Designing Ethical AI: Addressing Bias and Accessibility

As artificial intelligence becomes deeply integrated into daily life, ensuring these systems are fair, unbiased, and accessible to everyone is a critical responsibility. This text-only course provides a clear, foundational pathway to understanding how AI bias develops, how it impacts individuals with disabilities, and how you can design more inclusive technology. By reading through our structured explanations and practical scenarios, you will transition from understanding basic ethical principles to actively identifying and mitigating biases in AI models. You will gain the confidence to analyze systems through the lens of accessibility and modern compliance standards. What you'll learn: - Understand the core definitions of algorithmic bias, fairness, and ethical AI. - Identify how machine learning datasets and design choices can unintentionally exclude users with disabilities. - Apply inclusive design principles to create accessible AI interfaces and workflows. - Navigate key legal and regulatory frameworks, including the Americans with Disabilities Act (ADA) and emerging global standards. - Evaluate AI models for bias using modern fairness metrics and assessment techniques. - Implement mitigation strategies to improve representation and accessibility in training data. We begin with the essential terminology of AI ethics and the mechanics of algorithmic bias before moving into the practical intersection of AI and accessibility. You will explore real-world scenarios, review design patterns for inclusive data preparation, and learn how to align your projects with modern compliance standards. This course is designed for beginners, including product managers, developers, designers, and tech enthusiasts who want to build fairer technology. No prior background in artificial intelligence or data science is required. Start reading today to build a solid foundation in ethical AI and inclusive design.