Defaults, Decisions, and Dynamic Systems: Behavioral Science Meets AI
Lis Costa
Hugo Bowne-Anderson
Duncan Gilchrist
HomeEpisodes Subscribe Episode 19 Defaults, Decisions, and Dynamic Systems: Behavioral Science Meets AI Lis Costa, Chief of Innovation and Partnerships at the Behavioural Insights Team, joins High Signal to explore how behavioral science is reshaping public policy, digital platforms, and machine learning. She explains how defaults influence behavior at scale, why personalization and chatbots are unlocking new kinds of interventions, and what happens when AI systems meet real-world complexity. We also discuss the limits of nudging, the promise of boosting, and why building for human decision-making requires more than just good models.
Guest
Lis Costa
Behavioural Insights Team
Key Takeaways
There is no neutral system
Lis explains how every digital product encodes decisions, whether acknowledged or not. From tax letters to chatbot prompts, behavioral architecture is always present.
Defaults drive behavior
Default settings are often the most powerful levers in any system. Pension enrollment, vaccine uptake, and even organ donation outcomes all hinge on them.
Machine learning breaks in dynamic systems
Most ML models are trained on static data, but in the real world, every intervention changes the system. Prediction alone is not enough.
Designing for people means designing for context
Personalization, timing, and delivery all shape how messages land. A message is not just what you say, but how, when, and to whom.
Nudges help, but boosts may last
While nudging improves outcomes in the short term, Lis sees promise in boosting—building long-term decision-making capacity in individuals.
Personalization is no longer optional
Behavioral science is moving from static communications to adaptive tools like chatbots, enabling more effective interventions at scale.
Evidence, not intuition
BIT grounds its work in experimentation. From randomized trials to machine learning models, interventions are tested, not assumed.
Behavioral science belongs in AI development
ML systems shape human behavior, whether intended or not. Ignoring behavioral design undermines effectiveness and trust.
You can read the full transcript here.
0:00 Introduction to Behavioral Science and Machine Learning
00:42 Case Study: Chatbot for Vaccination 02:06 Exploring Behavioral Interventions 03:40 The Behavioral Insights Team 07:33 Nudge Theory and Choice Architecture 13:16 Evolution and Impact of Behavioral Insights 23:24 Combining Behavioral Science with Machine Learning 37:12 Boosting vs. Nudging: Enhancing Decision-Making 48:46 Adapting Behavioral Insights Across Contexts 50:45 Practical Lessons for Data and AI Leaders 52:27 Conclusion and Future Collaborations