Generative AI (GenAI) represents a shift from AI's ability to “recognize” to its ability to
“generate” solutions for a wide range of tasks. As generated solutions and applications grow …

The deployment of systems of artificial intelligence (AI) in high-risk settings warrants the
need for trustworthy AI. This crucial requirement is highlighted by recent EU guidelines and …

Decision trees (DTs) epitomize the ideal of interpretability of machine learning (ML) models.
The interpretability of decision trees motivates explainability approaches by so-called …

The last decade witnessed an ever-increasing stream of successes in Machine Learning
(ML). These successes offer clear evidence that ML is bound to become pervasive in a wide …

Straight Choices provides a fascinating introduction to the psychology of decision making,
enhanced by discussion of relevant examples of decision problems faced in everyday life …

A widespread need to explain the behavior and outcomes of AI-based systems has
emerged, due to their ubiquitous presence. Thus, providing renewed momentum to the …

Recent years witnessed a number of proposals for the use of the so-called interpretable
models in specific application domains. These include high-risk, but also safety-critical …

Crowdsourced data streams are popular and extremely valuable in several domains,
namely in tourism. Tourism crowdsourcing platforms rely on past tourist and business inputs …

Natural interaction with recommendation and personalized search systems has received
tremendous attention in recent years. We focus on the challenge of supporting people's …

In a recommender system, a user's interaction is often biased by the items' displaying
positions and popularity, as well as the user's self-selection. Most existing recommendation …