T-Squared: a Teaching and Technology Podcast

In the second part of their conversation, Jacob and Matt continue their discussion of AI ethics with Dr. Eric Covey from Grand Valley State University's Department of History.

To help find a truly international solution for climate change, they enlist the help of ChatGPT itself. Reading through its ideas leads to a conversation about whether large language models actually contain knowledge or whether it's something else. Discussing knowledge leads to the question of how creativity relates to randomness, and whether LLMs can truly be creative.

The conversation turns a bit more technical as they consider the idea of information compression as a way to understand how large language models operate. The analogy helps illuminate why there are two different types of bias present in LLMs.

The episode includes a discussion of the concept of "openness" and the financial costs involved, raising the question of how "open" generative artificial intelligence models are—and whether they can ever actually be truly open.

In the final moments of the episode, Eric relates a story about how one of his students used ChatGPT and didn't notice problems in the generated text. The group returns to some of the broad themes discussed, including the problem of what counts as "good enough", the need for technoskepticism, as well as the importance of digital literacy in the higher ed curriculum.

Jacob and Matt talk with Dr. Eric Covey of Grand Valley State University's Department of History. Compared to many faculty, Eric began talking with his students about generative Ai fairly early in the ChatGPT era. He anchored his discussion not in issues of plagiarism, as many faculty have, but in a discussion about the unseen ethical challenges that generative AI presents.

The conversation broadens to discuss ways in which education can help build learner self-awareness—whether of the global impact of their technological habits or the personal impact of practices of self-care and attention to learning science.

The question of critically engaging with technology leads to how individual educators and their institutions can balance concerns about educational technology with the institutional and societal imperatives to prepare learners for their future careers. The three consider why, compared to previous technological changes, so many in education are rapidly embracing generative AI.

The answer may lie in part with the way neoliberalism has shaped modern education. Considering the imperatives and constraints that neoliberalism places on higher ed leads to a question that will likely reappear in this podcast season: how long will it be until we see the rise of "AIU"—an institution that downplays human faculty, leverages generative AI, and claims to do so for the benefit of all.

The episode (the first of two with Eric) ends with a discussion about whether AIU will be successful, whether technical solutions to some of AI's problems will increase its popularity, and how to counter the fact that for many people a university run by AI will be "good enough."

Jacob Fortman and Matt Roberts introduce the rebooted T-Squared podcast, whose third season will focus on the topic of generative artificial intelligence. In this episode Jacob and Matt set the stage for the rest of the season by talking about ChatGPT and generative AI more broadly. While there's no shortage of news about AI—especially in higher education—Matt and Jacob lay out a plan to move past the hype and the hysteria. Future episodes will focus on a deeper discussion about generative artificial intelligence and how it differs from other types of AI; the relationship between AI, knowledge, and expertise; the legal and ethical factors involved in the use of AI; and the connections between efficiency, community, and education.