Back to Top


Advanced Identity Representation (AIR) Project


Everyone belongs to social categories based on factors such as musical preference, fashion, gender, or race. Yet, some category members are more central, privileged, or marginalized than others. Membership in such social categories is also dynamic: whether someone is a member or not may change over time, both within and between groups. Chimeria is a system to help people better understand social categorization phenomena such as marginalization and the dynamics of group membership. Chimeria does this through an interactive narrative. Consider the following story on a music-oriented social network: A punk rock music fan decides to listen to a little jazz. She listens to a couple of albums by the jazz musician Thelonious Monk, but however, still continues to post messages only about punk rock. She grows tired of being a punk rocker (who dabbles in jazz on the side), so listens again only to hardcore punk rock music. But now, upon returning back to punk rock, punk rock seems to have lost its luster. She finally decides to forsake punk rock and become a jazz fan...for good. In this story, a central member of a category moves toward the margins of the category, back toward the center, and finally changes categories altogether at the end. This pattern of movement within and between categories is the sort of phenomenon that Chimeria models mathematically. The story could have been one of racial or gender group membership; but for the initial version of Chimeria we have chosen music-related identity as a focus domain. These dynamics of group membership are simulated in Chimeria using an artificial intelligence (AI)-driven interactive story. Users interact with various characters within a novel social networking interface. Based on a player’s musical preferences and decisions in an online conversation, the system dynamically generates an interactive conversation centered upon snippets of music that takes place between the user and the other characters. This interactive conversation, grounded in a sociolinguistics model of conversational narrative, allows an engaging experience in which players may encounter various social category membership phenomena which occur in the real-world.


Online social networks and video games are prevalent in today’s society, and using both video game characters and social networking profiles cam potentially be used to help people better understand others’ experiences, delivering meaningful experiences which enable critical reflection upon one’s identity, and on others’ experiences related to identity. However, merely customizing graphical representations and text fields are insufficient to convey the richness of our real world identities.

AIR Toolkit Development

AIR Toolkit Development

The Advanced Identity Representation (AIR) Project ($535,060/5 years, NSF CAREER Award #0952896) is a new transdisciplinary approach to the problem of designing identity technologies to enable imaginative self-representations and to counter social stigmas by implementing dynamic social identity models grounded in computing and cognitive science.