What is bias in AI models?

What is bias in AI models?

Bias in AI models refers to systematic errors that lead to unfair outcomes, often due to skewed training data.

How does bias affect decision-making in AI?

Bias can lead to discriminatory practices, affecting decisions in hiring, lending, and law enforcement.

Can bias be eliminated from AI models?

While it may not be possible to completely eliminate bias, it can be reduced through careful data selection and model training.

What are some examples of biased AI systems?

Examples include facial recognition systems that misidentify people of color and hiring algorithms that favor certain demographics.

How can we ensure fairness in AI?

Ensuring fairness involves diverse data representation, regular audits, and involving stakeholders in the development process.