What are some examples of bias in data?

What are some examples of bias in data?

Bias in data can occur in various forms, such as selection bias, confirmation bias, and measurement bias. For instance, if a dataset used for training an AI model predominantly includes data from one demographic, the model may not perform well for others.

Can you explain selection bias?

Selection bias happens when the sample data is not representative of the population. For example, if a survey about health is conducted only among gym-goers, the results may not reflect the health status of the general population.

What impact does bias in data have on AI models?

Bias in data can lead to unfair or inaccurate AI models, resulting in discrimination or poor decision-making. For example, biased hiring algorithms may favor certain demographics over others.

How can we mitigate bias in data?

To mitigate bias, we can ensure diverse data collection, regularly audit datasets for fairness, and use techniques like re-weighting to balance the data.