School of Interactive Computing Ph.D. student Kalesha Bullard does research into helping AI gain basic building blocks for how to learn complex tasks. In one example, she describes the goal of packing a lunch box. What are the things that a robot must know in order to complete that task? The size and shape of fruits or beverages? The heigh or circumference of each object? The depth or surface area of the lunch box itself? Taking inspiration from human learners, including her own time as a teacher and student, Bullard offers some input into how these tasks can be achieved.