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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
A visionary guide for the future of learning and work
Long Life Learning: Preparing for Jobs That Don’t Even Exist Yet offers readers a fascinating glimpse into a near-future where careers last 100 years, and education lasts a lifetime. The book makes the case that learners of the future are going to repeatedly seek out educational opportunities throughout the course of their working lives — which will no longer have a beginning, middle, and end. Long Life Learning focuses on the disruptive and burgeoning innovations that are laying the foundation for a new learning model that includes clear navigation, wraparound and funding supports, targeted education, and clear connections to more transparent hiring processes.
Written by the former chief innovation officer of Strada Education Network’s Institute for the Future of Work, the book examines:
- How will a dramatically extended lifespan affect our careers?
- How will more time in the workforce shape our educational demands?
- Will a four-year degree earned at the start of a 100-year career adequately prepare us for the challenges ahead?
Perfect for anyone with an interest in the future of education and Clayton Christensen’s theories of disruptive innovation, Long Life Learning provides an invaluable glimpse into a future that many of us have not even begun to imagine.
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Seitenzahl: 373
Veröffentlichungsjahr: 2020
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Table of Contents
COVER
INTRODUCTION: AN ABIDING HOPE FOR THE FUTURE
Notes
Part I: From a Rigged System
1 A 100-Year Work Life
More Than 12 Jobs in a Lifetime
Are We Future-Proof?
The Never-Ending Debate on Education versus Workforce Training
Notes
2 The Theories Behind the End of College
Adult Learners to the Rescue?
Disrupting College
Notes
3 The Future of Workers, the Future of Us
The Blame Game: Send in the Employers
Not Systems, But an Ecosystem
The Opportunity Gap
Cutting into the Curb
Notes
Part II: To a New Learning Ecosystem
4 Seamless On- and Off-Ramps
Getting Unstuck
Guiding Principles for a New Learning Ecosystem
A Way Forward
Note
5 Navigating Our Next Job Transition
What We're Hearing
The Predicament
Seeds of Innovation
Notes
6 Wraparound Supports
What We're Hearing
The Predicament
Seeds of Innovation
Notes
7 Targeted Education
What We're Hearing
The Predicament
Seeds of Innovation: Right Skills, Right Path, Right Time
Notes
8 Integrated Earning and Learning
What We're Hearing
The Predicament: The Precious Resources of Time and Money
Seeds of Innovation: Making Time for and Funding Long-Life Learning
Notes
9 Transparent and Fairer Hiring
What We're Hearing
The Predicament
Seeds of Innovation: Toward Skills-Based Hiring
Notes
10 Getting Started: Taking Root
The Data to Knit It All Together
Growing the Roots of a New Learning Ecosystem
Notes
CONCLUSION
Are These the Jobs of the Future?
The Future Only We Can Write
Notes
ACKNOWLEDGMENTS
ABOUT THE AUTHOR
INDEX
END USER LICENSE AGREEMENT
List of Illustrations
Chapter 1
Figure 1.1 Human skills like communication, leadership, and problem solving...
Figure 1.2 T-shaped individuals combine broad knowledge and skills with deep...
Figure 1.3 Returning to learning throughout a 100-year work life.
Figure 1.4 Few majors report that their coursework is helpful or that they a...
Chapter 2
Figure 2.1 Populations of users.
Figure 2.2 The first iterations of innovations are usually more complicated...
Figure 2.3 Two trajectories: The performance of a product or service over ti...
Figure 2.4 Disruptive innovations push out along the z-axis to touch larger...
Figure 2.5 The elements of a business model.
Chapter 5
Figure 5.1 Journalism job postings increasingly require tech skills like ana...
Chapter 7
Figure 7.1 In St. Louis, cybersecurity skills are oriented toward data analy...
Figure 7.2 The unique cybersecurity skills gaps in Columbus.
Chapter 9
Figure 9.1 Anonymized user profile sourced from GitHub.
Guide
Cover
Table of Contents
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Long-Life Learning is a lifeboat for those of us swimming in the sea of confusing—and often contradicting—narratives about the future of learning, working, and living. Throughout, Michelle brings thoughtful and diverse evidence to bear on a host of pressing challenges facing not just schools but all of society and offers a deeply integrative set of insights from her years as a student of disruptive innovation to chart a better way forward—robots and all.
— Brian Fleming, Vice President of Innovation and Strategy, Southern New Hampshire University
Without handwringing about the rise of automation, or finger-pointing at our current systems of education and employment, Long-Life Learning advances a vision of the future that puts the needs of workers at the center. Recasting us all as “working learners,” Michelle Weise illustrates not just the value of repeated returns to learning, but the critical importance of seamlessly interweaving education and work throughout our careers.
—Van Ton-Quinlivan, CEO, Futuro Health
In Long-Life Learning, Michelle Weise articulates the critical need for adults to access an ever-evolving menu of learning and workforce skills development to remain relevant in the future economy and a 100-year work life.
— Deborah Quazzo, Managing Partner, GSV Ventures
MICHELLE R. WEISE
STRADA EDUCATION NETWORK, INC.
LONG LIFE LEARNING
PREPARING FOR JOBS THAT DON’T EVEN EXIST YET
Copyright © 2021 Michelle R. Weise. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simultaneously in Canada.
No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, (978) 750-8400, fax (978) 646-8600, or on the Web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748-6011, fax (201) 748-6008, or online at http://www.wiley.com/go/permissions.
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Library of Congress Cataloging-in-Publication Data:
Names: Weise, Michelle R., author.
Title: Long life learning : preparing for jobs that don't even exist yet / Michelle R. Weise.
Description: Hoboken, New Jersey : John Wiley & Sons, Inc., 2021. | Includes index.
Identifiers: LCCN 2020030474 (print) | LCCN 2020030475 (ebook) | ISBN 9781119597483 (cloth) | ISBN 9781119597513 (adobe pdf) | ISBN 9781119597520 (epub)
Subjects: LCSH: Employees—Training of. | Career education. | Occupational training. | Vocational education. | Manpower planning.
Classification: LCC HF5549.5.T7 W3879 2021 (print) | LCC HF5549.5.T7 (ebook) | DDC 650.1/3—dc23
LC record available at https://lccn.loc.gov/2020030474
LC ebook record available at https://lccn.loc.gov/2020030475
Cover image: © Maria_Galybina/Getty Images
Cover design: Wiley
For Mike, Noe, and Logan, the loves of my life,and for the risk takers, innovators, and coalition builders,this book is for you.
INTRODUCTION: AN ABIDING HOPE FOR THE FUTURE
One of the great privileges of my life was working with Clayton Christensen, the godfather of the theories of disruptive innovation. I coauthored a few pieces with him, including a short book on disruption in postsecondary education.1
After his much-too-early death in January 2020, I've reflected a great deal on how his theories have given me the foundation for a more hopeful stance toward the future. This, to me, is the most profound takeaway of disruption. It is not, as so many assume, the key to doomsday predictions about an industry. Instead, the theories of disruption are powerful because they provide a constructive and positive lens through which to analyze the unknown and the nascent.
Clay's theories give us pause as soon as we start to dismiss something that smacks of low quality, because it is precisely at that moment that we should wonder if there's something we should be paying attention to—something that might be just “good enough” (his words) to gain traction with people whose alternative is nothing at all.2 He called this population nonconsumers.
Prior to the pandemic, my team of education and workforce researchers at Strada Education Network's Institute for the Future of Work was focused on these nonconsumers, the people being left behind by the great deficiencies of our American education and workforce infrastructure. Over the course of more than 100 hour-long interviews, we listened to working-age adults displaced by the 2008 financial crisis who were unable to recover while the top 1 percent of the American labor market captured 85 percent of the income growth in the years following the recession.3 Throughout this book, you will hear from many of these displaced workers.
They include a high school graduate who was promised opportunities for growth at her local pharmacy but never saw those promotions come to pass due to the constant churn in staff and managers. They are also the people whose caregiving responsibilities—for young children, aging parents, or family members with disabilities—make it impossible to fit into the one-size-fits-all structure of many educational institutions.
Their personal experiences reveal how ill-suited our current postsecondary education and workforce systems are at facilitating seamless, flexible, and cost-effective learning pathways for people to keep up with the emerging demands of the economy. If students don't follow the typical two- or four-year college experience, our systems do not make it easy for them to return and retrain in the future. Learners are left to force-fit nonlinear realities into a rigidly linear system.
Capturing these small, poignant stories has been vital for my research and for understanding the obstacles new consumers of education face. It's also something that I've rarely encountered in other scholars' research on the future of work. Most of the analyses and research get bogged down in the what as opposed to the who. Researchers have been obsessed with quantifying and understanding the changing nature of work by anticipating mass unemployment, long periods of painful adjustment, and the enduring consequences of new technological advancements. Anxiety about the future of work can quickly devolve into a kind of fearmongering. It seems that almost every day there's a paralyzing new fact or figure about the future of work.
The truth is, we don't have to pinpoint the actual number or the specific jobs or tasks we can expect to see automated in the years to come. At a certain point, the statistics become overwhelming. As I write this introduction, COVID-19 has paralyzed the world economy, and the number of unemployment claims in the United States alone has topped 45 million—an unfathomable number.4 The problem is almost too big and amorphous to grapple with through statistics alone. Numbers don't account for the human cost of the problem—the real lives at the center—and the impact on you and me.
Author Daniel Pink describes the virus as the “great unmasking of problems that were in plain sight … there were always these fundamental cracks in the system.”5 Indeed, even before the pandemic, more than 41 million working-age Americans were seeking more direct connections to good jobs and good wages, but they kept falling through the cracks because of the limited way in which we train and hire our workforce.6
The global pandemic has laid bare how fragile our multiple, fragmented systems of K–12 education, postsecondary education, and workforce training are. For quite some time, these siloed and unintegrated systems have neglected millions of people looking to access the relevant information, funding, advising, support, and skills training they need in order to advance.
Adults have never had easy access to on- and off-ramps in and out of learning and work. Our systems are brittle and were never designed for continuous returns to learning. Sure, bits and pieces and discrete solutions exist, but they are neither connected nor integrated, especially for the people who need the most help in finding a way forward.
Newly laid-off workers don't have the technologies and tools they need to analyze their talents, bring them to the surface, and assess their skill gaps. They want information about how to choose the right career pathways—the type real-time labor market information and consumer reviews provide. They want guidance on which pathways will be most effective, targeted, and affordable in helping them grow and thrive in the labor market. But there are no human guides or support services to coach them.
Part I of my book touches on all of the barriers—structural, cultural, and political—that have stymied the advancement of millions of workers and learners. The first three chapters delve into the obstacles that make progress feel impossible for adults today.
From this complexity, we move to a more positive vision of the future. Part II introduces the constructive mental model of a new learning ecosystem that will show us the way, help us learn, endorse that learning, help us pay, and get us hired. Each chapter in this section delves deeply into each of these five guiding principles: A new learning ecosystem must be navigable, supportive, targeted, integrated, and transparent.
To illuminate each aspect of a lifelong learning ecosystem, we begin with what we're hearing from the new consumers of education, then move into the predicaments and barriers that hold their problems in place, and conclude by providing solutions and revealing the seeds of innovation that are helping more people launch into better opportunities. The solutions featured are not comprehensive lists but instead are meant to be illustrative of the kinds of building blocks we need to see more of in a better-functioning learning ecosystem.
We have to move from the future we don't want to the future we do want. We must practice thinking bigger and more boldly about the future we wish to create. In this book, we identify what's working now and consider how to replicate those advances for more working learners.
It takes significant energy and deliberate practice to think expansively and optimistically about what we can do now to prepare for an uncertain world of work. If we invest today in the infrastructure of the learning ecosystem of that future, we will ensure that generations of learners will be equipped with the relevant skills to thrive in the jobs of tomorrow. The doing will not come easily, but the opportunity is clear for us to stitch together new and existing programs and solutions that can serve as engines of upward mobility for millions of Americans, including you and me.
Notes
1
. Michelle R. Weise and Clayton M. Christensen,
Hire Education: Mastery, Modularization, and the Workforce Revolution
(Redwood City, CA: Clayton Christensen Institute, 2014),
https://www.christenseninstitute.org/wp-content/uploads/2014/07/Hire-Education.pdf
.
2
. Clayton M. Christensen,
The Innovator's Dilemma: When New Technologies Cause Great Firms to Fail
(Boston: Harvard Business School Press, 1997).
3
. Estelle Sommeiller, Mark Price, and Ellis Wazeter,
Income Inequality in the U.S. by State, Metropolitan Area, and County
(Washington, DC: Economic Policy Institute, 2016),
https://www.epi.org/publication/income-inequality-in-the-us
.
4
. Lance Lambert, “45.7 million have filed for unemployment during the pandemic–greater than the combined population of 23 states,” Fortune, June 18, 2020,
https://fortune.com/2020/06/18/45-7-million-have-filedunemployment-during-the-pandemic-greater-than-the-combined-population-of-23-states/
.
5
. Daniel Pink, “College Unbound Presents a Talk with Daniel Pink,” May 1, 2020, Zoom,
https://us02web.zoom.us/j/3518520288?pwd=SFpCMm5nclpMUW1QZDVCL1UxVUpUUT09
.
6
. 41,432,159 people to be exact. Strada Institute analysis of U.S. Census Bureau, American Community Survey (ACS), One-Year Public Use Microdata Sample (PUMS), 2018; generated by John Ratte using
data.census.gov
,
https://www2.census.gov/programs-surveys/acs/data/pums/2018/1-Year/
.
Part IFrom a Rigged System
1A 100-Year Work Life
People's life plans used to be a bit more straightforward. We were supposed to pack in some education early on in our lives, with the expectation that we would work and build a career—maybe even raise a family—and then retire. Learn, earn, rest.
Futurists and experts on aging and longevity are now suggesting that we can expect to live longer and that human life spans will extend decades longer than we had anticipated. The authors of The 100-Year Life explain: “For most of the last two hundred years there has been a steady increase in life expectancy. More precisely, the best data currently available suggests that since 1840 there has been an increase in life expectancy of three months for every year. That's two to three years of life added for every decade…. And perhaps more importantly, there is no sign that the trend is levelling off.”1
With advances in health care, medicine, and disease control as well as improvements in general living conditions, we have “found a way to slow down the process of bodily decay that was given to us by nature,” writes aging specialist Johannes Koettl, “a truly remarkable development that no other species has achieved before.”2 The Global AgeWatch Index Report anticipates that by 2100, the number of people aged 80 and over will increase more than sevenfold, from 125 million to 944 million.3 Some are even suggesting that the first people to live to be 150 years old have already been born.4
Let's think about that for a moment: 150 years.
The simple extension of our life span suddenly forces us to consider the dramatic lengthening of our work lives. Will the careers of the future last 60, 80, or 100 years?
This is a very different kind of future of work.
More Than 12 Jobs in a Lifetime
Already, workers who are 55 and older are staying in the workforce at historically high rates, well into their late 60s and even 70s.5 And job transitions have become an established part of life. In the United States alone, 10,000 baby boomers will turn 65 every day from now until 2030,6 and many of them will have experienced at least 12 job changes by the time they retire.7
With this new time horizon, it becomes hard to imagine a straight line from education to work and, finally, retirement. Gone are the days of retiring at age 65 and living on a guaranteed pension from one or a few employers that defined a person's career. Rather, the number of job transitions will only increase with time, as people confront longer and more turbulent work lives.
The notion of a 100-year work life is arresting and quickly snaps our education system into sharp relief by upending so many of our working assumptions. Our default mental model has been that education is largely a one-and-done experience situated on the front end of our development through young adulthood. This perception is further reinforced by societal expectations and financial policies that suggest that higher education is for young adults.8
Cast in this new light, however, two, four, or six years of college front-loaded at the beginning of a 100-year work life suddenly seem deeply inadequate. Technology's transformation of nearly every facet of our economy means that we will all need to develop new skills and knowledge at a pace—and on a scale—never before seen. Advancements will continue to give rise to entirely new kinds of jobs and careers, ones that we cannot even begin to name.
It's already been happening. In 2014, LinkedIn's top jobs were ones that hadn't existed five years earlier—roles like iOS/Android developer, UI/UX designer, cloud manager, big data architect, and social media intern.9 How many more as-yet unknown jobs will we hold in a 100-year work life?
The Future of Work = The Future of Learning
We are all going to have to prepare for jobs that don't even exist yet. Enter the concept of long-life learning. Through the lens of human longevity, the future of work becomes inextricably tied to the future of learning. In a 100-year work life, we may find ourselves in a state of continuous pivots—20 to 30 job transitions might become the new normal. Ongoing skill development will become a way of life.
No matter our current station, we will all become working learners, always flexing between working and learning, or juggling both at the same time—looping continuously in and out of learning and work and navigating more job transitions than we ever dreamed possible.
Moreover, we see how we are not artificially separated from the future of learning and work, as if it was some sort of alternate reality—for other people, not me, at least not now. This is not a future from which we are somehow removed. The concept of long-life learning makes our mandate so much clearer: Education and training will be more important than ever, because those future workers are all of us.
Where Are the On- and Off-Ramps?
The challenge is that we can't access many on- or off-ramps in and out of learning and work today. Educators, policymakers, and funders give a lot of lip service to the concept of lifelong learning, but this talk rarely translates into action. In fact, resources and funding are often geared toward the traditional 18- to 24-year-old college-going population and less often to working adults, the growing majority of learners. There is little investment in the systems, architecture, and infrastructure needed to facilitate seamless movements in and out of learning and work.
The current system of higher education is not forgiving. Today, close to 70 percent of high school graduates go on to college, but they do not always complete their degrees.10 Instead, they “stop out.” They take the one and only off-ramp available, are subsequently labeled “college dropouts,” and are then often punished further with some student loan debt.11 In total, 36 million people in the United States made it into college; they just didn't make it through or out of college.12
For most adults, taking time off work to attend classes at a local, brick-and-mortar community college or four-year institution will not be the answer. A one-, two-, or four-year college program may be a bridge too far in terms of both the time to credential and the full cost of attendance, including the lost wages associated with attending school instead of working more hours.
We must therefore begin prototyping more flexible reskilling and upskilling pathways for the future. We will have to change our approach and put some teeth into the concept of lifelong learning, an idea that has been good in theory (decades old!) but slow to catch fire. We agree with the concept but have not been moved to change our behavior and invest in the much-needed infrastructure for continuous development and advancement.
But once we understand that that we are the ones who will be affected—that the future of workers is about us—the fourth wall, or the imaginary wall between those people and us, breaks down. We will all have to harness the power of education over and over again throughout a longer work life. And we will need more on-demand pathways that tie education to economic relevance—more seamless ways to loop in and out of learning and work. Learn, earn, learn, earn, learn, earn.
Are We Future-Proof?
As periodic returns to learning become the new normal, which skills will we need to develop? Kevin Kelly, forecasting future tech trends in his book The Inevitable, puts it this way: “This is not a race against the machines. If we race against them, we lose. This is a race with the machines. You'll be paid in the future based on how well you work with robots. Ninety percent of your coworkers will be unseen machines. Most of what you do will not be possible without them. And there will be a blurry line between what you do and what they do.”13
There will be certain activities that humans will have to relinquish to computers. Economist David Autor suggests that the more clearly we can describe a task, the easier it may be to create rules for it; mathematics, logical deduction, and encoding quantitative relationships—really any work that involves “a set of formal logical tools”—can be automated.14 The harder the skill is to describe or enunciate, however, the more resistant it may be to computerization.
Autor named this phenomenon Polanyi's paradox after the Hungarian economist, philosopher, and chemist Michael Polanyi, who famously explains in his work The Tacit Dimension that “we know more than we can tell.”15 Polanyi explains that our tacit knowledge is greater than our ability to explicitly describe how we engage with the world around us.
Think about describing how you ride a bike or a horse, how you crack an egg on the side of a bowl, how you adjust your grasp when a cup of coffee is slipping out of your hands, or how you persuade someone when writing an essay. There are skills and rules in our human knowledge and capability that lie beneath consciousness. Polanyi's paradox helps us understand how we can thrive in the work of the future.
Automation Makes Us More Human
What is core to the human experience, or that which we do effortlessly as humans, may empower us to outcompete machines and coordinate better with them. A large part of the literature on the work of the future underscores a growing need for human skills, or capabilities that robots or machine learning cannot simulate. The McKinsey Global Institute notes that “as machines take on ever more of the predictable activities of the workday, these skills will be at a premium. Automation could make us all more human.”16
Human skills and abilities go by many names: soft, social-emotional, noncognitive, power, foundational, common, transferable, baseline, 21st century, employability, workforce readiness, interpersonal, talent, life, and professional skills. More and more research is pointing to these human skills as a way of categorizing our human strengths and defining our competitive edge over robots and machines.17 And there is a tremendous amount of emphasis on attributes such as high emotional or social intelligence, adaptability, flexibility, judgment, resilience, systems thinking, and communication.18 Indeed, we can easily imagine how machines might fail to understand nonverbal gestures and cues in order to guess at or sense the emotional state of a person. Machines are not as good as we are at reading distress, fear, worry, confusion, elation, or tone.
Not only will these skills become more important with time, but real-time labor market information also confirms that employers are already in desperate search of these human skills. An Emsi analysis of more than 36 million job postings, resumes, and social profiles shows that in just the first half of 2018, the skills in highest demand were leadership, management, communications, sales, and problem solving.19 (See Figure 1.1.)
This all sounds promising: Human skills are in higher demand than ever, and we appear to be well positioned (as humans) to demonstrate those uniquely human skills.
Figure 1.1 Human skills like communication, leadership, and problem solving are among the most common skills employers list in job postings.
Source: Robot-Ready: Human+ Skills for the Future of Work. Emsi job posting analytics, 2018. © 2018, Strada Education Network.
When Humans Fall Down on the Job of Being Human
But just because we're human doesn't necessarily mean we're great at the human side of work. In fact, human skills require practice; they are not innate. In his book Humans Are Underrated, author Geoff Colvin asserts, “At just the time when skills of human interaction are becoming the key to people's economic value, young people are abandoning those very skills in favor of digital communication…. Empathy has become a wasting muscle.”20 The work of the future increasingly demands more social and emotional intelligence, but the opportunities for us to broaden our human skills and define our competitive advantage have been progressively diminishing in our day-to-day lives.
First off, we're looking at each other less and spending more time on screens. Colvin discusses the various ways in which we as humans perceive differences in the slightest changes in facial expressions. He describes the work of the psychologist Paul Ekman, who has researched the 40 muscles in the human face, which can combine into over 10,000 expressions—3,000 of which have something to do with emotion.21 The effect of more hours spent on screens means that we are spending less time practicing our human skills in person with others, decoding facial expressions, body language, nonverbal cues, and tone. As a result, advancing technology is “doing much more than changing the nature of work,” Colvin argues. “It's also changing us.”22
What's in Your Bubble?
We are also relating less and less with people with whom we differ. The algorithms that undergird most of our apps have turned our social relationships into bubbles. Back in 2014, Eli Pariser gave a stirring TED talk called “Beware Online ‘Filter Bubbles’” in which he talked about the “invisible, algorithmic editing” that turns our World Wide Web into “a web of one.”23
There is no such thing as a standard Google search result, Pariser explained. Each of our search results looks different even if we use the same exact keyword. Pariser said, “[T]he Internet is showing us what it thinks we want to see, but not necessarily what we need to see…. And what's in your filter bubble depends on who you are, and it depends on what you do. But the thing is that you don't decide what gets in. And more importantly, you don't actually see what gets edited out.” These bubbles mean that we no longer have access to “a balanced information diet.”
How we relate to one another and reconcile differing views is diminishing drastically because of new forms of artificial intelligence (AI). We're surrounded by things with which we agree as opposed to issues or viewpoints that might challenge our thinking or make us feel uncomfortable. It takes practice to see things from another person's point of view, but it's impossible to empathize if we're never exposed to those ideas in the first place.
Hybrid Skills: Human + Technical Skills
All learners will need to develop, practice, and strengthen these durable and more human skills over the course of a lifetime. However, human skills alone are not enough. The jobs of the future will be hybrid in nature. Human resources expert Josh Bersin explains that these new hybrid jobs “do not lend themselves to static job descriptions and simple job titles. They are jobs that require technical, industry, managerial, and integrated thinking skills; they often require skills in communication, persuasion, and teamwork.”24
The skills needed for these jobs will also be hybrid. Employers demand intellectual dexterity and technical expertise in equal measure, or human + technical skills: emotional intelligence + artificial intelligence; ethics + logic; or communication + programming.25 It's not the “Tyranny of the OR,” as author Jim Collins describes it, but rather the “Genius of the AND.”26 The most valuable workers now and in the future will be those who can combine human + technical skills (human+ for short), and adapt to the changing needs of the workplace.
Deep learning AI, as author Scott Hartley puts succinctly in The Fuzzy and the Techie, requires “deep-thinking humans.”27 Problems can scale out of control via tech-enabled environments. Writer Lee Rainie explains, “Connected things and connected people become more useful, more powerful, but also more hair-trigger and more destructive because their power is multiplied by a networking effect. The more connections they have, the more capacity they have for good and harmful purposes.”28 Oddly, it is Facebook's own COO, Sheryl Sandberg, whose platform has been implicated in some of these global disasters, who said it so well: “When you write a line of code, you can affect a lot of people.”29
When a company like one of the Big Five tech giants experiments, the implications are vast. Each decision on each product has “volume-impact repercussions,” explains Gregory Chan, an engineering project manager at Apple.30 There are no precedents for dealing with the issues that tech companies will encounter when developing a new product that millions of people around the world will immediately adopt—sometimes in a matter of hours. In an interview, Chan reflected on his general education requirements for college and expressed his relief in having taken an ethics class alongside his mechanical engineering courses. A stronger grasp of human+ skills has enabled him to consider the voluminous repercussions of the choices that get made.
Enough Technical Skills to Be Dangerous
To be robot-ready, we're not only going to have to practice our human skills, but we're also going to need some domain knowledge to assess the work of the machines. All of us will need to have enough technical skills to be dangerous and intervene at the right times. The balance is critical.
Finland may therefore have the right approach with its “1 percent” AI initiative. With the support of government and private companies, the country is trying to teach 1 percent of its population (approximately 55,000 people) the basic concepts that lie at the root of machine learning.31
AI is complicated and abstract. The decisions and outputs of machine learning technologies are not always explainable, and that lack of transparency and explanation won't be acceptable as AI penetrates more parts of our lives, especially the medical and legal fields and other areas where human lives are at stake. People must ask: What kinds of ethical choices are happening on the back end of programming that need to be more explicit? Are these technologies leveraging biased computational formulas and unfairly discriminating against people because they have been trained on flawed data?
In its current format, AI is deeply problematic because it is being deployed widely across all sectors, but very few companies—fewer than a third, according to the authors of Human + Machine—“have a high degree of confidence in the fairness and auditability of their AI systems, and less than half have similar confidence in the safety of those systems.”32 What does it say that we've already become so reliant on these technologies, and yet we don't fully trust the algorithms that undergird them?
Human+ skills are critical. Working learners must understand what AI is, so that they can control what Andrew Ng, founder of the Google Brain Deep Learning Project, calls “the new electricity.”33 Just like electricity, AI will impact everything. Therefore, technical skills will be just as critical as the human values, morals, and principles needed to pair with them.
Otherwise, problems may scale. Theoretical physicist Stephen Hawking captured our societal dilemma well when he said that “success in creating effective AI could be the biggest event in the history of our civilization. Or the worst.”
America should be taking note of Finland's initiative. Empowering people with the basic principles of AI, along with its potential pitfalls, is a strategic first step in equipping citizens for future civic engagement while also preparing them for the world ahead.
Visualizing Long-Life Learning
In many ways, human+ skills are similar to the concept of the T-shaped learner, which entered the lexicon in the 1990s. The T-shape describes the combination of an individual's breadth of knowledge with the depth of their technical expertise. (See Figure 1.2.)
But, in a world in which our work lives become longer and more unpredictable, even the concept of a T-shaped person will become outmoded. This figure will change shape and turn jagged as an individual moves through life, acquiring new skills along the way. Sometimes this will involve a broadening of knowledge; at other times, more verticality or additional technical skills will be called for, depending on our context. (See Figure 1.3.)
In a 100-year work life, there will no longer be a single transition from schooling to work. As we try to make sense of a longer, more turbulent work life, we must anticipate that learning and continual skill development will become a way of life.
Figure 1.2 T-shaped individuals combine broad knowledge and skills with deep expertise in a narrow field.
At the same time, this won't necessarily be a linear process. Stanford University's d.school (design school) came up with the concept of an open loop university, where, over a six-year period, learners could begin at any time in their lives and loop in and out of the school to gain skills, access community and expertise, and loop back out to apply that new knowledge.35 The challenge, of course, is that even six years will not suffice, as working learners will have to loop in and out of cycles of earning and learning over a dramatically longer period of time.
There will need to be more on- and off-ramps for long-life learning. Picture a cloverleaf interchange off a highway. We'll need to harness the power of education just as if we were taking that cloverleaf, gaining what we need, and smoothly reentering the workforce highway in a seamless fashion.
Of course, this begs the question: Where exactly will we be going to access long-life learning? Where will we develop our human+ skills?
Figure 1.3 Returning to learning throughout a 100-year work life.
The Never-Ending Debate on Education versus Workforce Training
Learning and work are becoming inseparable … indeed one could argue that this is precisely what it means to have a knowledge economy or a learning society. It follows that if work is becoming learning, then learning needs to become work—and universities need to become alive to the possibilities.
—Michael Barber, Katelyn Donnelly, and Saad Rizvi36
While future-of-work researchers are discussing the skills needed for the 20 or 30 job transitions to come, higher education appears to be stuck, perseverating on just that first transition from young adulthood to the workforce. The long-standing debate revolves around whether institutions of higher education bear any responsibility for the preparedness of graduates for the workforce. Reluctant to train learners for work, colleges and universities remain wary of aligning their programs and majors to the needs of today's rapidly evolving labor market, fearing that college might resemble too closely vocational or career technical training programs.
Academics have historically separated teaching and scholarship as an enterprise distinct from vocational training. Utility was what trade, graduate, and professional schools were for, whereas college was the space and time for students to pursue their passions and gain a global perspective. Regular opinion pieces and articles in the journals Inside Higher Ed and The Chronicle of Higher Education reveal this strong sentiment.
In one example, Tim Johnston from the Council of Colleges of Arts and Sciences explains that there is a “‘mistaken emphasis’ on a student's first job out of college. ‘A college education really is a preparation for life, it's not training for the first job you get,’ he said, adding that most people these days have ‘changeable and unpredictable’ career paths.”37 In a different piece for the New England Board of Higher Education, George McCully argues that “education certainly includes training, but is both broader and deeper, intensely personal and social—focusing on the cultivation of values. Education is more about who, training is more about what, students are and will become in their subsequent lives and careers.”38
Training for work implies a narrower kind of learning experience. Critics sustain this argument in order to suggest that employers should therefore own and leverage workforce training to keep workers up to speed on “useful knowledge and skills” for a rapidly evolving labor market.39 College is much better suited, McCully argues, for the “permanent and characteristic mission of higher education,” or things that do not go “in and out of fashion with changes in economies or technologies.” This is an argument about the timelessness of a college education—learning that is not specifically tailored toward work or “the what,” as McCully calls it.
This never-ending debate highlights a puzzling disconnect: Educators uphold the notion of durable learning that can last a lifetime and nod vigorously whenever the concept of lifelong learning comes up. But lifelong learning does not occur in some sort of vacuum, untethered to the world of work. Nor is it just about an older worker pursuing his or her curiosity or passion. Learning for a lifetime is also motivated by the practical and utilitarian needs of workers seeking to survive and thrive in their work lives. These discussions cannot be separated, as if something unique happens in a college education, detached from the learning and experience gained through work.
A False Choice
It makes little sense to continue to pit a college education against workforce training. The American Academy of Arts and Sciences put it best in its report on the future of undergraduate education: “Today, the long-standing debate over the value of a liberal arts education versus a more applied postsecondary program presents a false choice.”40
Education and work are one and the same. As economist Anthony P. Carnevale writes: “The inescapable reality is that ours is a society based on work. Increasing the economic relevance of education should, if done properly, extend the ability of educators to empower Americans to work in the world, rather than retreat from it.”41 Carnevale describes it as a modern wage equation:
If you write an equation for earnings, one of the first variables you put in it to predict earnings is your education, your field of study, but then the variables that start having real power are what you learn on the job, your opportunity to learn on the job—formally, informally—and the power of the technology that you work with . . . And remember, you may go to college for one year, two years, three years, four years, five, but you're going to work for 40, 45, or 50 years. So, it's naturally the case that the most powerful teacher is the job itself.42
Through the lens of human longevity, work becomes inextricably tied to education. This isn't and shouldn't be a philosophical debate. The artificial separation between career readiness skills and generalist or humanist skills exists only at an academic level. In the lived experiences of learners, work is a major motivating factor. For over 50 years, The Freshman Survey has asked first-time full-time students why they go to college. “[T]o be able to get a job” has always been the number 1 or 2 reason—certainly the top reason since the recession.43
