HomeBlogCEL Scholar AI and the Increased Value of Expertiseby Amanda SturgillOctober 4, 2024 Share: Section NavigationSkip section navigationIn this sectionBlog Home AI and Engaged Learning Assessment of Learning Capstone Experiences CEL News CEL Retrospectives CEL Reviews Collaborative Projects and Assignments Community-Based Learning Diversity, Inclusion, and Equity ePortfolio Feedback First-Year Experiences Global Learning Health Sciences High Impact Practices Immersive Learning Internships Learning Communities Mentoring Relationships Online Education Place-Based Learning Professional and Continuing Education Publishing SoTL Reflection Relationships Residential Learning Communities Service-Learning Student-Faculty Partnership Studying EL Supporting Neurodivergent and Physically Disabled Students Undergraduate Research Work-Integrated Learning Writing Transfer in and beyond the University Style Guide for Posts to the Center for Engaged Learning Blog This post was written with ideation assistance from Google Gemini 1.5 Pro, using the following prompt: “Please act as a writing consultant. A client has come in and wants to write a 500-word blog post about the effect that AI might have on the development of expertise, particularly for college students. As the consultant, please ask 20 questions that will help the client to clarify a theme and support points for the post. Ask the questions one at a time.” I’m not too worried that AI is coming for my job tomorrow. But as a journalism professor, it’s coming for my students’ jobs today. From my perspective as an educator, the rollout of generative AI has been at once fascinating and worrying. The benefits like possible custom tutors are enticing, but I still wonder: If AI can easily create solid, if dull, basic work, what is going to happen to expertise? In the communications field, and in others as well, we’re facing the loss of the apprenticeship model that has let generations of new journalists develop their craft. Typically, students developed their skills through trial, feedback, and observation, moving from student to professional. But when AI can produce passable “competent-level” work, the time-consuming, often messy, process for a human seems less inviting for those in the field. I worry that we are replacing mastery with competence—a thirst for excellence being supplanted by a buffet of OK. AI is great at producing the same thing we already have, making more and doing it quickly. It doesn’t call in sick and can predictably fill the hole where copy is needed. A true expert, though, knows when and how to go beyond the expected. It’s an ability that develops over time, as the expert learns from experimentation and develops an engaging voice. Developing as an expert is iterative. So, what might an apprenticeship look like in the age of AI? One answer might lie in a big question that has accompanied internships for many years: why have an intern? Student interns in glamour fields like sports and communications often complete tasks for the company without pay. This brings up important questions about equality of opportunity (Silva 2021) and, in the US at least, the question of “who benefits” determines if internships can be unpaid at all. If the intern is benefitting through valuable educational experiences, guidance from the US Department of Labor suggests employers may not have to compensate them. Image created by Dall-E with the prompt: “Black and white line art of a robot sitting in a carnival booth with a sign reading “Ask the Expert.” This shifts the focus away from assessing outputs, and towards cultivating learning itself— a shift from product to process. If we want to continue to develop experts, learning (work-integrated or otherwise) needs to prioritize critical thinking, reflection, and metacognition. In the classroom, you might see students thoughtfully interact with AI, analyzing its work and evaluating the results from different approaches to the tools. Assignments can ask students to document process and to reflect on the evolution of their learning. It could work similarly in apprenticeships, where interns could be asked to help evaluate tools the employer might use. This feels counterintuitive for a business, where the goal is to make money, but investment today could pay off tomorrow. Yesterday’s experts had the ability to adapt, and that strength has become even more important as technology engages with work. About the Author Amanda Sturgill, Associate Professor of Journalism at Elon University, is a 2024-2026 CEL Scholar, focusing on the intersection of artificial intelligence (AI) and engaged learning in higher education. Connect with her at asturgil@elon.edu. How to Cite this Post Sturgill, Amanda. 2024. “AI and the Increased Value of Expertise.” Center for Engaged Learning (blog). Elon University, October 4, 2024. https://www.centerforengagedlearning.org/ai-and-the-increased-value-of-expertise/.