From Score-Driven to Value-Sharing: Understanding Chinese Family Use of AI to Support Decision Making of College Applications

2024-11-15

arXiv.org

AI Summary

This study investigates the practical deployment of AI tools—such as Quark GaoKao—in China’s college admission counseling and the underlying family decision-making processes. Drawing on 32 in-depth interviews and reverse engineering of AI functionalities, we identify a structural imbalance wherein parents dominate tool usage while students remain largely excluded; an overreliance on score-based matching at the expense of long-term career development; and critical risks including algorithmic misrecommendation, third-party data exploitation, and digital inequity exacerbating disparities among disadvantaged families. To address these issues, we propose the “value co-articulation” theoretical framework—a shift from short-term admission probability modeling toward collaborative family consensus-building and alignment of educational choices with lifelong career values. Based on empirical findings, we derive six context-sensitive, multi-stakeholder design principles to advance human-centered, equitable AI in education. (149 words)

Technology Category

• Humans and AI: Learning Human Values and Preferences
• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Constraint Satisfaction and Optimization: Constraint Learning and Acquisition

Application Category

• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

This study investigates how 18-year-old students, parents, and experts in China utilize artificial intelligence (AI) tools to support decision-making in college applications during college entrance exam -- a highly competitive, score-driven, annual national exam. Through 32 interviews, we examine the use of Quark GaoKao, an AI tool that generates college application lists and acceptance probabilities based on exam scores, historical data, preferred locations, etc. Our findings show that AI tools are predominantly used by parents with limited involvement from students, and often focus on immediate exam results, failing to address long-term career goals. We also identify challenges such as misleading AI recommendations, and irresponsible use of AI by third-party consultant agencies. Finally, we offer design insights to better support multi-stakeholders' decision-making in families, especially in the Chinese context, and discuss how emerging AI tools create barriers for families with fewer resources.

Problem

• AI tools used for college application decisions in China
• Limited student involvement in AI-assisted decision-making
• Challenges with AI recommendations and resource disparities

Innovation

• AI tool for college application decisions
• Generates lists based on scores, preferences
• Focuses on immediate results, not long-term goals