From public health to global security, leaders face high-stakes decisions under deep uncertainty. Navigating these challenges requires understanding how human judgment operates—where it is deeply valuable and where it is systematically prone to error. As machine intelligence takes on a growing role in routine analysis and prediction, the quality of human judgment becomes increasingly consequential.
Drawing on research from psychological science, behavioral economics, neuroscience, and ethics, this course provides a scientific foundation for improving decisions by revealing how people perceive risk, interpret information, and make choices. By integrating theory with practice, students learn to anticipate behavioral responses and design policies and communications that achieve their intended effects. A central component of the course is the analysis and redesign of real-world choice architectures to improve clarity, accessibility, and decision quality while preserving individual agency.
Students will leave the course with a structured approach to improving judgment and decision-making in organizations and public policy.
There are no formal prerequisites. However, prior courses in psychology, behavioral economics (including MLD-304*), and/or statistics may be helpful. For HKS students, the course qualifies for the HKS Data and Research Methods Track as well as the Certificate in Management, Leadership, and Decision Science. Cross registrants are welcome. No auditors are permitted, unfortunately. * While some overlap between MLD-308 and MLD-304 is intentionally included, each course also covers a set of novel topics not covered in the other. Thus, students may take each one before the other.