Ethical Considerations and Data Privacy in AI Education

Abstract

The incorporation of artificial intelligence (AI) into education has led to a multitude of questions regarding ethics and data privacy. Despite advancement in modern research and novel techniques being created, lingering concerns remain whether AI education can be completely ethical and have an impeccable data privacy and security system. We scrutinized an array of contemporary literature and identified numerous ethical and privacy challenges of AI education as well as a variety of methods put forth to overcome those obstacles. Over the course of our research, a very critical hurdle to the implementation of AI education emerged: a system that can perpetuate bias and still lead students to the same fixed outcomes they would have reached nonetheless. While data privacy can be ensured to a certain extent with the use of newly established machine learning techniques, such as federated learning, it remains unclear whether AI education can truly deliver a differentiated experience that will cultivate students’ learning growth instead of leading them down a set path. The aforementioned statement is not intended to deter investment in AI education; rather it serves to cast light on the significant challenge of AI education offering authentically personalized pathways for students.