What are some real-world examples of drift in AI models?

What are some real-world examples of drift in AI models?

Drift in AI models refers to the degradation of model performance over time due to changes in the underlying data. One example is in credit scoring models, where economic shifts can affect the predictive power of the model.

Can you give me another example?

Sure! In healthcare, a model predicting patient outcomes may experience drift if new treatments or diseases emerge, making previous data less relevant.

How can we detect drift in AI models?

Drift can be detected using statistical tests, monitoring model performance metrics, or comparing the distribution of incoming data against the training data.

What are the consequences of not addressing drift?

If drift is not addressed, it can lead to poor decision-making, increased errors, and ultimately, a loss of trust in the AI system.