Can Artificial Intelligence Expand Our Capacity for Human Learning?

• 05/08/23

Grush: How would you describe human learning? Could AI in education help build the capacity for thinking and learning about more complex things? If so, could AI actually pave the way for understanding?

Campbell: For me, human learning is among the most extraordinary phenomena our universe has to offer, more beautiful and awe-inspiring than galaxies, nebulae, or any other natural phenomena. Human learning, especially in the way it can empower insight, lies at the very center of my own experience of meaning, of purpose, and indeed of love. One of the reasons I so love to write and think about the work of John Milton, the focus of my doctoral work, is that Milton placed an extremely high value on the human capacity for learning as the very core of what it means to be human. He even wrote a pamphlet on education reform!

Human learning is among the most extraordinary phenomena our universe has to offer, more beautiful and awe-inspiring than galaxies, nebulae, or any other natural phenomena.

I do think the current conversations surrounding AI can help focus our attention on the essential term "understanding," a capability generative AI does not have. Just what is understanding, and how far should we as educators proceed to teach with AI technologies we can employ but not truly understand ourselves? Are there frameworks, levels, or modes of understanding we'd be willing to work within to achieve or measure against certain curricular goals? We need even more robust conversations among educators about the notion of understanding: what we mean by it and how learners might demonstrate it.

How far should we as educators proceed to teach with AI technologies we can employ but not truly understand ourselves?

Of course, there are always new tools, applications, and, in fact whole new fields of generative AI to explore and — safely — experiment with. For example, there's an emerging field called "prompt engineering," the study and practice of eliciting the most useful and accurate results from generative AI. In essence, it's the study of how to pose questions that will get good and relevant answers. That's an interesting thing to think about as something that might have implications for teaching our writing students about good, clear expository prose.

Grush: We've already touched on the scaling of AI. Are there any additional comments you'd like to make about scale?

Campbell: Indeed, I could make many more comments! But for now, I'll summarize by saying that, unfortunately, I see extraordinary dangers ahead as scaling up the availability and use of generative AI also scales up most or perhaps all of the most misguided approaches to the digital age that higher education has pursued for decades. For a more extensive exploration of what I believe to be these disastrous missteps within higher education, I invite readers to start with my 2009 article "A Personal Cyberinfrastructure" and go from there, especially by viewing my blog writings — for example, The Odyssey Project: Further Discoveries. Also see videos of my keynote presentations on my YouTube channel.

Grush: In order for fruitful and beneficial applications of AI in education to occur, what would help? I know there are several institutional components that might need to "come along" as AI adoption continues — maybe assessment, digital competencies, core curriculum revisions, or alignment with strategic plans, as examples. Is there one thing you think institutions could concentrate on that would be most useful, something that may even help us discover how AI could expand the capacity for human learning?

Campbell: There are many areas that need to be ready for change. To that end, as a proposed first step, networks of colleges and universities might declare "The Age of AI" as a theme for the upcoming academic year, and devote themselves to networked learning experiences around that theme both within their institutions and across that interinstitutional network. I don't mean speakers series and symposia alone. An institutional commitment to asking the difficult questions should encourage substantive, thoughtful experiences integrated within and across the curriculum, and be inclusive of all students, faculty, and staff.

Expanding the capacity for human learning is a tall order, but it is the real goal. The choices we as educators make now for AI adoption can mean the difference between disaster and continued progress. Let's hope the choices are still ours.