Ethics and Bias in Machine Learning: Navigating the Complex Landscape explores one of the most critical and timely challenges in AI today—ensuring that machine learning systems are fair, transparent, and accountable.
This insightful guide goes beyond the code to examine the ethical dilemmas, unintended consequences, and real-world impacts of biased algorithms. Through thought-provoking examples and case studies, you’ll discover how bias enters data, how it shapes outcomes, and what developers, data scientists, and organizations can do to mitigate harm.
Whether you’re a practitioner, policymaker, student, or curious reader, this eBook equips you with the knowledge and tools to build responsible AI systems that serve society ethically and equitably
