The Artificial Intelligence (AI) presence in devices and services that have become ubiquitous to our daily lives creates the need to specify development guidelines in order to protect the user’s privacy, rights and to prevent criminal use. As AI models have often become too complex, Explainable Artificial Intelligence (XAI) methods were introduced to allow the understanding of the decision-making process of AI tools. This Chapter investigates aspects related to fairness, trust and privacy of AI implementations, aspects that are often overlooked in XAI method implementation, because they are not critical as interpretability, transparency or robustness, but are becoming important in the light of national and international regulatory considerations. The Chapter creates an overview of existing literature, current and future regulatory space, the advantages and disadvantages of integrating XAI methods and the potential effect on future explainable ethical AI development.