Ethics in Big Data and Artificial Intelligence

As artificial intelligence and big data increasingly shape our daily lives, understanding their ethical implications is no longer optional. This course provides a foundational guide to navigating the complex intersection of computational power, data collection, and human values. You will transition from a passive observer of technology to an active, informed evaluator of digital systems. By exploring real-world scenarios and critical dilemmas, you will gain the vocabulary and frameworks needed to analyze data practices and advocate for responsible, human-centric AI development. What you'll learn: - Understand the foundational concepts of big data, machine learning, and artificial intelligence. - Analyze the ethical challenges of data collection, including user consent and digital surveillance. - Identify algorithmic bias and explore modern techniques for mitigation in automated systems. - Evaluate privacy-preserving concepts such as differential privacy and secure data storage. - Apply ethical frameworks to modern AI technologies, including generative models and large language systems. - Examine the future societal impacts of AI safety, alignment, and governance. The course begins by establishing essential definitions and the history of the digital revolution before diving into the core ethical dimensions of privacy, bias, and accountability. You will progress through structured written readings and conceptual exercises that challenge you to apply these principles to modern technological dilemmas. This course is designed for absolute beginners, professionals, and curious citizens who want to understand the impact of technology on society, requiring no prior programming or mathematical background. Equip yourself with the knowledge to help build a fairer, more ethical digital future.