Building trust in AI: Transparent models for better decisions

AI is becoming a part of our daily lives, from approving loans to diagnosing diseases. AI model outputs are used to make increasingly important decisions, based on smart algorithms and data. But if we can't understand these decisions, how can we trust them? One approach to making AI decisions more understandable is to use models that are inherently interpretable. These are models that are designed in such a way that consumers of the model outputs can infer the model's behaviour by reading the parameters of the model. Popular inherently interpretable models include Decision Trees and Linear Regression.