Why is data quality important in AI systems?

High-quality data is crucial in AI systems because it directly influences the accuracy and effectiveness of the models being developed. When a model is trained on high-quality data—meaning the data is accurate, relevant, and representative—it enables the model to learn patterns and relationships that reflect reality. This leads to better predictions and more reliable outcomes.

In contrast, poor data quality can introduce noise, biases, and inaccuracies, which ultimately degrade the model's performance. Even if a model is complex or has access to large amounts of data, if that data is flawed or not of high quality, the results can be misleading or entirely incorrect. Therefore, the importance of high-quality data cannot be understated, as it serves as the foundation upon which successful AI systems are built.