DECODING AI BIAS IN MEDICINE Audiobook By Anthony James, Benoit Tano cover art

DECODING AI BIAS IN MEDICINE

How Artificial Intelligence Ignores Traditional, Indigenous, and Holistic Healing

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DECODING AI BIAS IN MEDICINE

By: Anthony James, Benoit Tano
Narrated by: Virtual Voice
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In the groundbreaking book 'DECODING AI BIAS IN MEDICINE,' Dr. Anthony B. James compellingly explores the complex landscape where artificial intelligence meets traditional, indigenous, and holistic healthcare practices. Amid the rapid advancement of AI in medicine, this critical dialogue addresses the overlooked biases embedded within AI systems that often disregard non-Western, traditional, Nave American, and indigenous healing methods, which have thrived for centuries across various cultures worldwide. Through a meticulous examination, Dr. James delves into how AI's algorithmic structures, built predominantly on Western medical data, inherently marginalize other globally recognized and effective health paradigms. The book is structured to methodically unpack the facets of AI integration in healthcare, beginning with an insightful overview of AI's current applications in modern medicine. It examines the nuanced forms of bias present in AI algorithms and how these biases not only affect diagnostic and treatment outcomes but also perpetuate a cycle of cultural insensitivity and exclusion. Dr. James does not stop at highlighting problems but leads us on a profound journey, exploring the historical interactions between colonial medicine practices and indigenous healthcare, and showcasing the systematic marginalization that still echoes today. Particularly compelling are the various case studies derived from real-world scenarios that illustrate AI's frequent failures in recognizing and integrating the wisdom of traditional healing practices. In a bold move, the text shifts towards solutions and advocacy, outlining robust frameworks for the decolonization of medical AI. It lays down innovative strategies to recalibrate AI development with a culturally inclusive mindset, ensuring equitable healthcare for all communities. The closing chapters of the book are dedicated to prospects, emphasizing AI's potential role in fostering a more diverse, ethical, and holistic medical environment. This book is an essential read for AI developers, healthcare professionals, and policymakers, providing the necessary tools and insights to steer AI towards more ethical, inclusive, and holistic applications in global health.
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