The most successful Machine Learning (ML) systems remain complex black boxes to end-
users, and even experts are often unable to understand the rationale behind their decisions …

ABSTRACT The World Health Organisation has emphasised that misinformation–spreading
rapidly through social media–poses a serious threat to the COVID-19 response. Drawing …

AI-assisted decision-making that impacts individuals raises critical questions about
transparency and fairness in artificial intelligence (AI). Much research has highlighted the …

AI systems are being deployed to support human decision making in high-stakes domains
such as healthcare and criminal justice. In many cases, the human and AI form a team, in …

Many experts have emphasised that chatbots are not sufficiently mature to be able to
technically diagnose patient conditions or replace the judgements of health professionals …

Although promising results of high-performance AI algorithms have been reported in recent
predictive maintenance researches, most of the existing studies merely deal with AI-only …

We propose a theoretical model based on the judge-advisor system (JAS) and empirically
examine how algorithmic advice, compared to identical advice from humans, influences …

Increasingly, artificial intelligence (AI) is being used to assist complex decision-making such
as financial investing. However, there are concerns regarding the black-box nature of AI …

This paper contributes with a pragmatic evaluation framework for explainable Machine
Learning (ML) models for clinical decision support. The study revealed a more nuanced role …

Intelligent everyday applications typically rely on automated Recommender Systems (RS) to
generate recommendations that help users make decisions among a large number of …