Artificial Intelligence and Human Decisions

Catalog description

This course explores how humans and intelligent systems make decisions, with a focus on the opportunities and risks of AI-driven decision technologies in shaping judgment and action. Students begin by examining the foundations of decision-making and the role of AI across domains such as data collection, data quality, and visualization. Core approaches in statistical learning and machine learning are introduced, including methods for pattern discovery, prediction, and model evaluation, reinforced through weekly laboratory coding practicals in a data science computing environment. Building on these methods, the course considers how AI systems interact with human decision-makers, covering topics such as collaborative intelligence, auditing for bias, and ethical frameworks for responsible deployment. Advanced sessions highlight emerging adaptive systems that learn, optimize, and respond in uncertain environments. By the end of the course, students will be able to apply core AI methods, while critically assessing their ethical and societal implications.