AI alignment aims to make AI systems behave in line with human intentions and values. As
AI systems grow more capable, so do risks from misalignment. To provide a comprehensive …

The emergence of Explainable Artificial Intelligence (XAI) has enhanced the lives of humans
and envisioned the concept of smart cities using informed actions, enhanced user …

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 …

The rising popularity of explainable artificial intelligence (XAI) to understand high-performing
black boxes raised the question of how to evaluate explanations of machine learning (ML) …

AI systems are adopted in numerous domains due to their increasingly strong predictive
performance. However, in high-stakes domains such as criminal justice and healthcare, full …

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 …

Machine learning is increasingly used to inform decision making in sensitive situations
where decisions have consequential effects on individuals' lives. In these settings, in …

Predictions obtained by, eg, artificial neural networks have a high accuracy but humans
often perceive the models as black boxes. Insights about the decision making are mostly …

As various post hoc explanation methods are increasingly being leveraged to explain
complex models in high-stakes settings, it becomes critical to develop a deeper …

Deep neural networks have been well-known for their superb handling of various machine
learning and artificial intelligence tasks. However, due to their over-parameterized black-box …