Network pharmacology is an emerging area of systematic drug research that attempts to
understand drug actions and interactions with multiple targets. Network pharmacology has …

Explanation has been a central feature of AI systems for legal reasoning since their
inception. Recently, the topic of explanation of decisions has taken on a new urgency …

Understanding black box models has become paramount as systems based on opaque
Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response …

While there is a growing effort towards AI for Sustainability (eg towards the sustainable
development goals) it is time to move beyond that and to address the sustainability of …

With automation of routine decisions coupled with more intricate and complex information
architecture operating this automation, concerns are increasing about the trustworthiness of …

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

Research on the ethics of algorithms has grown substantially over the past decade.
Alongside the exponential development and application of machine learning algorithms …

The paper presents an approach for implementing inscrutable (ie, nonexplainable) artificial
intelligence (AI) such as neural networks in an accountable and safe manner in …

The increasing implementation of and reliance on machine-learning (ML) algorithms to
perform tasks, deliver services and make decisions in health and healthcare have made the …

Explainability for artificial intelligence (AI) in medicine is a hotly debated topic. Our paper
presents a review of the key arguments in favor and against explainability for AI-powered …