Artificial intelligence (AI) is being increasingly adopted in medical research and applications.
Medical AI devices have continuously been approved by the Food and Drug Administration …

As AI systems demonstrate increasingly strong predictive performance, their adoption has
grown in numerous domains. However, in high-stakes domains such as criminal justice and …

Abstract Visual Counterfactual Explanations (VCEs) are an important tool to understand the
decisions of an image classifier. They are “small” but “realistic” semantic changes of the …

Algorithmic approaches to interpreting machine learning models have proliferated in recent
years. We carry out human subject tests that are the first of their kind to isolate the effect of …

Recently, a significant amount of research has been investigated on interpretation of deep
neural networks (DNNs) which are normally processed as black box models. Among the …

There is a growing concern that the recent progress made in AI, especially regarding the
predictive competence of deep learning models, will be undermined by a failure to properly …

In recent years, there has been a rapidly expanding focus on explaining the predictions
made by black-box AI systems that handle image and tabular data. However, considerably …

Influence functions approximate the" influences" of training data-points for test predictions
and have a wide variety of applications. Despite the popularity, their computational cost …

As machine learning methods see greater adoption and implementation in high stakes
applications such as medical image diagnosis, the need for model interpretability and …

Explaining deep learning model inferences is a promising venue for scientific
understanding, improving safety, uncovering hidden biases, evaluating fairness, and …