GENDER AND DIVERSITY POLICY IN AI

This unique compendium explores the crucial role of inclusivity in the development, deployment, and governance of artificial intelligence systems. It addresses the growing ethical and social concerns surrounding the lack of representation in AI, emphasizing how gender and diversity are integral to creating fair, responsible, and innovative technologies.

The book delves into the ethical, social, and economic benefits of promoting diversity in AI teams and research. Covering a wide range of topics, from data biases to global policy frameworks, and through case studies and real-world examples, it illustrates both the successes and challenges in achieving gender and diversity in the field.

This useful reference text is designed for academics, AI professionals, policymakers, and corporate leaders of machine learning and AI, and innovation and technology.

Contents:

• Preface
• About the Authors
• Introduction to Gender, Diversity, and Bias in AI
• Bias and Fairness in AI
• Metrics of Bias and Fairness in AI
• Bias Mitigation and Fair AI
• Tools and Real-World Case Studies
• Current Diversity Policy of AI and Its Regulatory Frameworks
• Gender and Diversity Policy Recommendations
• Bibliography
• Index

Readership: Researchers, professionals, academics and graduate students in machine learning and AI, and innovation and technology.