Presentation
An Agent-Based Model of GenAI in Creative Writing: Novelty Gains and Diversity Declines
DescriptionGenerative artificial intelligence (GenAI) is being rapidly adopted in education. Its effects on creativity unfold at both individual and collective levels. We develop an agent-based model that represents students' creative outputs in a two-dimensional idea space to examine how GenAI assistance in creative writing shapes individual creativity and classroom-level idea diversity. Simulations show that GenAI increases individual creativity, with disproportionately larger gains for less creative students, while reducing collective diversity through idea homogenization. Critically, the model reveals a more nuanced, non-linear pattern of collective diversity than empirical accounts of homogenization alone: collective diversity can increase at low-to-moderate adoption rates before reaching a tipping point and declining at high adoption rates. These findings highlight the need to evaluate GenAI in education using both individual performance metrics and collective system outcomes.
Event Type
Lecture
TimeTuesday, October 20th5:10pm - 5:30pm PDT
Location