Explainable, Interpretable, and Transparent AI Systems by B.K. Tripathy Hardcove

Explainable, Interpretable, and Transparent AI Systems by B.K. Tripathy Hardcove

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In the book “Explainable, Interpretable, and Transparent AI Systems” by B.K. Tripathy, readers are taken on a journey into the world of artificial intelligence and the importance of creating systems that are not only powerful and efficient, but also understandable and accountable.

Tripathy delves into the complexities of AI systems and the potential risks and challenges they pose if they are not transparent and interpretable. He emphasizes the need for AI systems to be explainable in order for users to trust and rely on them, as well as to comply with regulations and ethical standards.

Through practical examples and case studies, Tripathy illustrates the benefits of implementing explainable AI systems, such as improved decision-making, increased user trust, and enhanced accountability. He also discusses various techniques and methods for making AI systems more interpretable, such as feature importance analysis, model explanation tools, and transparency frameworks.

Overall, “Explainable, Interpretable, and Transparent AI Systems” serves as a comprehensive guide for developers, researchers, and policymakers looking to design AI systems that prioritize transparency and accountability. It is a must-read for anyone interested in the future of AI and the ethical implications of its widespread adoption.
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