5 papers
UbiQVision: Quantifying Uncertainty in XAI for Image Recognition
Akshat Dubey, Aleksandar Anžel, Bahar İlgen +1
Recent advances in deep learning have led to its widespread adoption across diverse domains, including medical imaging. This progress is driven by increasingly sophisticated model…
Human Agency, Causality, and the Human Computer Interface in High-Stakes Artificial Intelligence
Georges Hattab
Current discourse on Artificial Intelligence (AI) ethics, dominated by "trustworthy" and "responsible" AI, overlooks a more fundamental human-computer interaction (HCI) crisis: the…
UbiQTree: Uncertainty Quantification in XAI with Tree Ensembles
Akshat Dubey, Aleksandar Anžel, Bahar İlgen +1
Explainable Artificial Intelligence (XAI) techniques, such as SHapley Additive exPlanations (SHAP), have become essential tools for interpreting complex ensemble tree-based models,…
Toward Human-Centered Readability Evaluation
Bahar Ä°lgen, Georges Hattab
Text simplification is essential for making public health information accessible to diverse populations, including those with limited health literacy. However, commonly used evalua…
PHAX: A Structured Argumentation Framework for User-Centered Explainable AI in Public Health and Biomedical Sciences
Bahar Ä°lgen, Akshat Dubey, Georges Hattab
Ensuring transparency and trust in AI-driven public health and biomedical sciences systems requires more than accurate predictions-it demands explanations that are clear, contextua…