AI Meets HigherEdTech: Implications for Better Student Outcomes

Artificial Intelligence and Machine Learning have the potential to automate, optimize and advance decision making in higher education. Potential areas may include anticipating enrollment, assisting in enrollment selection, predicting student success and informing learning and remediation pathways for individual students. This panel consists of four experts: two in the AI space and two from the learning and assessment space. The panel will discuss and debate issues relevant to higher education including current and future applications of AI and ML in educational technology such as providing actionable data for more efficient education, equity and fairness in student learning and outcomes, data privacy concerns and potential decision biases that may arise from these emergent technologies.

Moderator: Jerry Gorham


Lev Gonick

Sergey Karayev

Andreas Oranje

Alina Von Davier