What are the effects of bias in AI systems?

What are the effects of bias in AI systems?

Bias in AI can lead to unfair treatment, discrimination, and perpetuation of stereotypes in decision-making.

Can you give examples of bias in AI?

Sure! Examples include biased hiring algorithms that favor certain demographics or facial recognition systems that misidentify people of color.

How can we mitigate bias in AI?

Mitigating bias involves diverse training data, regular audits, and involving diverse teams in AI development.

What are the ethical implications of biased AI?

Ethical implications include accountability for harm caused, loss of trust in technology, and potential legal consequences.