{ "item_title" : "Beyond Feature Attribution", "item_author" : [" Maher Asaad Baker "], "item_description" : "The most powerful artificial intelligence systems on Earth have become entirely incomprehensible to us. Deep neural networks that diagnose diseases, generate art, and make life-altering decisions operate inside an impenetrable black box-and the tools we built to explain them are dangerously flawed. This book exposes the uncomfortable truth behind Explainable AI. SHAP and LIME, the darlings of the field, don't actually explain how AI thinks; they generate plausible rationalizations that can change with the slightest input variation. When a model denies a loan or misdiagnoses a patient, post-hoc explanations provide little more than comforting illusions. But the crisis is deepening. Generative AI-transformers, diffusion models, multimodal systems-doesn't just classify the world; it dreams it into existence through stochastic, probabilistic journeys. You cannot explain a dream with static feature weights. This is a bold call for a new era: XAI 2.0. Moving beyond fragile approximations to process-aware transparency. Building explanations that align with human cognition, respect cognitive limits, and calibrate trust rather than manufacture compliance. Navigating the complexity of multimodal data while exposing hidden biases. Essential reading for AI practitioners, policymakers, and anyone who wants to understand how we can build systems that are not just intelligent-but truly trustworthy.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/99/935/356/9999353568_b.jpg", "price_data" : { "retail_price" : "54.50", "online_price" : "54.50", "our_price" : "54.50", "club_price" : "54.50", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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