The growing complexity of software systems and the influence of software-supported
decisions in our society awoke the need for software that is transparent, accountable, and …

This article attempts to bridge the gap between widely discussed ethical principles of Human-
centered AI (HCAI) and practical steps for effective governance. Since HCAI systems are …

Abstract Previous research in Explainable Artificial Intelligence (XAI) suggests that a main
aim of explainability approaches is to satisfy specific interests, goals, expectations, needs …

Providing user-understandable explanations to justify recommendations could help users
better understand the recommended items, increase the system's ease of use, and gain …

Personalization of natural language generation plays a vital role in a large spectrum of
tasks, such as explainable recommendation, review summarization and dialog systems. In …

Researchers have developed a variety of approaches to evaluate explainable artificial
intelligence (XAI) systems using human–computer interaction (HCI) user‐centered …

Recently, requirements for the explainability of software systems have gained prominence.
One of the primary motivators for such requirements is that explainability is expected to …

Research in the social sciences has shown that expectations are an important factor in
explanations as used between humans: rather than explaining the cause of an event per se …

The growing complexity of software systems and the influence of software-supported
decisions in our society sparked the need for software that is transparent, accountable, and …

Explanations in artificial intelligence (AI) ensure that users of complex AI systems
understand why the system behaves as it does. Expectations that users may have about the …