Nathan Carter, Professor of Mathematical Sciences and Director of the Center for Analytics and Data Science at Bentley University, joins the podcast to share his current research on whether AI can accurately grade mathematical proofs and provide meaningful feedback to students. The conversation explores the challenges of precision, logic, and ethical concerns in AI-assisted grading, and considers broader implications for teaching, learning, and faculty development. Listeners will also gain in...
All content for AI in Academia: Navigating the Future is the property of Professor Noah Giansiracusa and Gaurav Shah and is served directly from their servers
with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
Nathan Carter, Professor of Mathematical Sciences and Director of the Center for Analytics and Data Science at Bentley University, joins the podcast to share his current research on whether AI can accurately grade mathematical proofs and provide meaningful feedback to students. The conversation explores the challenges of precision, logic, and ethical concerns in AI-assisted grading, and considers broader implications for teaching, learning, and faculty development. Listeners will also gain in...
The head of Bentley's philosophy department, Axel Seeman, chats about the new computer science/philosophy joint major in AI at Bentley, why interdisciplinarity is "bloody hard," what role philosophy plays in AI and in preparing students for a world full of AI, what Descartes would have said about the latest chatbots, and what impact AI is going to have on our social lives and our feelings of loneliness.
AI in Academia: Navigating the Future
Nathan Carter, Professor of Mathematical Sciences and Director of the Center for Analytics and Data Science at Bentley University, joins the podcast to share his current research on whether AI can accurately grade mathematical proofs and provide meaningful feedback to students. The conversation explores the challenges of precision, logic, and ethical concerns in AI-assisted grading, and considers broader implications for teaching, learning, and faculty development. Listeners will also gain in...