The AI Degree Boom: A Necessary Evolution or a Risky Gamble?
The rise of AI degrees in Massachusetts universities is more than just an academic trend—it’s a seismic shift in how we prepare the next generation for a world increasingly dominated by artificial intelligence. Personally, I think this is one of the most fascinating developments in higher education in decades. It’s not just about teaching students to code or manage algorithms; it’s about reshaping how we think about work, ethics, and the very nature of human expertise.
What makes this particularly fascinating is the speed at which these programs are emerging. Just four years ago, only four schools in the U.S. offered AI degrees. Today, that number has skyrocketed to 79, with over 100 institutions offering minors or concentrations. This rapid expansion reflects a broader panic—or perhaps, a pragmatic response—to the relentless pace of AI innovation. Universities are no longer just reacting to technological change; they’re trying to get ahead of it.
But here’s the catch: AI isn’t just another tool like Microsoft Word or Photoshop. It’s a transformative force that challenges the very foundations of how we work and think. Allan Glass, a business professor at Endicott, nails it when he says, ‘Students have to figure out how to be good managers of AI, not competitors with it.’ This raises a deeper question: Are we teaching students to use AI, or to lead with it?
From my perspective, the focus on talent over technology is crucial. MIT’s ‘Artificial Intelligence and Decision Making’ program, now the second-most-popular major at the institute, isn’t just about coding. It’s about teaching students to critically evaluate how AI informs decisions—a skill that’s as much about ethics as it is about efficiency. What many people don’t realize is that the real challenge isn’t implementing AI; it’s understanding its limitations and potential biases.
Take Suffolk University’s recent rollout of an AI co-major, which sparked a student petition with over 1,200 signatures. The petitioners argued that the university should focus on ‘a more sustainable future that doesn’t rely on artificial intelligence.’ While I sympathize with their concerns, I think this reaction highlights a broader misunderstanding. AI isn’t inherently good or bad—it’s a tool, and like any tool, its impact depends on how we wield it. The real issue isn’t whether we should teach AI, but how we teach it.
One thing that immediately stands out is the emphasis on interdisciplinary learning. Northeastern’s approach, for example, integrates AI into fields like behavioral neuroscience, chemical engineering, and even philosophy. This isn’t just about creating AI specialists; it’s about creating AI-fluent professionals across industries. Sam Iannone, a Northeastern student, used AI to automate a tedious inventory report at Whoop, proving that even small applications can have a big impact.
But here’s where it gets interesting: According to a 2023 MIT report, 95% of organizations fail to see a return on their AI investments. Why? Because they don’t know how to integrate AI into their workflows. This is where AI degrees could be game-changing. By training students to become ‘AI orchestrators,’ as Northeastern Chancellor Ken Henderson puts it, universities are addressing a critical gap in the workforce.
However, this raises another question: Are we moving too fast? The field of AI is evolving so rapidly that curricula risk becoming outdated before students even graduate. Charles Fadel, founder of the Center for Curriculum Redesign, argues that fluency in AI is essential, but I wonder if we’re placing too much emphasis on technical skills at the expense of critical thinking. After all, AI can process data, but it can’t replace human judgment.
What this really suggests is that AI degrees aren’t just about teaching technology—they’re about teaching adaptability. The ability to learn, unlearn, and relearn will be the most valuable skill in the AI era. Universities that focus on this—like Endicott, with its required internships and liberal arts foundation—are likely to produce graduates who can thrive in an uncertain future.
In my opinion, the AI degree boom is both necessary and risky. Necessary because AI is reshaping every industry, and risky because we’re still figuring out how to teach it effectively. If you take a step back and think about it, this isn’t just about education; it’s about redefining what it means to be skilled in the 21st century.
So, is this the future of higher education? Personally, I think it’s a step in the right direction, but it’s far from perfect. The real test will be whether these programs can keep pace with AI’s evolution while instilling the ethical and critical thinking skills students will need to navigate its complexities. As one commentator put it, ‘AI won’t replace jobs—people who know how to use AI will.’ The question is, are we teaching them how?
