AI engineering glossary · AI ethics law product
What is algorithmic bias?
Algorithmic bias (also called AI bias, machine learning bias): Systematic and repeatable errors in an automated system that lead to unfair outcomes for particular people or groups, such as giving one group worse loan terms or lower hiring scores. It usually comes from skewed training data, flawed labels or design choices rather than from any deliberate intent, which is why it must be measured.
Algorithmic bias: an example
A resume-screening model trained on ten years of past hires from a mostly male team scores women's resumes lower, even though gender was never an input column.
Related terms
More AI ethics law product terms
- Algorithmic impact assessment
- Algorithmic recourse
- Anonymization
- Automated decision-making
- Automation bias
- Bias audit
- Bias mitigation
- Black-box model
Where you learn it
Algorithmic 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.