Students are most likely to learn about climate change in science class, statistics in math class, and reading comprehension in English class. If this pattern tells us anything, it’s that students will be most likely to learn about Artificial Intelligence in computer or technology classes.
Not approaching any of the aforementioned topics from an interdisciplinary angle does a disservice to our students. When topics are siloed by subject, students miss the connections to where they will encounter those issues in the real world. If climate change was integrated into a civics curriculum, students might better understand its policy implications, and if statistics were mentioned in humanities classes, it might improve media literacy skills. Likewise, if AI is only discussed in a computer science context, students will miss out on the broader, more nuanced discussions that we should all be having about these emerging technologies.
The Interdisciplinary Imperative
Artificial Intelligence (AI) is rapidly becoming more prevalent in our daily lives, affecting multiple aspects of our career, academic, and civic life. As a result, learning how to use AI is a skill that must be taught like any other skill. However, to truly understand the implications and applications of AI, it is necessary to approach it from an interdisciplinary perspective.
A single-discipline approach to teaching AI can limit students’ understanding of its broader significance. Teaching students about AI only in computer science classes, for example, will give them the technical skills but not the context in which to use them. Moreover, it may exclude students who have other interests or are intimidated by computer science.
On the other hand, an interdisciplinary approach to AI education offers many benefits. It provides a more nuanced understanding of AI and its implications, expands students’ opportunities to learn about AI, and allows for a broader understanding of how AI can be used. In the long run, AI development also stands to benefit from the diverse perspectives that different disciplines can offer. If the AI-driven future is to be ethical and equitable, it will require input from everyone.
Today’s students are already understanding the need to learn new generative AI tools like ChatGPT, regardless of their field of study. Some University of Texas students are asking their university to create an intro to AI class as core requirement for all undergraduate students. And there’s good reasons to support this idea: AI literacy is a relevant skill for everyone today and you don’t need a masters degree in AI to use Chat GPT effectively.
Embracing an Interdisciplinary Approach
Other schools, academics, and researchers are understanding this imperative as well. UNC Chapel Hill created a new AI Project housed in its philosophy department that is “designed to advance research and collaboration on the philosophical foundations and significance of artificial intelligence and virtual worlds”. Likewise, Stanford’s Human-Centered Artificial Intelligence institute partners with faculty across disciplines to conduct research on AI.
With all the talk of embracing an interdisciplinary approach to AI in higher education, where philosophy professors can teach entire classes about AI ethics, there is much less understanding of what that might look like for k-12. In truth, an interdisciplinary k-12 AI curriculum will require topics related to AI, and practice using it, to be thoughtfully incorporated across subjects. Different disciplines can be responsible for approaching AI education in various ways in order to provide a comprehensive understanding of the technology. Computer classes can approach it from a technical dimension, while humanities can focus on the social and personal impact of AI. Social sciences can approach AI education from a policy angle and explore what AI means for civic engagement, as well as discuss regulation and its impact on the workforce. Even ELA classes can leverage AI to learn new analytical skills, like dissecting and critiquing AI writing.
Artificial intelligence is obviously not the only subject that would greatly benefit from a more comprehensive, interdisciplinary approach. But, the recent onslaught of new technologies requires everyone in the education community to embrace AI beyond its computer science roots. Today’s students deserve a well-rounded understanding of the technology and its broader significance in society. They are tomorrow’s AI developers, but they are also tomorrow’s policy makers, doctors, teachers, voters, and community members. They need the in-depth awareness of how AI will affect their future lives, and the AI industry needs the diverse perspectives that various fields can offer in order to be effective, ethical, and equitable.