AI in Education

The sudden, widespread, and largely unplanned adoption of genAI tools in education is unprecedented. Historically, innovations find their way slowly to classrooms, after long periods of testing and refinement in factories, offices, and homes. In contrast, teaching and learning have quickly emerged as the primary use cases for genAI tools to the extent that leading companies like OpenAI are quickly retooling their business plans for the education market.

In real time, teachers and students in every field of study are hastily improvising and negotiating new norms and expectations surrounding the use of AI tools.

The AI In Education team responds to this critical moment by considering the current, likely, and ideal impacts of GenAI tools on education from four complementary vantages:

Understanding users: This subteam seeks to understand the attitudes and behaviors and competencies of students, faculty, and administrators as they relate to the application of GenAI tools in educational settings.

Evaluating tools: This subteam explores the capabilities and limitations of generative AI tools for educational purposes, including spin-off technologies such as AI detection tools.

Assessing impacts: This subteam performs technological assessments to identify the current and likely risks and benefits of AI on student learning.

Innovating EdTech: This subteam innovates new educational technology aimed at maximizing the benefits and/or mitigating the risks of generative AI in education.

Faculty Advisor:

• Alexander Landfair

  • landfair@nyu.edu