Meeting Summary: Many concepts in our everyday lives exist as continuous spectrums (such as color, sound, gender, and political ideology), but people typically perceive and talk about them in discrete categories (such as red/yellow/green, liberal/conservative/moderate). Although categories are commonly used, we actually have little rigorous understanding of many aspects of categories. In this working group, we will address four major questions about categories: (1) Are categories useful to understand continuous things? (In terms of accuracy, speed, memory, and ease of communication) (2) What is the cost of having additional categories? (3) From an evolutionary perspective, what mechanism creates these categories? (4) What can we learn from how we categorize natural things like color and sound (which we know more about) to help us understand how we categorize other people and ourselves? To examine these questions, we propose approaches comprised of machine learning, human subject experiments, and mechanistic modeling.
Pod A Conference Room
This event is by invitation only.