When I tell people my kid is heading to Sarah Lawrence for a liberal arts degree, I get that look. You know the one. The gentle head tilt that says, “But what will they actually DO with that?”
Five years ago, I might have had the same reaction. We’ve all been programmed to think specialization equals success. Get a computer science degree. Learn data science. Pick a lane and dominate it.
But AI just flipped that script entirely.
The Specialization Trap
While everyone’s been rushing toward narrow expertise, AI got really good at narrow expertise. It can code better than most junior developers, analyze data faster than most analysts, write marketing copy that converts better than most copywriters.
The jobs getting automated first? The hyper-specialized ones with clear rules and patterns.
The skills that make you irreplaceable? Liberal arts colleges have been teaching them for centuries.
What Sarah Lawrence Gets Right
Sarah Lawrence doesn’t do majors the traditional way. Students design their own curriculum around questions that fascinate them. They write constantly. They think across disciplines. They question everything.
To get value from AI, you need to know how to ask good questions, synthesize information from multiple domains, evaluate sources, spot bias, and communicate complex ideas clearly.
Liberal arts students spend four years practicing exactly this. They read philosophy and connect it to economics. They study history and apply it to current events. They analyze literature and use those insights to understand human behavior.
This isn’t unfocused wandering. It’s training for a world where making unexpected connections is your competitive advantage.
Why Now Is Different
Previous technology waves rewarded specialization. The industrial revolution needed people who could master specific machines. The early computer era needed people who could write code in specific languages.
AI is different. It’s a general-purpose technology that amplifies human thinking. You can’t compete with AI at specialized tasks. But you can use AI to do things that neither you nor AI could do alone.
That requires exactly the kind of flexible, questioning, synthesizing mindset that liberal arts education develops.
The Meta-Skills That Matter
When I worked at Yahoo, LinkedIn, and Zynga, the people who rose fastest weren’t necessarily the deepest technical experts. They were the ones who could frame problems in new ways, communicate across different teams, adapt quickly when circumstances changed, and work with ambiguity.
Wrestling with big questions across multiple disciplines develops these skills better than anything else. Students learn how to learn. How to think. How to question assumptions and synthesize insights from disparate sources.
They’re developing the exact cognitive toolkit you need to thrive alongside AI.
The New Reality
In a world where AI can handle routine tasks, human judgment becomes the luxury good. The ability to ask better questions. To think ethically about implications. To communicate in ways that create understanding and connection.
Technical skills matter, but their half-life keeps shrinking. Programming languages change. Platforms evolve. Tools become obsolete.
What doesn’t become obsolete? The ability to think clearly, communicate effectively, and approach problems from multiple angles.
That’s what my kid is getting at Sarah Lawrence. Not job training for today’s economy, but thinking skills for tomorrow’s.
While everyone else races to out-specialize the machines, liberal arts students are developing the one thing machines can’t replicate: human wisdom applied to human problems.
In a world where AI can do almost everything, that might be the only thing that really matters.