The rapid growth and use of artificial intelligence (AI)-based systems have raised concerns
regarding explainability. Recent studies have discussed the emerging demand for …

Explainability is motivated by the lack of transparency of black-box Machine Learning
approaches, which do not foster trust and acceptance of Machine Learning algorithms. This …

The recent developments of machine learning (ML) approaches within artificial intelligence
(AI) systems often require explainability of ML models. In order to establish trust in these …

Abstract Explainable Artificial Intelligence (XAI) aims to bridge the understanding between
decisions made by an AI interface and the user interacting with the AI. When the goal of the …

With the proliferation of Artificial Intelligence-based systems, several questions arise
involving ethical principles. In addition, the human-centered approach takes the focus on the …

With advancements in natural language processing and understanding, conversational
agents (CAs) have become one of the fundamental modes of human-computer interaction …

This paper describes the conception, design, and first evaluation attempts of a learning lab
on artificial intelligence (AI). The learning lab, which consists of 25 learning activities, aims to …

Exploring end-users' understanding of Artificial Intelligence (AI) systems' behaviours and
outputs is crucial in developing accessible Explainable Artificial Intelligence (XAI) solutions …

The recent developments of machine learning (ML) approaches within artificial intelligence
(AI) systems often require explainability of ML models. In order to establish trust in these …