Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs
Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs
As the use of machine learning (ML) models in product development and data-driven decision-making processes became pervasive in many domains, people's focus on building a well-performing model has increasingly shifted to understanding how their model works. While scholarly interest in model interpretability has grown rapidly in research communities like HCI, …