Ethical Data and AI: Mitigating Bias in Modern Technology

As automated systems and artificial intelligence increasingly shape our daily lives, the data powering these technologies can unintentionally perpetuate harmful biases. Understanding how to identify and address these ethical challenges is no longer optional—it is a critical skill for anyone working with data. This course guides you through the foundational principles of data ethics, helping you transition from a tech enthusiast to an advocate for responsible innovation. You will learn to recognize systemic bias, evaluate algorithmic fairness, and champion ethical decision-making in any data-driven environment. What you'll learn: - Understand the core principles of data ethics and responsible technology design - Identify common sources of racial, gender, and demographic bias in datasets - Apply algorithmic fairness metrics to evaluate model performance and equity - Explore modern AI alignment concepts and ethical frameworks for generative technologies - Formulate actionable strategies to advocate for ethical data practices within organizations The course begins with essential terminology and the history of algorithmic bias, then moves into practical frameworks for analyzing datasets and implementing ethical checks in modern tech workflows. This course is designed for absolute beginners, with no prior programming or data science experience required. It is ideal for aspiring data professionals, product managers, and anyone interested in the social impact of technology. Start reading today to build a fairer, more ethical future for data-driven technologies.