If your inbox is anything like mine, it is inundated with invitations to workshops, webinars, and resources related to artificial intelligence (AI). Indeed, AI is inescapable, and not just in education. It can augment our work by making tasks simpler and more efficient. At the same time, it can dehumanize work and present ethical dilemmas. It can also perpetuate stereotypes and biases. Some fear it will replace us as educators. The proliferation and polarization of AI views are precisely why my colleagues and I chose this topic as our “wicked problem” for Fall 2024.
My college, the College of Applied and Collaborative Studies, believes strongly in project-based learning and interdisciplinary collaboration, such that all of our programs incorporate this philosophy. Students work on real-world problems that connect to course content, sometimes in conjunction with industry partners. In our dual credit program, North Texas Now!, students take an introductory communication course in their first semester, along with English, History, and Political Science courses. The cohort/learning community approach to this program allows us to collaborate and develop connected assignments. Each semester we select a “wicked problem,” defined as a complex policy- related issue with no clear solution (Rittel & Webber, 1973), and at least one project centered around the problem. This semester we ambitiously introduced two AI-related projects, the development of an AI policy and the creation of an AI-based app or product. Whether you are interested in developing an AI-themed course or another topic, I would like to describe our process and share some ideas, resources, and lessons learned with you.
Our process began in Spring 2024 with a day-long retreat, where we selected the fall topic. From there we met regularly throughout the summer to build and connect assignments, and we continue to meet throughout the fall semester to discuss course planning, student observations, and teaching strategies. Because AI was relatively new and mysterious to all of us, we had to educate ourselves by reading books and articles and watching videos about AI. I found the books Unmasking AI, by Joy Buolamwini, and Co- Intelligence: Living and Working with AI, by Ethan Mollick (2024), to be good foundational resources that sparked some ideas about how I might incorporate AI into my introductory communication course. We also completed a two-part microcredential course on AI offered through our university, and required students to complete part of this course as well.
Course Projects
Our program director selected a common reader, The Worlds I See, by Dr. Fei-Fei Li (2023), and each of us developed an assignment related to it. Common reader programs, where all students in a program or college read the same text, can build community and improve information literacy, particularly when included as part of a first-year experience (Philips & Case, 2013). Dr. Li’s memoir describes her experiences immigrating to the United States from China and her quest to develop artificial intelligence tools for societal benefit, so this text integrated well into all courses. For example, in the book Dr. Li describes her quest to discover her “North Star,” something to pursue or even obsess over, which would drive her research. Along these lines, in English, students wrote a “North Star Narrative” relating what guides them, and they will orally present these narratives in my Communication class at the end of the semester.
Reading this book introduced us to Dr. Li’s website, AI4ALL, which contains open educational curricula on a variety of AI-related topics. We were particularly intrigued by the AI and Ethics lesson, which teaches students to analyze the ethical, privacy, fairness, and explainability issues with AI tools such as automated essay graders and culminates in students creating an idea for an AI-powered app or product to address a problem in education. This became the project for the second half of the semester, which students are currently working on. They will pitch their ideas in a poster presentation to the community.
In the first half of the semester, students wrote an AI policy for the program and presented their proposed policy to the class and faculty. In their Political Science class, students learned how policies are made and completed an analysis of other universities’ AI policies. In their English class, students developed technical writing skills by following the university’s template for policies. And in my class, Communication, they honed their public speaking abilities by presenting their ideas as a team and responding to audience questions. After their presentations, they journaled about their experience and applied their proposed policy to various scenarios in their History class. This case study approach was intended to strengthen their critical thinking skills and test the applicability of their policies.
The AI theme allowed me to focus individual lessons on AI issues and incorporate practical application into the course. For example, in the lesson on verbal communication we discussed prompt engineering and how to elicit better responses from AI tools by using language that is less abstract. Additionally, I infused some of AI4ALL’s lesson on facial recognition into the unit on nonverbal communication, and demonstrated some AI coaching tools such as Yoodli and Microsoft Speaker Coach to improve speech delivery.
When explaining interpersonal communication and the stages of relationships, students were introduced to AI friends and wrote a story imagining a relationship with an AI companion. You might think of artificial intelligence as a computer science subject, but as I read and learned about AI, I discovered many connections with communication studies such that I will continue to include these lessons beyond this semester.
Lessons Learned
While our process was collaborative, interdisciplinary, and exciting, we did encounter some unintended consequences. First, teaching students about AI seemed to encourage them to use it without fully understanding its limitations, something we continue to address. We shared many of the same concerns as other faculty about using AI tools to cheat, and this semester did not dissuade us from this worry. However, through readings and discussions we learned strategies to discourage unethical AI usage, such as limiting the amount of information in writing prompts. Second, and surprisingly to us, many students included faculty in their AI policies. They seemed to feel that if students are prohibited or restricted from using AI, then faculty should be, too. As they argued, faculty are using AI tools for grading, developing rubrics, and writing recommendation letters so perhaps there should be ethical guidelines for them as well. Mollick (2024) noted that employees generally refrain from telling others they are using AI, primarily because they worry about negative repercussions if they are caught, but also because they worry about being replaced. While this may or not be true for higher education faculty as well, students certainly offered thought-provoking recommendations.
Lastly, I caution against overdoing the AI theme to the point where you as the instructor become sick of the topic. With all of the AI readings, discussions, and ethical challenges, my colleagues and I may be suffering from AI burnout, and perhaps our students are too. I look forward to our final conversations this semester and I recommend incorporating an end-of-semester survey to uncover their lessons learned about AI.
Whether you are considering a brand-new course on AI and Communication or a themed basic course like the one presented here, I hope this article has given you some ideas and resources. Though my colleagues and I select a different wicked problem each year, I will continue to bring AI lessons into my courses because this topic is timely, relevant, and important. Students who know how to responsibly and ethically use AI not only become marketable prospective employees but responsible and ethical citizens of society. By embedding AI lessons into our curricula, we can inspire learners to approach AI with responsibility and vision, ready to tackle the next technological or human challenge.
References
Buolamwini, J. (2023). Unmasking AI: My mission to protect what is human in a world of machines. Penguin Random House.
Li, F. (2023). The worlds I see: Curiosity, exploration, and discovery at the dawn of AI. Flatiron Books.
Mollick, E. (2024). Co-Intelligence: Living and working with AI. Penguin Publishing.
Philips, S. F., & Case, E. (2013). Contextualizing information literacy enrichment through a common reader in a First-Year Experience seminar. College & Undergraduate Libraries, 20(1), 1–24. https://doi.org/10.1080/10691316.2013.761046
Rittel, H. W. J. & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4, 155-169.