ISBN: 9781032869773 - debiasing ai: rethinking the intersection of innovation and sustainability (10 Ergebnisse)

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Paperback. Zustand: New. In an era where artificial intelligence (AI) drives unprecedented change, Debiasing AI examines the vital intersection of technology, innovation, and sustainability. This book confronts the pressing challenge of bias in AI systems, exploring its far-reaching implications for fairness, trust, and ethical practices. Through a multidisciplinary lens, the author examines how human biases are embedded in large language models, amplified by coded machine learning, and propagated through trained algorithms. Practical strategies are offered to address these issues, paving the way for the development of more equitable and inclusive AI technologies.With actionable insights, empirical case studies, and theoretical frameworks, Debiasing AI offers a roadmap for designing AI technologies that are not only innovative but also ethically sound and equitable. A must-read for scholars, industry leaders, and policymakers, this book inspires a reimagining of AI's role in creating a fairer and more sustainable future.…

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Zustand: New. 2025. 1st Edition. paperback. . . . . .

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Paperback. Zustand: Brand New. 280 pages. 9.18x6.12x9.21 inches. In Stock.

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Taschenbuch. Zustand: Neu. Debiasing AI | Rethinking the Intersection of Innovation and Sustainability | Donghee Shin | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | Routledge | EAN 9781032869773 | Verantwortliche Person für die EU: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu. …

Paperback. Zustand: New. In an era where artificial intelligence (AI) drives unprecedented change, Debiasing AI examines the vital intersection of technology, innovation, and sustainability. This book confronts the pressing challenge of bias in AI systems, exploring its far-reaching implications for fairness, trust, and ethical practices. Through a multidisciplinary lens, the author examines how human biases are embedded in large language models, amplified by coded machine learning, and propagated through trained algorithms. Practical strategies are offered to address these issues, paving the way for the development of more equitable and inclusive AI technologies.With actionable insights, empirical case studies, and theoretical frameworks, Debiasing AI offers a roadmap for designing AI technologies that are not only innovative but also ethically sound and equitable. A must-read for scholars, industry leaders, and policymakers, this book inspires a reimagining of AI's role in creating a fairer and more sustainable future.…