As social agents, humans are capable of using motion, facial expressions, audio, and many more complex signals to convey their thoughts and to seamlessly understand and navigate through daily social situations. Given the monumental utility of social signals in daily life, there is extensive work in psychology dedicated towards understanding how we acquire them through developmental processes.

As we leap towards artificial intelligence that interacts more directly with humans, there is an increasing demand for understanding the development of these social abilities to enable richer machine-human interactions. This line of research has improved our understanding of social cognition, and has enabled the generation of life-like interactions with avatars, robots, and other forms of artificial intelligence.

With an improved understanding of social dynamics, we can work towards assistive devices that can preempt your needs, teaching agents that can customize interactions with students based on their nonverbal responses, or navigational robots that can make more informed trajectory decisions based on subtle human body movements.