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Is your AI product actually working? How to develop the right metric system
Metrics are critical for determining AI product performance. But where to begin? Here's a framework to apply across various use cases.
With such a complex web of interdependencies among internal and external customers, choosing the right metrics to capture the impact of the product was critical to steer it towards success. The risk of having multiple flavors of an ‘accuracy’ or ‘quality’ metric is that everyone will develop their own version, leading to a scenario where you might not all be working toward the same outcome. However, in some instances (like question 3 above) especially for ML based products, you have the option of manual or automated evaluations that assess the model outputs.
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