Cognitive Artificial Intelligence for Health and Climate: Deep Models, Interpretability, and Decision Support

Abstract

The intersection of health, climate, and artificial intelligence represents both a challenge and an opportunity. This book explores how Cognitive AI — combining deep learning, reasoning, and interpretability — can address pressing issues in healthcare and climate science while supporting trustworthy, informed decision-making. Focusing on deep models, explainable AI, and decision-support frameworks, we examine methods that go beyond automation to enable human–AI collaboration in complex, high-stakes environments. Through research insights and real-world case studies, the book bridges theory and practice for researchers, practitioners, and decision-makers seeking resilient and transparent AI solutions. It is my hope that this work inspires the development of AI systems that are as trustworthy as they are innovative, serving society’s urgent needs with clarity, fairness, and resilience. In writing this book, I have drawn on my own experiences in research, teaching, and collaboration across disciplines, as well as the invaluable contributions of the AI, health, and climate research communities. I am grateful to colleagues, students, and partners whose insights have shaped the ideas presented here. May this work inspire continued exploration into AI systems that serve humanity’s most urgent needs — and do so with clarity, fairness, and resilience.