Op-Ed: McConaughey Didn't Prepare Me For This Tesseract
Matthew McConaughey floating around in space for three hours is hardly how I imagined finding inspiration for the Future of Work and Education.
Yet, watching ol’ Coop tumble through the Tesseract – that hyper-cubic library of moments where past, present, and future are visible and interconnected – felt strangely familiar. Not the saving-humanity part, perhaps, but the feeling of being inside a system where everything influences everything else, all at once. The Interstellar wiki calls it a place where moments are "linked by the strings of time."
I like the Tesseract metaphor. Lately, I feel I’m living in one: since September 2024, I've been navigating working full-time on Generative AI at Google Cloud while pursuing a full-time MBA at Stanford.
In Google’s Sunnyvale campus, where I work out of 5 days a week, I debate with my colleagues (who are brilliant and make me question my intelligence all the time) about the immediate application of AI advancements and the urgent adaptations required of today's workforce.
In Stanford’s Knight Management Center classrooms, my incredible peers (whose talents make me question my abilities all the time) and I practice skills that Stanford believes business leaders should have for the future.
In my spare time, I work with collaborators on an independent study sponsored by the legendary Scott Brady, pioneer of Research-Driven Innovation. We interview learning designers, startup founders, professors like Stanford’s Vice Provost of Digital education Matthew Rascoff, and Teach For America alumni about their past experiences. These interviews have helped me realize just how little I know about learning.
Consequently, the past, present, and future swirl around my Google Calendar like a cosmic centrifuge.
This daily juggle is a microcosm of the knotty societal challenge we all face. How do we navigate this real-life Tesseract, where the future of work we're hurtling towards, the education system we need to build, and the actions we must take right now are tangled together and demanding simultaneous attention?
Thinking inside this Tesseract helps explain why changing things feels so hard. Education outputs feed industry inputs, industry demands shape educational goals, and entrenched structures resist tiny tweaks. It clarifies why many well-intentioned EdTech 'revolutions' failed to deliver systemic transformation. Consider Massive Open Online Courses (MOOCs): launched with utopian ideals of democratizing education, their actual impact on broad educational pathways has been limited, often hampered by low completion rates. While rates vary and have evolved, early extensive studies reported median completion rates of only 12.6% (source). EdTech is often a point solution aimed at one wall of the Tesseract, ignoring the interconnected geometry of the whole thing.
Moreover, I find it strange how our language and societal structures reflect a binary attitude about Education and Work. Or rather, Education then Work. Maybe there’s a little detour for Grad school; perhaps a coding bootcamp adventure later on. But for the most part, America’s workforce still operates on an assembly-line model designed for the Industrial Age factory: Classroom learning for two decades, and then poof! Out pops a worker ready to follow instructions.
This model isn't just aging, it's crumbling in the face of the Digital Age with AI accelerating everything.
A significant 'skills gap' persists: 87% of companies worldwide report skill gaps or expect them within a few years, causing tangible economic consequences of trillions of dollars over the next decade if unaddressed (source). The gaps are growing too: 70% of HR professionals see a skills gap in their organization, a sharp increase from previous years (source). The challenge is compounded by the rapid pace of change – the World Economic Forum has estimated that a significant percentage (e.g., 44%) of core worker skills could be disrupted in the coming years, driven heavily by technological adoption like AI (source). AI itself is expected to automate tasks that currently absorb a large portion of employee time, further requiring workforce adaptation and upskilling (source).
So what tangible steps can we – as individuals building careers, founders spotting opportunities, educators shaping minds, leaders managing teams, policymakers setting frameworks – take?
Solving this takes more than building a web app. Remember Canvas? The learning management system (LMS) hailed as a classroom game-changer? Stanford GSB leaned heavily on it during COVID. It's useful, certainly, for distributing materials and managing grades (source). Research suggests LMS platforms can positively impact student achievement and provide structure, but their potential is often limited by how they are implemented. Many institutions primarily use them for administrative convenience rather than leveraging features for deep pedagogical change, collaborative learning, or personalized pacing (source). EdTech is often just a knob on one wall of the Tesseract, rarely changing the underlying architecture of how we teach or learn.
Perhaps instead of changing the current system bit by bit from within, a full creative destruction is due. Let’s do a fun thought experiment: If you were designing a 'learning system' for a brand-new nation in the Digital Age, what would it look like? Would there even be 'schools' as we know them? How would skills be acquired and validated across a lifetime?
For an entrepreneur, a builder, anyone trying to make a dent, understanding this Tesseract will help find leverage. Where, in this complex, interconnected system, can a well-aimed stone throw actually create meaningful change? What are the potential leverage points?
Could it involve validating skills through more agile, non-degree pathways? Alternative credentials like certificates, micro-credentials, and digital badges are gaining traction, designed to verify specific competencies quickly (source).
Could it take accelerating the shift towards skills-based hiring, which focuses on demonstrable abilities over degree proxies? This approach is rapidly gaining adoption, with reports indicating a significant majority of employers (potentially over 80% by 2024, up from ~56% in 2022) are using skills-based practices (source). Proponents argue it widens the talent pool, potentially increases retention, and is seen as a better predictor of job success than traditional resume screening. Major companies and even governments have begun removing degree requirements for many roles (source).
Does it mean embracing fundamentally different structures like competency-based education (CBE)? CBE models allow learners to progress based on mastery of skills rather than time spent in class, offering flexibility and potentially improving preparation for real-world application (source). While direct comparison studies yield mixed results depending on metrics, CBE aims for deeper understanding demonstrated through application (source).
Or does significant change require policy interventions that foster innovation? Examples include state and local policies enabling school choice, competency-based credit flexibility, flexible funding for technology integration, or initiatives directly linking education programs with local business workforce needs (source). Creating space for R&D in education, which currently receives minimal funding compared to other sectors, could also be crucial.
For now, I’m still navigating my own little corner of the Tesseract between Palo Alto and Sunnyvale, where I’ve joyously crash-collided with fellow hyper-cube explorers: a neuroscientist-turned-entrepreneur, former TFA teachers, and brilliant AI scientists.
We’re excited to draw insights from education (what do we teach?), cognitive science (how do we actually learn?), computer science (what can tech realistically enable?), industry (what skills truly matter?), and crash-collisions yet to occur. Understanding the intricate connections within this Tesseract is the first step toward finding the leverage needed to build a future where education and work dynamically enable, rather than constrain, human potential.
