Building Trust in Algorithms

This chapter examines the critical concept of trust and trustworthiness in algorithms, stressing the importance of being trustworthy over simply wanting to be trusted. It highlights the necessity of rigorous evaluations of AI systems, drawing parallels with drug development, and emphasizes transparency and interpretability in algorithmic models, especially in healthcare. Through real-world examples, the chapter illustrates how personalized explanations can enhance user understanding and improve decision-making in complex environments like breast cancer treatment.