Recent interest in design through the artificial intelligence (AI) lens is rapidly increasing.
Designers, as a special user group interacting with AI, have received more attention in the …

High prevalence of mental illness and the need for effective mental health care, combined
with recent advances in AI, has led to an increase in explorations of how the field of machine …

Recent advances in AI combine large language models (LLMs) with vision encoders that
bring forward unprecedented technical capabilities to leverage for a wide range of …

As AI-powered systems increasingly mediate consequential decision-making, their
explainability is critical for end-users to take informed and accountable actions. Explanations …

Artificial intelligence (AI) in healthcare has the potential to improve patient outcomes, but
clinician acceptance remains a critical barrier. We developed a novel decision support …

Deep learning algorithms promise to improve clinician workflows and patient outcomes.
However, these gains have yet to be fully demonstrated in real world clinical settings. In this …

Despite the plethora of telehealth applications to assist home-based older adults and
healthcare providers, basic messaging and phone calls are still the most common …

As algorithms become an influential component of government decision-making around the
world, policymakers have debated how governments can attain the benefits of algorithms …

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 …

Recent advances in AI and machine learning (ML) promise significant transformations in the
future delivery of healthcare. Despite a surge in research and development, few works have …