£179.99

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Springer Fairness in Language Models - AI Theory & Algorithms

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Description

Explore the critical intersection of fairness and artificial intelligence with this comprehensive guide from Springer's Foundations, Theory, and Algorithms series. This book examines how language models can perpetuate bias and discrimination, and presents theoretical frameworks and practical approaches for building fairer AI systems. Designed for researchers, practitioners, and students in machine learning and AI ethics, the text combines foundational concepts with advanced algorithmic solutions. Whether you're developing language models, implementing AI systems, or studying AI policy, this resource provides the essential knowledge needed to understand and address fairness challenges in modern language technologies. Ideal for those seeking to align AI development with ethical principles and responsible deployment practices.

Key Features

Part of Springer's authoritative Artificial Intelligence: Foundations, Theory, and Algorithms series, establishing credibility in academic and professional AI research.

Addresses fairness issues specific to language models, covering bias detection, measurement, and mitigation techniques applicable to modern NLP systems.

Combines theoretical foundations with practical algorithms, enabling both conceptual understanding and hands-on implementation of fairness solutions.

Suitable for graduate students, researchers, and AI practitioners who need to incorporate fairness into language model development and deployment.

Published by Springer, a leading academic publisher ensuring peer-reviewed content and rigorous treatment of complex AI ethics topics.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
26 November 2026
Listed Since
07 August 2026

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