April 17, 2025 - 18:07
Artificial Intelligence (AI) is increasingly being utilized in higher education to enhance the prediction of student success. These advanced tools analyze vast amounts of data, including academic performance, attendance, and even social factors, to identify students who may need additional support. While the potential benefits of AI in this context are significant, experts caution that without proper safeguards, these technologies could inadvertently perpetuate existing racial and social biases.
The algorithms used in AI systems can reflect the biases present in the data they are trained on. If historical data contains disparities related to race or socioeconomic status, the AI may reinforce these biases in its predictions. This raises ethical concerns about equity in education, as disadvantaged students might be unfairly categorized as less likely to succeed, leading to a lack of support and resources for those who need them most.
To mitigate these risks, institutions must prioritize transparency and fairness in their AI systems. Implementing regular audits and involving diverse stakeholders in the development process can help ensure that AI tools serve to uplift all students, rather than entrenching existing inequalities.
