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Aprašymas

Provides an overview of the challenges and opportunities presented by AI across the insurance value chain. As insurers rapidly integrate machine learning, deep learning, and predictive analytics into underwriting, claims processing, fraud detection, and pricing, the need for robust ethical frameworks and responsible AI governance has become paramount. The book serves as a foundational guide for developing AI systems in insurance that are not only efficient but also equitable and socially responsible.

Algorithmic structures and data pipelines that shape modern insurance systems, that review potential sources of bias, opacity, and inequality are examined. The book addresses technical, legal, and organizational dimensions of ethical AI adoption-ranging from explainability and accountability mechanisms to data privacy, informed consent, and inclusion.

The book is targeted at professionals, scholars, data scientists, actuaries, and policymakers.