Diverging Perceptions of Artificial Intelligence in Higher Education: A Comparison of Student and Public Assessments on Risks and Damages of Academic Performance Prediction in Germany

Abstract

The integration of Artificial Intelligence (AI) into higher education, particularly through Academic Performance Prediction (APP), promises enhanced educational outcomes. However, it simultaneously raises concerns regarding data privacy, potential biases, and broader socio-technical implications. Our study, focusing on Germany–a pivotal player in shaping the European Union’s AI policies–seeks to understand prevailing perceptions of APP among students and the general public. Initial findings of a large standardized online survey suggest a divergence in perceptions: While students, in comparison to the general population, do not attribute a higher risk to APP in a general risk assessment, they do perceive higher societal damages when confronted with specific damage scenarios.

Marco Lünich

Social Scientist

My research interests include the public perception of Digital Media, Big Data, and Artificial Intelligence.