How does data bias affect AI decision-making?

What is data bias and how does it impact AI decision-making?

Data bias refers to systematic errors in data that can lead to unfair or inaccurate AI outcomes. It affects decision-making by skewing results based on flawed data.

Can you give me an example of data bias in AI?

Sure! One example is facial recognition technology, which has been shown to misidentify individuals from certain demographic groups due to biased training data.

How can we mitigate data bias in AI systems?

Mitigating data bias involves using diverse datasets, implementing fairness algorithms, and continuously monitoring AI performance to ensure equitable outcomes.

What are the consequences of ignoring data bias in AI?

Ignoring data bias can lead to discriminatory practices, loss of trust in AI systems, and potentially harmful decisions that affect individuals and communities.