Breakout Session #2: Education

There is a conflicting cultural discourse about the use of AI in higher education. On the one hand, enthusiasts like Ethan Mollick and Mary Meeker suggest that AI will revolutionize higher education by changing the way that students learn. On the other hand, skeptics like John Warner and Nick Bostrom suggest that generative AI could lead to devaluing higher education and a loss of student ability to master fundamental skills. We believe that neither side is fully correct, and that the reality lies somewhere in between. In this paper our faculty/student collaborative research group will describe how we used a mixed methods approach to test both student perception of the ethicality and effectiveness of using generative AI for the writing process, a dimension of education that is seen as most “at-risk” with the growing ubiquity of generative AI. We will discuss the results of our campus-wide survey and follow up interviews along with a multi-classroom experiment designed from the results of this preliminary work. Our aim is to demystify how students are actually using generative AI as a collaborative partner show students where it is an effective and ethical choice for their educational growth.

AI has been around for several decades. It has been mostly embedded in the domains of computer science, natural language processing, computer vision, and machine learning, to name a few. Today, the perceived sleeping giant is awake and roaring. AI continues to permeate many domains that touch our professional and personal lives, including learning, training, education, healthcare, criminal justice, marketing, business, transportation, climate, and creative arts.

When a technology seamlessly interacts, influences, and integrates into the life of a common man, it is our collective responsibility to create, build, and sustain a workforce that is literate and cognizant of the power, applications, and ethics behind the technology. AI literacy is, therefore, imperative for institutions, organizations, governments, and societies particularly as we are still in the process of building guardrails around this double-edged sword.

Being literate and knowledgeable about AI is no longer a choice, given the transformational impact, both positive and negative, on jobs, industries, and governments. AI literacy o as “the ability to understand, use, monitor, and critically reflect on AI applications without necessarily being able to develop AI models.” AI literacy has emerged as a new skill set that everyone should learn in response to this new era of intelligence (Ng. et al., 2021).

This paper discusses strategies to implement the four key tenets of AI literacy for all stakeholders in higher education, including students, faculty, administrators, and alumni): 1) Know and understand, 2) Use and apply, 3) Evaluate and create, and 4) AI Ethics. (Ng. et al., 2021). Integrating AI literacy into existing curriculum using Bloom’s taxonomy as a framework and current best practices along these four dimensions will be outlined.