Machine learning-based decision systems have been widely used in a wide range of application domains, like credit score, insurance risk, and health monitoring, in which accuracy is of the utmost importance. Despite their success, their use may present ethical and legal risks, made even more serious and subtly by the opacity of recent decision support systems, which are often complex and their internal logic is usually inaccessible to humans.

Nowadays, most Artificial Intelligence (AI) systems are based on Machine Learning algorithms. The relevance and need for ethics in AI are supported and highlighted by various initiatives from the researchers to provide recommendations and guidelines in making AI-based decision systems explainable and compliant with legal and ethical issues. The challenge to design and develop trustworthy AI-based decision systems is still open and requires a joint effort across technical, legal, sociological, and ethical domains.

The purpose of XKDD, eXplaining Knowledge Discovery in Data Mining, is to encourage principled research that will lead to the advancement of explainable, transparent, ethical, and fair data mining and machine learning. 

The workshop will be held by the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2023.