Humility Is the New Smart

Rethinking Human Excellence in the Smart Machine Age

Edward D. Hess, Katherine Ludwig

• Publisher: Berrett-Koehler Publishers
• Year: 2020
• Print ISBN: 9781626568754
• eBook ISBN: 9781626568778
• Edition: 1
• Topic: Business
• Subtopic: Management
• Index: Business

Smart machines are replacing more and more jobs. Edward Hess and Katherine Ludwig show how to develop abilities that machines don't have so we can thrive in this Smart Machine Age. Underlying them all is a sense of personal humility: honestly recognizing our limitations and working to mitigate them.
In nearly every industry, smart machines are replacing human labor. It's not just factory jobs-automated technologies are handling people's investments, diagnosing illnesses, and analyzing written documents. If we humans are going to endure, Edward Hess and Katherine Ludwig say we're going to need a dose of humility. We need to be humble enough to let go of the idea that smart means knowing the most, using that information quickest, and making the fewest mistakes. Smart machines will always be better than we are at those things. Instead, we need to cultivate important abilities that smart machines don't have (yet): thinking critically, creatively, and innovatively and building close relationships with others so we can collaborate effectively. Hess and Ludwig call this being NewSmart. To develop these abilities, we need to practice four specific behaviors: keeping our egos out of our way, managing our thoughts and emotions to curb any biases or defensiveness, listening to others with an open mind, and connecting with others socially and emotionally. What all these behaviors have in common is, again, humility-avoiding self-centeredness so we can learn from and work with other humans. Hess and Ludwig offer a guide to developing these NewSmart abilities and to creating organizations where these qualities are encouraged and rewarded.

Part 1

A New Mental Model for the Smart Machine Age

1

The Smart Machine Age:
A New Game Requires New Rules

We can be humble and live a good life with the aid of the machines or we can be arrogant and die.

—Norbert Wiener

Norbert Wiener, an MIT mathematics professor and computer science pioneer, wrote those words in 1948 in a recently discovered unpublished essay for the New York Times. He literally meant them as an apocryphal warning about the dangers to humanity of uncontrolled advances in automation and artificial intelligence. For decades, such dire predictions remained on the fringe of societal concerns and relevant only to science fiction fans. The technologies that were only a gleam in Wiener’s eye, however, have finally come to fruition.

Smart machines are becoming autonomous and able to tackle nonroutine cognitive tasks previously thought the exclusive purview of people. Machines are gaining natural language capabilities, voice and facial recognition, and the ability to draft sports columns and analyze due diligence documents better and faster than many human reporters or lawyers. Thanks to advances in automated perception, sensors, and robotics, machines are now able to handle what had previously prevented them from tackling nonroutine manual jobs as well, such as driving cars, picking out products from warehouse shelves, and sorting mail. High-functioning human-oid robots can now be seen on hospital floors and in hotels, restaurants, museums, and shopping malls. They aren’t just flipping burgers behind the scenes: they’re interacting with patrons and patients—like “Connie,” the robot concierge Hilton began rolling out in 2016 in lobbies across the country in partnership with IBM Watson.

With respect to nonroutine cognitive jobs, using automated tools and algorithms, machines can now handle data analytics, pattern recognition, and deductive reasoning. Machines are becoming better than a roomful of Wharton graduates at devising portfolio investment theory for hedge funds and better than a team of Sloan-Kettering doctors at diagnosing illnesses.¹ With investments from companies like Google, implantable biometric sensors will soon allow us to monitor our own health.² Facial expression analysis software will detect the emotions and engagement of others better than our own minds.³ A group of researchers from MIT and the Masdar Institute, who conducted the first quantitative study of skill content changes in occupations between 2006 and 2014, concluded, “For any given skill one can think of, some computer scientist somewhere may already be trying to develop an algorithm to do it.”⁴

Combining the development of artificial neural codes and networks that model the human brain with access to Big Data, programmers can give machines the ability to process information and learn on a level that rivals and may soon exceed that of the human race.

Machines quite literally are now beating us at our own games. In March 2016 in what many artificial intelligence (AI) experts touted as the match of the century, AlphaGo—a computer program developed by Google’s DeepMind AI company—defeated South Korean Go master Lee Se-dol four matches to one in the ancient Chinese strategy game. Almost twenty years after IBM’s supercomputer DeepBlue bested the chess champion Gary Kasparov, AlphaGo’s victory still surprised many experts who predicted that it would take at least another decade to develop a computer program with the ability to outwit and out-strategize a Go master in arguably the most complicated human board game ever invented. The CEO of DeepMind, Demis Hassabis, said that algorithms used for AlphaGo “one day can be used in all sorts of problems, from health care to science.”⁵

Plenty of today’s technology experts, from Silicon Valley entrepreneurs to current MIT and University of Oxford academics, have sounded alarms about the potentially devastating impacts to our economy and society because of such recent and imminent technology advances.⁶ We repeat Wiener’s warning here, however, not because we believe that the robot apocalypse is around the corner but because we believe that it’s crucial to our relevancy as human workers and the vitality of the organizations for which we work that we pause and acknowledge the drastic changes coming and prepare ourselves to not only survive but to thrive.

We believe that there’s a path to successfully navigating these strange new highly automated waters, but many of us will have to fundamentally change our views of what it means for humans to be “smart” and what it takes for humans to succeed and reach their fullest potential. To do otherwise—to ignore the impact and fail to prepare for what’s to come—would indeed be a foolhardy exercise in human arrogance.

Smart Machines and a New Era

There’s a growing consensus among most computer science experts, economists, and business leaders that smart machines—whether humanoid robots or invisible networked connections—that can learn, think, and perform both manual and cognitive tasks in most cases better than their human counterparts could be the biggest game changer both personally and organizationally since the Industrial Revolution. It’s likely that the business, education, and leadership models created for the Industrial Revolution could become obsolete. Technological and scientific advances in artificial intelligence, the Internet of Things, virtual reality, robotics, nanotechnology, deep learning, mapping the human brain, and biomedical, genetic, and cyborg engineering could fundamentally change how all of us—from laborers to knowledge workers—live and find livelihood.

Technology that can learn and even program itself will become ubiquitous in homes, factories, and offices and soon displace even the highly educated people who have thought that their professions are immune to the risks of automation, including accountants, business managers, doctors, lawyers, journalists, researchers, architects, higher-education teachers, and consultants. Artificial intelligence—deep learning or machine learning—will be especially transformative in this regard. Speaking at a technology industry conference in May 2016, Jeff Bezos, the founder of Amazon, stated, “It’s probably hard to overstate how big of an impact it’s going to have on society over the next 20 years.”⁷

Andrew Ng, an associate professor of computer science at Stanford University, a chief scientist at Baidu, and chairman and cofounder of Coursera, recently told the Wall Street Journal: “The age of intelligent machines will see huge numbers of individuals unable to work, unable to earn, unable to pay taxes. Those workers will need to be retrained—or risk being left out in the cold. We could face labor displacement of a magnitude we haven’t seen since the 1930s.”⁸

Similarly, Kevin Kelly, co-founder of Wired magazine, says in his new book The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future: “It is hard to imagine anything that would ‘change everything’ as much as cheap, powerful, ubiquitous artificial intelligence.… The advantages gained from cognifying inert things would be hundreds of times more disruptive to our lives than the transformations gained by industrialization.”⁹

In the next two decades, technological advances could displace as many as eighty million US workers, according to the chief economist of the Bank of England,¹⁰ or 47 percent of the US workforce, based on a 2013 study by leading researchers at Oxford University.¹¹ According to a study by McKinsey & Company, by adapting technologies already demonstrated as of 2015, as many as 45 percent of the job tasks US workers are currently paid to do could be automated. Not even the most highly skilled or highly paid are safe. McKinsey also estimated that current technology could be adapted to replace at least 20 percent of a CEO’s work activities.

The result is that no longer will human scale be necessary for value creation in most fields. Without question, technology will transform how most businesses operate and are staffed in terms of both numbers and job requirements and skills. Routine jobs in hierarchical organizations—both those requiring manual and those requiring cognitive skills—will rapidly disappear. Most businesses in the near future will be staffed by some combination of smart robots, smart machines, and humans, and the job and skill requirements for each will be in flux.

In addition, the kind of long-term employment at stable organizations that characterized previous generations will be rare. The percentage of “contingent workers,” including part-time, temporary, and independent contractors, has been on the rise and recently made up a whopping 40 percent of the workforce, according to an April 2015 report of the US Government Accountability Office.¹² Another recent study predicted that by 2020, over half of the country’s workforce will be consultants, freelancers, and independent contractors, cobbling together their own gigs.¹³

Martin Ford, a Silicon Valley entrepreneur and the author of Rise of the Robots: Technology and the Threat of a Jobless Future, recently argued that “emerging industries will rarely, if ever, be highly labor-intensive”; rather, they’ll be more like You-Tube and Instagram, “where we’ve come to expect tiny work forces and huge valuations and revenues.”¹⁴ Similarly, Tony Wagner argues: “While the Intels, IBMs, and Genentechs of the last century employed hundreds of thousands (the majority of whom were low- and middle-skilled workers), the Googles, Facebooks, and Twitters of the 21st century will employ an order of magnitude fewer employees. Almost all of them will be creative problem-solvers.”¹⁵ Howard Gardner made a similar statement: “The future belongs to those organizations, as well as those individuals that have made an active lifelong commitment to learning.”¹⁶

In the age of these smart machines—what we’re calling the Smart Machine Age or SMA—operational excellence may well become almost totally technology-driven, making human innovation the key to value creation. Organizations will need their people to be hyperlearners who can adapt to rapidly changing environments. These needs are unlike what was required in the command-and-control-style organizations of the Industrial Age or more recently with respect to the repetitive and routine nature of knowledge work. Agility, adaptability, and responsiveness also will be required for most, and thus organizational efficiency will be necessary but no longer sufficient. The type of human learning that will be required is continuous and iterative learning, where one’s beliefs are constantly stress-tested against changing phenomena and adapted to better reflect reality. Those human processes are not efficient. In fact, they are hard and emotionally messy.

What’s Left for Humans to Do?

Humans can no longer add value by merely accumulating or analyzing knowledge. The creation of new knowledge is increasing exponentially, and it’s now believed that most knowledge has a less than three-year shelf life. What you think you “know” is so quickly out of date that you must continually update your learning. Moreover, it’ll be impossible for humans to know more facts or concepts than a smart machine or be able to process, remember, recall, pattern match, and synthesize more data faster or more accurately than smart machines such as Google’s AlphaGo and IBM’s Jeopardy!-winning Watson.

Instead, to be marketable and stay relevant in the SMA, humans will need to excel at the kinds of jobs and skills that either complement technology or are those that technology cannot do well—at least not yet. That list includes critical thinking, innovative thinking, creativity, and high emotional engagement with others that fosters relationship building and collaboration. Collectively we refer to these as the SMA Skills. (Note that by creativity we mean to refer to the original expression of ideas and thoughts, including through art and otherwise. By innovation, we mean to refer to the commercialization of new ideas, methods, or things.)

Other jobs that will remain in the near future are those manual jobs requiring customized tasks and physical dexterity, but here we’re focusing on the cognitive skills remaining for the majority of us who consider ourselves knowledge workers. Regardless of job or position, most of us will have to think and behave more like scientists, entrepreneurs, and artists and better engage socially and emotionally with others. The SMA Skills amount to our summary of the conclusions drawn by leading business and education leaders, economists, and researchers at MIT, Oxford, McKinsey & Company, the World Economic Forum, and the National Educational Association, among many other experts on the most important human skills in the twenty-first century.¹⁷

The purpose of this book, however, is not to justify or debate the primacy of the four SMA Skills or t...

Table of contents

• Cover
• Title Page
• Copyright Page
• Dedication
• Contents
• Introduction: Why You Should Read This Book
• Part 1: A New Mental Model for the Smart Machine Age
• Part 2. NewSmart Behaviors
• Part 3: The NewSmart Organization
• Your NewSmart Organizational Assessment Tool
• Epilogue: Our Invitation to You
• Notes
• Recommended Reading
• Acknowledgments
• Index
• About the Authors