Ivan Bofarull is Chief Innovation Officer at Esadedisruptive innovation speaker and author of ‘Moonshot Thought’.

As we have seen in various industries, higher education is adapting to change and moving from a centralized setting to a world where most learning takes place beyond the boundaries of traditional institutions (decentralized education or “DeEd”). This shouldn’t be surprising, as most industries have gone on a similar journey. Even health care, another of the building blocks of society, has moved from a hospital-centric setting to a more patient-centric and “liquid” hospital model.

This migration from centralized education to decentralized education was forced by a perfect storm: a massive process of upskilling and reskilling that occurs mainly outside traditional universities (new players, independent courses, bootcamps, etc.); the emergence of a new infrastructure (Web 3) that enables new types of peer-to-peer transactions within the so-called “creator economy”, including courses taught by leading experts in all conceivable domains; and finally, an abundance of capital invested in education – we have seen, for example, Owl Venturesone of the leading VCs in this space, is raising $1 billion for edtech ventures, a scale of funding rarely seen in education.

There are at least three major shifts, or macrotrends, that support this journey to a radically decentralized learning experience:

In terms of how students access knowledge, we are changing from a model where students have access to “very good” professors, to a model where students have access to the best in the world. To take Master class, a startup that has raised nearly $500 million in recent years and offers class subscriptions with “celebrity” instructors like Bill Clinton or Howard Schultz (the founder of Starbucks). GSV Ventures called this trend “Hollywood meets Harvard.” I’m not saying it’s a complete substitute, but it’s a development that reshapes the value of traditional education.

In terms of how students learn, we are moving towards from a framework based on everyone learning in the same place and at the same pace, to a flexible and hybrid model where the basic idea is “it depends”. The science of learning argues that for certain aspects of learning, an asynchronous model may work better (for example, to acquire “codifiable” knowledge, which is easily transferable), while a synchronous model is much better for the rest. Companies like Engagedfrom the founders of Coursera and Class Technologies, are developing new interfaces and ecosystems that make synchronous online learning increasingly sophisticated.

But the main transformation of educational space will occur when tokens, instead of credits, become the primary unit of learning. In other words, the future of learning might look more like the online gaming platform Roblox, where learning happens as a non-linear process from 0 to 100, instead of going linearly from 100 to 0 (penalizing errors). In this new model, students learn more by interacting with and being validated by their peers, and less by being wise on stage.

However, these trips do not represent the main destination of this trip. If most disruptive innovations have something in common, it’s that they follow non-linear trajectories. One of the main characteristics of exponential technologies is the transformation of old scarcities into new abundances. However, it is also true that new shortages then appear, and new standards are set only when companies can produce a synthesis of both abundances and new shortages.

There are a few examples in the higher education space:

While content is a new abundance and learning new skills is relatively quick (think, say, coding bootcamps), what I like to call “Operating system skills” are a new rarity. Take, for example, judgment, a skill that has a long shelf life and helps you navigate future scenarios and make better decisions. Philosophy can even be considered one of the main topics for the future, as suggested by Reid Hoffman, founder of LinkedIn and investor at Greylock. As innovations are increasingly based on new architectures rather than specific technologies, we can think of a business as a stackable construct, where Lego bricks are represented by existing open source technology. With this provision in mind, innovation begins by questioning an architecture from scratch, from first principles, and this is why philosophical thought can become increasingly relevant to apprehend a disruptive future. Along these lines, Minervain San Francisco, a new player in the higher education space and a strategic partner of Esade, talks about nurturing “critical wisdom” as the main foundation of its active learning approach.

If access to knowledge is a new abundance, then learning communities (in other words, the people you will learn with) are becoming a new rarity. To take Mavena startup founded by Gagan Biyani and Wes Kao, former founders of Udemy and altMBA respectively, that gives high-level instructors the tools to teach incredible cohort-based courses that focus on community, not content .

Finally, in a world where explicit knowledge and knowledge validation are a new abundance (think how many stackable micro-certificates you can rack up these days), AI-facilitated invisible learning becomes a new rarity. Sensean Israeli startup, has developed an algorithm that recognizes patterns among exams students submit, and thus allows instructors to see different learner archetypes and thus offer personalized feedback.

Given this context, I believe the universities of the future must be based on three major fundamental layers: (1) A center of critical wisdom, where “operating system” skills are learned. This requires moving from disciplinary silos to an interdisciplinary organization. (2) A platform that becomes a curator of content, curator of learning communities and, in the not so distant future, curator of microloan registers. (3) An augmented learning space: this must be at the intersection of the digital twin of the university and the digital twin of the student. Some will probably call it the metaverse, but in practice it is a space where teaching and learning are complemented by a variety of AI that create new avenues for continuous improvement.

The challenges of higher education are not that different from the challenges faced by many other industries. The leadership of academic institutions can learn from the past mistakes of companies and organizations that have been quietly disrupted (and pushed down a slow slope of decline) by actors who remained in a blind spot, or were spotted in time but failed to were not seen as attractive or threatening enough.

Instead of focusing on technology, supply-driven courses, and credit hours, universities should focus on reassessing the kind of problems they can solve and rethinking them from the ground up, as well as reviving the core mission for which they still existand which will not become a completely encased replica of Google in an ivory tower.