Explainable artificial intelligence: a comprehensive review
Thanks to the exponential growth in computing power and vast amounts of data, artificial
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
A systematic review of explainable artificial intelligence in terms of different application domains and tasks
Artificial intelligence (AI) and machine learning (ML) have recently been radically improved
and are now being employed in almost every application domain to develop automated or …
and are now being employed in almost every application domain to develop automated or …
[HTML][HTML] Connecting the dots in trustworthy Artificial Intelligence: From AI principles, ethics, and key requirements to responsible AI systems and regulation
Abstract Trustworthy Artificial Intelligence (AI) is based on seven technical requirements
sustained over three main pillars that should be met throughout the system's entire life cycle …
sustained over three main pillars that should be met throughout the system's entire life cycle …
Explanations can reduce overreliance on ai systems during decision-making
Prior work has identified a resilient phenomenon that threatens the performance of human-
AI decision-making teams: overreliance, when people agree with an AI, even when it is …
AI decision-making teams: overreliance, when people agree with an AI, even when it is …
Explainable ai is dead, long live explainable ai! hypothesis-driven decision support using evaluative ai
In this paper, we argue for a paradigm shift from the current model of explainable artificial
intelligence (XAI), which may be counter-productive to better human decision making. In …
intelligence (XAI), which may be counter-productive to better human decision making. In …
Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability
Abstract Machine learning algorithms enable advanced decision making in contemporary
intelligent systems. Research indicates that there is a tradeoff between their model …
intelligent systems. Research indicates that there is a tradeoff between their model …
How to explain AI systems to end users: a systematic literature review and research agenda
Purpose Inscrutable machine learning (ML) models are part of increasingly many
information systems. Understanding how these models behave, and what their output is …
information systems. Understanding how these models behave, and what their output is …
Recent advances in trustworthy explainable artificial intelligence: Status, challenges, and perspectives
Artificial intelligence (AI) and machine learning (ML) have come a long way from the earlier
days of conceptual theories, to being an integral part of today's technological society. Rapid …
days of conceptual theories, to being an integral part of today's technological society. Rapid …
Counterfactuals and causability in explainable artificial intelligence: Theory, algorithms, and applications
Deep learning models have achieved high performance across different domains, such as
medical decision-making, autonomous vehicles, decision support systems, among many …
medical decision-making, autonomous vehicles, decision support systems, among many …
[HTML][HTML] Effects of Explainable Artificial Intelligence on trust and human behavior in a high-risk decision task
Understanding the recommendations of an artificial intelligence (AI) based assistant for
decision-making is especially important in high-risk tasks, such as deciding whether a …
decision-making is especially important in high-risk tasks, such as deciding whether a …