40228 - Education and Stratification in the AI Era

Description

Generative artificial intelligence has stormed K12 and higher education. Some, such as those advocating for AI-backed tutors and assistance for English Language Learners, see promise for reducing educational equity (e.g., Khanmigo.ai). Others, such as those pointing to racial and gender biases in AI, suggest it can exacerbate educational inequality (Benjamin 2019). More broadly, scholars have investigated the ways in which technology in education can unwittingly exacerbate stratification in ways that go beyond differences in material resources (Puckett 2022; Rafalow 2020; Warschauer 2019). Some have proposed guidelines to ensure that technological developments are used and implemented equitably (Stonier et al. 2023). In this session panelists will discuss the growth of generative AI in education, with a specific focus on implications for educational stratification.

Sub Unit

• Thematic Session

Presider

• Natasha Warikoo, Tufts University

Panelists

• Cassidy Puckett, Emory University

• Steve G. Hoffman, University of Toronto

• Sepehr Vakil, Northwestern University

• Renzhe Yu, Teachers College, Columbia University

Discussant

• Mitchell L. Stevens, Stanford University

Session Organizer

• Natasha Warikoo, Tufts University