What are some examples of model drift in AI?

What are some examples of model drift in AI?

Model drift occurs when a model's performance degrades over time due to changes in the underlying data. Examples include a recommendation system that becomes less accurate as user preferences change, or a fraud detection model that fails to identify new types of fraudulent behavior.

Can you give me a specific case where this happened?

Sure! One notable case is the Netflix recommendation system, which experienced model drift as viewer preferences shifted over time. They had to continuously update their algorithms to maintain accuracy.

How can we detect model drift?

Model drift can be detected using statistical tests, monitoring performance metrics over time, and comparing the distribution of incoming data to the training data.

What can be done to mitigate model drift?

To mitigate model drift, you can retrain models regularly, use adaptive learning techniques, and implement continuous monitoring to catch drift early.