Education Is Not The Answer (Part 1)
The notion of education implies that there’s a path towards a definitive, finished state wherein an individual has become “educated.” But in a world of accelerated change, with rapid disruption cycles in industry and with rising automation, that end state of being “educated” is just no longer meaningful. An individual must have learning agility — the ability to learn, adapt, and apply in quick cycles. Part One of this piece discusses the learning-over-knowing imperative, and Part Two will examine the specifics of learning agility.
Rising Automation: Stream, Don’t Store, Knowledge
History has held that individuals were educated and trained for expertise and knowledge, then employed to use knowledge and skills to do work over decades. Our reality now is that rising machine intelligence can render anything that can be codified both digitized and automated. This rapid proliferation of global connectivity and dissemination of content reduces the value of each individual human’s stock of knowledge, and it reduces the ability of a worker to monetize a single dose of education over a career lifespan and leaves the concept of a profession in question. As John Hagel, of Deloitte Center for the Edge says: “We must re-orient people to not develop stocks but rather work with flows of knowledge as we move from scalable efficiency as a competitive advantage to saleable learning as a competitive imperative”. Or as Laurence Van Elegem so elegantly put it “Stream, don’t store, Knowledge”.
The Paradox of Education: Learning Over Knowing
In her 2011 book Now You See It: How Technology and Brain Science Will Transform Schools and Business for the 21s t Century, Cathy N. Davidson wrote that 65% of the students in K-12 schools today will work in jobs that do not currently exist. A 2013 study by Oxford University predicts that 47% of today’s jobs will be automated in the next two decades. The Integrated Post-Secondary Education Data System (IPEDS), which tracks higher education data on retention and degree completion, focuses on the 150%, or 6-year, the marker for undergraduate (4-year) degree graduation rates. Ironically, Deloitte University Press recently projected that by 2020, 50% of the content in an undergraduate degree will be obsolete in 5 years. So, the process of becoming educated is now likely to be longer than the shelf life of the knowledge, training, and degree that’s gained.
Shift: From Learning the Tool, To Learning From the Tool
As a human species, we have moved from using hand tools to assist with labor tasks to interacting with tools that entirely replace labor. As we entered the information age we shifted from assisting labor to assisting cognitive tasks. We are now on the crest of massive human technological displacement from current jobs, at a time when an algorithm can achieve anything mentally routine or predictable. In one significant manifestation of this disruption, educational efforts once focused on training students for mastery of a tool — say, a software program or an app — to use throughout their education and career, are now obsolete. Tools are now built as adaptive learning platforms — designed to understand the learner’s progress and a threshold of competence to advance them with just the right degree of friction and frustration to generate learning. As a particularly good example, tools that enable generative design are ones in which the output (designed element) is the product of a set of parameters defined by the designer. In generative design, rather than design the output, the designer defines the outcomes and collaborates with the tool to achieve the desired artifact (a building structure or physical product, for example) or process. This is a massive shift from learning to master the tool, to both learning from the tool and collaborating with the tool.
Why Does This Matter? Rapid Shift of Norms
In the next decade we will see a number of tectonic shifts. Signs of exponential technological expansion and adoption will materialize around us; for example, Cisco predicts (2011) there will be six connected devices per person, and Business Insider (2015) predicts an estimated 10 million autonomous (self-driving) vehicles will appear on our roadways. Per Futurist Ray Kurzweil’s prediction, soon a computer costing $1000 will have the equivalent processing power of the human brain [Note: Kurzweil’s technology predictions over the past 30 years have an 86% accuracy rate]. Advances in health care are shifting our demographics; we will soon have more people older than 65 than people younger than 15. Per a McKinsey Study (2013) will also see a massive economic global shift as almost half of the Fortune 500 companies will be headquartered in emerging markets by 2025 (up from 5% in 2000). These changes demand that we rethink our fundamental assumptions about the problems we solve and for whom we solve them — a tectonic shift away from creating products and services for the young and affluent first-world population, towards collaborating with rising machine intelligence to create new solutions for an aging, global population. Further, we will no longer limit our “global view” to earth as we begin to expand the galaxy via exploration of Mars in 2020.
As Mark Bonchek, Chief Epiphany Officer of Shift, describes it: “Ours is the first generation in history with a need to update our mental maps within a single generation. The old models are rapidly becoming obsolete. This creates a challenge of not only learning; but rather unlearning. For example, this may be the last generation that needs to learn how to drive.”
If you don’t believe these shifts are already taking place, consider how much you have already outsourced to your smartphone, from contacts to directions.
All these tectonic shifts are smashing our contextual references and rendering notions of a single linear dose of education and the straightforward status of being “educated” both insufficient to fuel a multi-decade career. The future of work is learning agility and cooperating within a deep interface between humans and machines. Part Two of this series will delve into the facets of learning agility.
Further Reading and Talks
- Welcome To the Augmented Age (Jeff Kowalski, CTO, Autodesk)
- The Shift Index (John Hagel, Deloitte)
- Predictions For The Next 25 Years (Ray Kurzweil, Singularity)
- Shift Thinking (Mark Bonchek)
- Discussion of Generative Design (Conversation with John Maeda (Design Partner at Kleiner Perkins Caufield & Byers) and Carl Bass (CEO Autodesk)
- The Future of Employment (Oxford University 2013)
- The Second Machine Age (McAfee and Brynjolfsson)
- Shifting Global Demographics (Stanford Center for Longevity)
- Urban World: The Shifting Global Business Landscape (McKinsey 2013)
- The Self-Driving Car Report (Business Insider 2015)
- The Internet of Things (Cisco 2011)
Heather McGowan works at the intersection of the future of work and the future of learning, an emerging field that integrates design strategy, management consulting, and education. McGowan uses single frame visuals to help people quickly understand shifting mental maps and contextual references. She assists executives in rethinking their business models, teams, and organizational structures. In higher education, she advises presidents to develop learning agility to prepare graduates for jobs that do not yet exist. Heather was the architect of the Kanbar College of Design, Engineering, and Commerce at Philadelphia University — the first undergraduate college explicitly focused on innovation. She is the co-author and co-editor of the book Disrupt Together: How Teams Consistently Innovate. Her corporate clients range from small start-ups to publicly traded, Fortune 500 companies ranging from Autodesk to BD Medical. McGowan speaks internationally on the future of work and the future of learning. www.heathermcgowan.netOriginally published at www.linkedin.com.