Designing Complementary Intelligence: Cognitive Foundations for Human–AI Teaming

The next frontier in AI is not building ever more powerful models, but creating complementary intelligence between humans and machines. This talk explores how computational cognitive models can guide the design of AI systems that enhance rather than replace human decision-making. I introduce the concept of Cognitive AI—AI grounded in models of human cognitive processes such as learning, memory, and decision making—and contrast it with the large-scale optimization focus of Machine AI. I argue that integrating these complementary paradigms provides a foundation for effective human–AI teaming. Through shared representations, human-guided learning, and coevolution, Cognitive AI can align with human preferences, support judgment under uncertainty, and enable adaptive collaboration in dynamic environments. I will present examples from decision-making, human–AI teaming, and applications that illustrate how cognitive models can move beyond explaining human behavior to designing AI systems that collaborate effectively with people.