How does data quality affect AI performance?

How does data quality affect AI performance?

Data quality is crucial for AI performance. Poor quality data can lead to inaccurate predictions and biased outcomes.

Can you give examples of poor data quality?

Sure! Examples include missing values, incorrect labels, and outdated information, all of which can skew results.

What are the consequences of using low-quality data?

Using low-quality data can result in unreliable models, decreased trust in AI systems, and potential financial losses.

How can we improve data quality for AI?

Improving data quality involves regular audits, cleaning data, and ensuring diverse and representative datasets.

Is there a way to measure data quality?

Yes, data quality can be measured using metrics like accuracy, completeness, consistency, and timeliness.