Too Many People Go to University?

A Debate Resurfaces

Following the publication of my recent article, The Death of Universities? From Factories to Ecosystems, an unexpected suggestion appeared on my YouTube feed: a video titled Too Many People Go to University. Was it a coincidence? The video, filmed at the Royal Geographical Society on January 30, 2007, reignited a debate that remains unresolved: should higher education be for everyone?

In that debate, voices clashed over whether university expansion had diluted the quality of education, reduced its economic value, and burdened students with unnecessary debt. The opposition argued that broad access to universities strengthens societies by fostering critical thinking and innovation. Yet, more than a decade later, the world has changed. AI, blockchain, and decentralized learning are reshaping what it means to be educated. If we were to have this debate today, how would it be different?

Image: Digital Diploma debuts at MIT. Source News.MIT

In The Death of Universities?, I explored how higher education must evolve from a rigid, degree-based system into a dynamic learning ecosystem. This transformation is now accelerating as AI, decentralized education, and new skills-based hiring practices force universities to reimagine their roles. If 2007’s debate asked whether too many people go to university, today’s question might be: are universities even the best place to gain an education anymore?

Are Universities Preparing Students for Jobs That Won’t Exist?

In 2007, concerns about university expansion focused on the relevance of degrees in the job market. Today, the debate is not merely about employability – it is about whether universities can keep up with the accelerating disappearance of traditional jobs. AI and automation are rendering many professions obsolete, shifting labor demands to high-tech, creative, and human-centered skills (Frey & Osborne, 2017). If universities continue to function as degree-granting institutions rather than adaptive learning ecosystems, will they remain relevant in the face of AI-driven skills marketplaces (Brynjolfsson & McAfee, 2021)?

Fifteen years ago, critics of university expansion worried about the dilution of academic rigor. Today, an alternative is emerging: decentralized education models where students earn blockchain-based credentials instead of degrees (Davidson et al., 2023). AI-powered tutors are now outperforming human lecturers in knowledge delivery and adaptability (Nguyen & Dede, 2022). Platforms like OpenAI’s Codex and Khan Academy’s AI tutor prototype challenge the monopoly of universities in knowledge dissemination. Should higher education be unbundled, allowing students to assemble their own learning pathways without enrolling in traditional institutions?

Global Higher Education Disparity – Visualizing the stark contrast in university access between different world regions.

In the United States, student loan debt has surpassed $1.7 trillion (Federal Reserve, 2023). Yet, major employers, including Google, Tesla, and Apple, no longer require degrees for hiring (Cappelli, 2020). Instead, skills-based hiring is taking over, where companies assess talent based on competencies rather than credentials (LinkedIn, 2022). If the future of employment is driven by skills rather than diplomas, does it still make sense for students to spend years accumulating debt for degrees that may hold diminishing economic value?

This trend is accelerating: 45% of companies now prioritize skills over degrees, up from 27% in 2022 (LinkedIn Workforce Report, 2024). AI-powered assessment tools like HireVue and Pymetrics are replacing resumes with skills-based evaluations, further marginalizing degrees as a hiring criterion. The World Economic Forum’s 2024 Future of Jobs Report predicts that by 2030, 50% of all jobs will require AI proficiency, yet only 15% of universities have AI-integrated curricula.

Rise of Skills-Based Hiring (2020–2024) – Illustrating how companies are increasingly prioritizing skills over degrees in hiring decisions.

Meanwhile, alternative universities are emerging. 42 Network and Minerva University have pioneered no-tuition, project-based learning models, showing that universities don’t need traditional classrooms to prepare students for the workforce. At the same time, UNESCO data highlights how only 9% of students in low-income countries have access to higher education, compared to 78% in high-income countries. This raises an even more profound question: is the debate about “too many students in university” only relevant in Western countries?

Historical Parallels: Are We Witnessing the Next Education Revolution?

Throughout history, education has undergone radical shifts that reshaped economies and societies. During the Industrial Revolution, guild-based apprenticeships were replaced by formal university systems to meet the demands of mass production economies. Similarly, the digital revolution led to the rise of online education and MOOCs (Massive Open Online Courses) in the early 2000s. Now, AI and Web3 learning models could mark the next great shift in education, potentially replacing traditional universities with autonomous learning ecosystems.

If we look back, previous education revolutions weren’t gradual; they were rapid and disruptive. The printing press transformed knowledge dissemination overnight, making universities less about rote learning and more about critical thinking. Could AI tutors, blockchain credentials, and decentralized universities do the same in our lifetime?

Student Loan Debt Growth (2000–2024) – A line graph showing the exponential rise in student loan debt, emphasizing financial burdens on students.

Source: learningchain.

Blockchain-based education models are beginning to disrupt traditional degrees. LearnCard and EduDAO are pioneering decentralized credentialing, allowing students to earn verified skills-based certifications. The University of Nicosia (Cyprus) now offers a Master’s in Blockchain, entirely certified via on-chain credentials, meaning students own their diplomas as NFTs.

Moreover, elite institutions are experimenting with decentralized identity systems for alumni verification. MIT and Stanford have begun integrating blockchain-based credentials, potentially making traditional university-issued diplomas redundant (MIT Digital Credentials). AI-powered learning platforms such as Socratic AI and Khanmigo are proving more effective than traditional lectures, further challenging the traditional education hierarchy.

In response to the global climate crisis, some universities are becoming leaders in sustainability rather than just degree providers. ETH Zurich has implemented carbon-negative campus designs, while the Global University Climate Alliance (GUCA) now includes over 100 institutions committed to embedding sustainability solutions into their curricula. Universities may need to redefine themselves as climate innovation hubs, solving planetary challenges instead of merely producing graduates.

The Future of Learning: A Call to Action

If universities want to remain relevant, they must embrace AI-driven modular learning, skills-based hiring models, and blockchain credentialing – not resist them. To move forward:

• Universities should integrate AI-driven curricula and explore decentralized accreditation.
• Students should focus on micro-credentials and industry-recognized certifications, not just degrees.
• Policymakers should expand government-backed funding for alternative education pathways beyond traditional institutions.

We are no longer merely asking whether too many people go to university. The real question is: who will lead the next educational revolution – universities, or something entirely new?

The time for passive observation is over – how will we shape the future of learning?