Guests tackle the question of how we preserve the kind of deep disciplinary understanding the next generation will need to best serve their patients and clients.
“This invention will produce forgetfulness in the minds of those who learn to use it, because they will not practice their memory. … They will imagine that they have come to know much, while for the most part they will know nothing.”
That sounds like sharp criticism of artificial intelligence (AI), but those were actually the reported words of Socrates about 2,400 years ago, and the invention he worried would ruin young minds was writing. Fortunately — and ironically — one of his students, Plato, did write those words down.
Now, no one wants to get rid of writing, but Socrates did have a good point. Every new advance in information technology has raised worries about what we now call cognitive offloading. We don’t use paper maps in the car anymore. We just do whatever Waze tells us to do. Cellphones have always had a Phonebook app, so most of us don’t remember anyone’s number. And when our phones got “smart,” we gained the magical power to get the answer to any question immediately.
Want to know about ancient Mayan pyramids? There is, I think, very close to zero chance you will go to the library and check out a bunch of books. Google provides 11.8 million hits on that search term in .19 seconds.
Still, this time with generative AI it feels different.
After Brown University professor Roberto Serrano gave his first take-home exam of the spring semester, he knew something had gone wrong. The average score for the class came back at 96 out of 100, with 40 perfect scores. So, Serrano told the class the final exam would be in-person and closed-book.
A flood of students dropped out, including 22 who had received those perfect scores. The average score in the final dropped from 96 to just 48. So, Serrano and his colleagues everywhere are reassessing not only how they teach, but how they assess what students have actually learned.
Some are taking a hard line.
The University of Chicago banned the use of AI in all of its core social science courses. Its law school had already banned laptops, tablets, and wearable electronics from first-year classes to encourage pen-and-paper critical thinking. Duke University has even banned applicants from using AI to write admissions essays.
However, more than $4 trillion in AI investment in just the last two years suggests it’s here to stay. That's why some others argue it might make more sense to treat AI like the proverbial horse and ride it in the direction it’s going.
In his piece in Juristnews three months ago, Maryland Carey Law professor Donald J. Tobin, JD, wrote this about restrictive policies at certain other law schools:
“The deepest flaw in these restrictive policies is that they misidentify where the cognitive work now lies. Increasingly, the lawyer’s task is not to produce a first draft from a blank page but to direct, interrogate, and evaluate machine-generated work product.”