Complex Behavioral Design and Possible AI-Driven Applications
This lecture will present an advanced framework for behavioral diagnosis to be used in applying behavioral economics to drive complex behavior change in business and policy, particularly in the areas of health behaviors and finance, and show examples of applying AI driven management.
Elements covered: complexity vs. simplicity, behavior units, chain of behaviors, constraints, layers of objectives, time horizons, positive-driver spiral, tangible vision, baseline habits, behavior prompts,
Possible use cases of AI in behavioral design and choice architecture, including management of behavior chain. The technology exists already to manage and personalize complex behavior change. We will discuss practical near-term use cases in complex health and financial situations.
Learning Objectives:
- Understand the theory of complex behavioral change
- Be able to draw up a complex behavioral chain
- Understand the possible application of AI-driven management in making complex behavioral change succeed