Ruth emphasizes the importance of reliability in AI, particularly in applications like smart cars that must account for various outlier scenarios. She shares her journey into responsible AI, highlighting the practical need for solutions that address fairness in machine learning models, such as identifying biases related to age, gender, and ethnicity through tools like Fairlearn and interpret ML.
