What is data bias?

What is data bias?

Data bias refers to systematic errors in data collection, analysis, or interpretation that can lead to misleading conclusions.

Can you give me an example of data bias?

Sure! An example is when a facial recognition system is trained mostly on images of light-skinned individuals, leading to poor performance on darker-skinned faces.

How can we reduce data bias?

To reduce data bias, ensure diverse data representation, regularly audit datasets, and apply fairness algorithms during analysis.

What are the consequences of data bias?

Consequences include unfair treatment in AI applications, perpetuation of stereotypes, and loss of trust in technology.