academia

Robert Paul Wolff: A Personal Tribute to a Life of Teaching and Thought

I didn’t get to know of Robert Paul Wolff’s passing until recently. And yet, his work has been with me for years.

He made Kant and Freud more accessible to me. For that, I will always be grateful to him. I was an Eklavya of sorts—learning from a distance, drawing from his words, and inspired by a life that fought on despite odds that I only knew too well.

His personal blog, with all its warts and all, is a window to his mind. It is unfiltered, deeply intellectual, sometimes grumpy, often humorous, and always honest. It is a rare thing—to get inside the head of a philosopher, not through curated books but through everyday reflections, political rants, and candid stories of struggle.

This is a personal tribute to the man.

A Teacher Until the End

In the spring of 2024, at the age of 90, Robert Paul Wolff was still teaching. From a nursing home in North Carolina, he logged into Zoom every Friday to lead a discussion on Das Kapital. His students weren’t just eager undergraduates—among them were Harvard faculty and graduate students, all drawn in by his ability to make Marxist theory come alive.

“It was one of those very rare Harvard events where people actually showed up, not because of some resume item, but because they were actually interested,” said Social Studies lecturer Bo-Mi T. Choi in The Harvard Crimson, who helped design the course.

Even through a screen, his presence was unmistakable.

“Even on the Zoom screen, you could tell he was probably one of the most compelling teachers one could ever meet, a truly extraordinary man,” said David Armitage, Chair of the Committee on Degrees in Social Studies.

It wasn’t about status or prestige for Wolff. Teaching was simply what he did.

The Man Who Built Ideas

Robert Paul Wolff was the last surviving co-founder of Harvard’s Social Studies concentration—one of the first interdisciplinary programs of its kind. Launched in 1960, it brought together philosophy, politics, and economics to help students engage with the complexities of the real world. The idea was simple: problems don’t fit neatly into academic departments, so why should education?

During his time at Harvard, Wolff was one of the founding members of the Social Studies concentration in 1960 and became the head tutor for the program’s first year. At its inception, the program admitted only 20 to 30 honours degree candidates a year, hoping to train them in cross-disciplinary thinking unconstrained by departmental boundaries.

Armitage said Wolff, in the 1950s, felt that the world’s problems were “so big that they cannot be handled by one single department”—something Armitage believes is still true today.

But Wolff didn’t just build programs. He built ways of thinking.

At the University of Massachusetts Amherst, he co-founded the Social Thought and Political Economy (STPEC) program, and when UMass wanted to establish a PhD program in African American Studies, he was asked to help. He had no background in the field. So, as the story goes, he spent an entire summer reading every major book in the discipline—because if he was going to be involved, he would do it right.

Why He Matters

1. He Made Philosophy Accessible

Philosophy can be dense and difficult. Wolff had a way of making it clear. His works on Kant, Freud and several others continue to be read by students around the world. His lectures—many of which remain freely available on YouTube—are a reminder that great teachers don’t just explain things well; they make you care about them.

His blog, The Philosopher’s Stone, was an extension of this. He wrote about the subjects that fascinated him, but also about his personal struggles, his frustrations with academia, and his reflections on life. It wasn’t always polished. But it was real.

2. He Never Stopped Teaching

By 2021, he had already been living with Parkinson’s disease for over a year. His handwriting had become nearly illegible, and he relied on speech-to-text software to continue his work. In a deeply personal note on his blog, he shared that while his body had begun to slow down, his mind remained clear.

By January 2024, at the age of 90, he reflected on how much his mobility had declined. He accepted it with characteristic bluntness. But what mattered to him most? He had one more chance to teach. He was preparing for a study group—one that would explore ideas he had studied for decades. That, more than anything, brought him joy.

3. He Stood for What He Believed In

Wolff wasn’t just an academic; he was an activist. He protested against apartheid, fought for university divestment from South Africa, and stayed politically engaged until the very end. For him, philosophy was never just about ideas—it was about action.

A Legacy That Carries On

Robert Paul Wolff passed away on January 6, 2025, at the age of 91.

The tributes that followed said it all.

The University of Massachusetts Amherst remembered him as a brilliant mind and fierce advocate for interdisciplinary education. The North American Kant Society acknowledged his “significant contributions to philosophy.” Philosopher Brian Leiter summed it up best: “A long life, well-lived.”

Even Parkinson’s couldn’t stop him. Even when his body failed, his mind kept working, his passion for learning never dimmed.

His work lives on. His ideas live on. And if you haven’t looked him up before, now might be a good time. His books, his lectures, and his blog are still out there.

And if you want to see his mind in its rawest, most unfiltered form, start with his blog. It’s all there.

There are more fascinating insights about his generosity and commitment to change in his obituaries in The Harvard Crimson and UMass Amherst.

AI in Academia: The Grind, The Gain, and the Great Recalibration

A few months ago, I was teaching a bright MBA class when a student raised his hand in the middle of a lecture. He said he had misgivings about my arguments. And then, right there in class, he told me he had been using an AI tool to critique my points.

I learned a thing or two that day. Not just about the subject, but about how AI was changing the very nature of learning. I left the class not thinking about how students should avoid AI, but about how I could use AI to prepare better.

I wasn’t prepared for the question, and I’ll admit—I felt mildly threatened.

Now, my parents were both professors. I’ve been teaching a paper at a top-tier business school for over a decade, in addition to my other work. I’ve seen academia up close—the passions, the programmes, and the politics. So when I came across the California Faculty Association (CFA) resolution on AI, I paid attention.

California, after all, is at the heart of the tech world. If any faculty association could chart the future of AI in academia, I thought it would be this one.

But what the CFA put out was quite the contrary.

The CFA is pushing for strict rules on AI in universities, raising concerns that AI might replace roles, undermine hiring processes, and compromise intellectual property. As they put it:

“AI will replace roles at the university that will make it difficult or impossible to solve classroom, human resources, or other issues since it is not intelligent.”

I respect their concerns. But I also believe the real challenge isn’t what AI should do—it’s what humans should still do in a world where AI can do so much.

And that leads to some fundamental dilemmas.

A Moment to Recalibrate

The goal of education was always to teach thinking—knowledge was simply a measure of that thinking. Somewhere along the way, we confused the measure with the goal.

Instead of focusing on fostering deep thought, we turned education into a test of memory. AI now forces a reckoning. If AI can retrieve, process, and even generate knowledge faster, more accurately, and with greater depth than most students, what does that mean for education?

AI offers an opportunity not to restrict learning, but to recalibrate it—to return to the real goal: teaching students how to think, question, and navigate complexity.

Three Dilemmas Academia Must Confront

1. Who Does the Work—Humans or AI?

AI can grade essays, draft research papers, and provide instant feedback. It’s efficient. But efficiency isn’t learning.

Law firms now use AI for contract analysis. Junior lawyers “supervise” the process. The result? Many don’t develop the deep reading skills that once defined great legal minds. If universities follow the same path—letting AI mark essays and summarise concepts—students may pass courses but never truly engage with ideas.

Douglas Adams once said, “We are stuck with technology when what we really want is just stuff that works.” AI works—but at what cost?

2. Who Owns the Work?

Professors spend years developing course material. AI scrapes, reuses, and repackages it. Who owns the content?

The entertainment industry has been fighting this battle. Writers and musicians pushed back against AI-generated scripts and songs trained on their work. Academia isn’t far behind. If AI creates an entire course based on a professor’s lectures, who gets the credit? The university? The AI? Or the human who originally built it?

The CFA resolution warns about this:

“AI’s threat to intellectual property including use of music, writing, and the creative arts as well as faculty-generated course content without acknowledgement or permission.”

The same battle playing out in Hollywood is now knocking on academia’s door.

3. Does Efficiency Kill Learning? Or Is That the Wrong Question?

It is easy to assume that efficiency threatens deep learning. The grind—rewriting a paper, wrestling with ideas, receiving tough feedback—has long been seen as an essential part of intellectual growth.

AI makes everything smoother. But what if the rough edges were the point?

A medical student who leans on AI for diagnoses might pass exams. But will they develop the instincts to catch what AI misses? A student who lets AI refine their essay may get a better grade. But will they learn to think?

Victoria Livingstone, in an evocative piece for Time magazine, described why she quit teaching after nearly 20 years. AI, she wrote, had fundamentally altered the classroom dynamic. Students, faced with the convenience of AI tools, were no longer willing to sit with the discomfort of not knowing—the struggle of writing, revising, and working their way into clarity.

“With the easy temptation of AI, many—possibly most—of my students were no longer willing to push through discomfort.” – Victoria Livingstone

And therein lies the real challenge.

The problem isn’t efficiency itself—it is what is being optimised for.

If learning is about acquiring knowledge, AI makes that easier and more efficient. But if learning is about developing the ability to think, question, and synthesise complexity, then efficiency is irrelevant—because deep thinking requires time, struggle, and iteration.

So maybe the question isn’t “Does efficiency kill learning?” but rather:

What kind of learning should be prioritised in an AI-enabled world?

If efficiency removes barriers to learning, then we must ask:

What should learning look like when efficiency is no longer a limitation?

A Complex Problem Without Simple Answers

It is tempting to look for quick fixes—ban AI from classrooms, tweak assessments, introduce AI literacy courses. But this is not a simple or even a complicated problem. It is a complex one.

Dave Snowden, from his Cynefin framework, would call this a complex problem—one that cannot be solved with predefined solutions but requires sense-making, experimentation, and adaptation.

Livingstone’s frustration is understandable. AI enables students to sidestep the very struggle that shapes deep learning. But banning AI will not restore those lost habits of mind. Universities cannot rely on rigid policies to navigate a world where knowledge is instantly accessible and AI tools continue to evolve.

Complex problems do not have rule-based solutions. They require adaptation and iteration. The real response to AI isn’t restriction—it is reimagination.

Engage with AI, rather than fight it. Encourage students to think critically about AI’s conclusions. Reshape assessments to focus on argumentation rather than recall.

In a complex system, progress does not happen through control. It happens through learning, adaptation, and deliberate experimentation.

Reimagination, Not Regulation

Saying no to AI is a false choice. AI will seep into academia like a meandering tsunami that doesn’t respect traffic lights at the shore. The real challenge is not limiting AI, but reimagining education.

The CFA is right to demand a conversation about AI in education. But academia must go beyond drawing lines in the sand. It must reinvent itself.

AI is not the threat. The real danger is holding on to learning models that worked well in an earlier time.

That time is past.

It is time to unlearn. And recalibrate.