Ethics in AI, AI & the Garbage In, Garbage Out Problem:: Why Data Cleansing is Critical for Responsible AI

In “Ethics in AI, AI & the Garbage In, Garbage Out Problem: Why Data Cleansing is Critical for Responsible AI,” Benjamin Osei provides a comprehensive and accessible guide to understanding the pivotal role of data quality and ethics in artificial intelligence. Designed for beginners and professionals alike, this book explores the fundamentals of AI, the importance of clean data, and the ethical principles essential for responsible AI development.

Key Features:

• Fundamentals of AI: Learn the basic concepts of artificial intelligence, its historical evolution, and the different types of AI.
• The GIGO Problem: Understand the “Garbage In, Garbage Out” problem and its impact on AI systems, emphasizing the critical need for high-quality data.
• Data Cleansing Best Practices: Discover practical steps and techniques for effective data cleansing to ensure accurate, consistent, and unbiased AI outputs.
• Ethical AI Principles: Explore the key ethical considerations in AI, including fairness, transparency, accountability, and societal impact.
• Real-World Case Studies: Gain insights from real-world examples that illustrate the importance of data quality and ethical AI in various industries.

About the Author:

Benjamin Osei is an accomplished Project Manager, seasoned Product Owner, and forward-thinking Chief Technology Officer (CTO) with a diverse background in the finance, energy, and technology sectors. Currently serving as the CTO at CS-Give, LLC and Chief Data Officer at ADRF, Benjamin leads innovative technology strategies and data governance initiatives. His passion for data quality and ethical AI drives his commitment to advancing responsible AI practices.

Why Read This Book:

This book is an essential resource for anyone interested in AI, whether you are a student, data scientist, business leader, or technology enthusiast. With clear explanations, actionable insights, and practical guidance, Benjamin Osei empowers readers to embrace AI responsibly and contribute to building AI systems that are fair, transparent, and accountable.