AI Bias: Ethical Engineering Fundamentals

As artificial intelligence becomes increasingly integrated into our lives, understanding and addressing bias is paramount. This course provides a foundational yet practical approach to the ethical challenges posed by AI bias. By completing this course, you will gain a clear understanding of what AI bias is, where it originates, and how to apply ethical engineering principles to build more equitable and trustworthy AI solutions. You will be prepared to critically evaluate AI systems and contribute to responsible AI development. What you'll learn: * Understand the various sources and types of bias in AI systems, from data collection to model deployment. * Learn foundational ethical principles and frameworks for guiding responsible AI development. * Apply practical methods to detect and measure bias in datasets and machine learning models, including common fairness metrics. * Implement effective strategies and responsible AI practices for mitigating bias throughout the AI lifecycle. * Practice evaluating AI systems for potential ethical implications and societal impact. This course begins by defining key concepts of AI bias and ethical AI, then progresses through methods for detection and mitigation, concluding with principles for responsible AI development. It is designed for beginners with no prior experience in AI ethics or advanced machine learning. Start your journey to building fair and ethical artificial intelligence today.