The interdisciplinary field of explainable artificial intelligence (XAI) aims to foster human
understanding of black-box machine learning models through explanation-generating …

Convolutional neural networks (CNNs) offer great machine learning performance over a
range of applications, but their operation is hard to interpret, even for experts. Various …

Explainability is a hot topic nowadays for artificial intelligent (AI) systems. The role of
machine learning (ML) models on influencing human decisions shed light on the back-box …

Saliency maps can explain how deep neural networks classify images. But are they actually
useful for humans? The present systematic review of 68 user studies found that while …

We have become increasingly reliant on recommender systems to help us make decisions
in our daily live. As such, it is becoming essential to explain to users how these systems …

O uso de modelos de previsão cada vez mais complexos tem se tornado comum em uma
variedade de aplicações. Em muitas delas, a opacidade destes modelos representa um …