More AI ethics law product terms
- Responsible AI
- Retention rate
- Right of access
- Right to erasure
- Right to explanation
- Saliency map
- Sensitive personal data
- Shadow mode
Where you learn it
Representation bias is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.