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Modeling A Human-AI Cooperation Task In ACT-R

Authors
Chris Dancy
The Pennslyvania State Universtiy, University Park ~ Industrial and Manufacturing Engineering, Computer Science and Engineering, African American Studies
Tanishca Sanjay Dwivedi
The Pennslyvania State Universtiy, University Park ~ Industrial and Manufacturing Engineering
Abstract

How can we model the ways race-based systems of power and oppression impact the ways people interact with AI agents? To approach this question, we are developing a computational model of a human-AI interaction study that explores the impact of racialization on such interactions. We’re developing an ACT-R model that connects with the existing study infrastructure and code to complete the Pig Chase task (a modified version of the Stag hunt task) using NodeJS. Connecting the existing Pig Chase Environment to ACT-R provides us with an opportunity to understand and in turn lay out the process of recognizing the steps taken to make certain decisions, particularly without creating another environment, something that can be especially time consuming for the computational cognitive modeling process. To develop a more complete simulation of related human behavior with greater resolution, we are developing a connection between ConceptNet and ACT-R. Integrating it with our model will provide the model with existing historical and sociocultural perspectives and provides us with a more realistic ability to understand the interaction between the user and the environment after it has the knowledge of the race of the AI agent.

Tags

Keywords

ACT-R
Conceptnet
Human-AI Cooperation
Pig Chase
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Cite this as:

Dancy, C. L., & Dwivedi, T. (2023, July). Modeling A Human-AI Cooperation Task In ACT-R. Abstract published at MathPsych/ICCM/EMPG 2023. Via mathpsych.org/presentation/1228.