How do you teach AI? Do you simply lay out the nature of reinforcement learning, backpropagation and the march of the perceptron toward tokenization and world models? Or do you apply it to the real world, showing students how AI works “in praxis,” and integrating it into a broader view of what matters when it comes to our newest technologies?

A new effort developed through MIT’s Common Ground program, led by professor Asu Ozdaglar , takes aim at the latter philosophy of instruction, suggesting that it’s time to take AI education to the next level.

“We want to empower students to become critical thinkers about AI, not just users of the technology,” said Asu Ozdaglar in coverage at MIT News Sept. 9 .

The idea is that to do this, it’s necessary to provide examples along with concepts, to flesh out the technical aspects of AI, to imagine the actual use of LLMs and neural nets, for instance, in robots, and to really get a better bird’s eye view of what humans are dealing with.

“What is usually missing is context: Opportunities for instructors and students to connect AI concepts to specific disciplines, problems, and ways of thinking,” writes MIT News reporter Amanda Diehl, citing input from Saurabh Amin, the faculty director of the AI Educators Pilot. “Those connections are often built through dialogue and reasoning, rather than by presenting AI as a fixed set of ideas to be received. But instructor capacity remains one of the scarcest resources.”

Put in simple language, schools need more teachers who are prepared to introduce AI to students in a more colorful and integrative way.

I was perusing the main goals of the Common Ground program in setting this up. First you have:

“Address the need for computing education across many disciplines, not only as a tool but conceptually.”

“Educate ‘computing bilinguals’–students fluent in both the ‘language’ of computing and that of their discipline–a core part of the College’s mission.”

Combining AI savvy with a particular field – that makes sense.

“Bring the forefront of rapidly-changing computer science and artificial intelligence fields together with the problems and methods of other disciplines.”

This sounds like more of the same.

“Infuse computing education in a coordinated manner across MIT.”

I think this speaks more to just a broader application around the MIT community.

Of course, I don’t speak for MIT, but I think all of this will be helpful as humanity contemplates a future with these technologies.

Here’s part of how it’s described on the web site:

“Departments have joined forces to pilot several new subjects under the Common Ground, many of which now satisfy requirements for majors and minors. Some of these subjects include a common core together with discipline-specific material taught in different departments in parallel. Some involve offering variants of existing classes centered around computational thinking in the context of other disciplines. Others create new versions of existing classes with an integrated presentation of computational and numerical tools and issues.”

Notes on the program show that instructors will want students to take the ideas that they have learned in the course, and choose which ones they will apply to a given field or domain. In general, as mentioned above, domain experience is valuable.

“How do we make sure that machine learning is not just a black box, nor this magic piece of new technology?” asks workshop instructor Shen Shen. “You can think of it as a tool, or a new framing to help you solve the problem in your specific domain.”

Here’s another quote on the program from Brandeis assistant professor of computer science Dylan Cashman:

“It’s helpful to know that everybody within different disciplines at different universities is struggling with the same questions of how we can best serve our students as the technology is changing. Hopefully, we can set them up for success by being a little bit more forward and anticipatory of what the AI use is going to be.”

Using AI to Research My Title

I think this program is going to be helpful for MIT undergrads.

I was playing around with GPT and I wanted to share this with you, in closing. First off, I found it curious that when I started thinking of teacher names for titling this piece, the first thing that came to mind was “Mr. Chips,” a relic of a bygone era.

So I asked GPT about Mr. Chips. My first question was this, without additional context: was Mr. Chips a good teacher?

“Yes,” GPT said. “Mr. Chips is portrayed as a good teacher, although not necessarily an exceptional teacher in the conventional academic sense.”

Here’s what I asked next: would Mr. Chips have taught AI in a way that is vibrant and compelling?

I’m going to include the whole GPT response, because I think it gives you the real flavor of what it is saying:

“I think eventually, yes, but in a very Mr. Chips way. He probably wouldn’t be the teacher dazzling students with the latest model architecture or showing off a new agent every Tuesday.

At first, Chips would likely be suspicious of AI. He is a classicist, a traditionalist, and a believer in accumulated human knowledge. He might regard a machine that can instantly produce an essay on Thucydides as rather unsporting.

But the older, warmer Chips would probably discover that AI provides marvelous material for teaching the humanities. Imagine him asking his class whether a machine can actually understand a poem, whether intelligence requires experience, whether an AI can possess character, or what Plato would make of a chatbot. He could move naturally from Aristotle to Alan Turing and from Latin translation to machine translation.

And that could be genuinely vibrant because Chips’s great strength isn’t technological expertise. It’s storytelling, humor, memory, and human connection. AI would become another means of asking the questions he has always cared about: What is knowledge? What makes somebody wise? What distinguishes imitation from understanding? What does one generation owe the next?”

Last question: can you describe the existential value of Mr. Chips in 50 words?

Keep in mind, here, that I often ask GPT for 50 words, just so I don’t end up with a wall of text like that above, which I actually ended up abridging after all.

“Mr. Chips embodies the existential value of a life made meaningful through relationships, service, memory, and continuity,” GPT said in response. “He achieves neither fame nor fortune, yet profoundly influences generations of students. His story suggests that meaning emerges not from extraordinary accomplishment but from sustained human presence: showing up, caring, teaching, remembering, and being remembered.”