Technology is the Spell, Creativity is the Wizard
Every day we interact with tomorrow. Cars drive themselves and wake us up when we’ve arrived. Toasters pronounce our names. Nanobot drugs know our medical history before we swallow them. We deposit checks with our smartphone cameras. In every corner of the economy, from small service businesses to large industries, the pattern is the same: automation and artificial intelligence are replacing humans. Truckers have diagnostic tools that network with big data, identify future mechanical trouble, and save them a trip to the service station. Farmers program drones to monitor their crops. Surgeons perform low-risk operations with VR gloves, letting robots perform their incisions while their hands are zip codes away.
Not even professions based in the humanities evade the impact of this shift. Miss last night’s game, and the recap you read could have been written by an algorithm, one that crunches all the cliches of sports-writing and translates them into every major language. File a dispute on eBay, and there’s a nine out of ten chance your case will be mediated by automated legal software. Of course, with every innovation comes adaptation. Bank tellers get their hours cut. Service stations for truckers hang up GOING OUT OF BUSINESS signs. Fast food employees hand their hairnets over to order-placing consoles and e-payment systems. And while the debate over immigration rages on, an understanding of the future of jobs, and who will fill them, remains elusive.
People are not losing their jobs to other people they’re losing them to robots, to technological innovations, and to changing consumer demands. Innovations in automation account for 80% of lost manufacturing jobs, and production and manufacturing is more efficient than ever. Mass manufacturing jobs may move back to high GDP economies, but factories will most likely be staffed by machines, not people.
We know the middle class has become hyper-specialized, and the working class has shifted from the factory to the service counter, but even these jobs may be in jeopardy. The Bureau of Labor Statistics predicts that 75% of the next decade’s fastest growing occupations will involve some form of outpatient healthcare and a hospice worker might just show up at a client’s house to discover a home companion robot refilling the client’s pill box.
Klaus Schwab, founder of the World Economic Forum and a Ph.D in mechanical engineering, economics, and social science, has spent over 50 years surveying and striving to understand these seismic economic changes. At the beginning of 2016, he declared that our modern economic and social lives were on the brink of a technological revolution, one that will forever change how we live, work, and relate to one another. Here’s how Schwab laid it out:
In its scale, scope, and complexity, the transformation will be unlike anything humankind has experienced before. We do not yet know just how it will unfold, but one thing is clear: the response to it must be integrated and comprehensive, involving all stakeholders of the global polity, from the public and private sectors to academia and civil society.
Schwab calls what we’re experiencing a Fourth Industrial Revolution. Let’s put that in context. The first two Industrial Revolutions enhanced efficiency through natural resource exploitation: first came the steam power of mechanization and then the electricity and fossil fuels of mass production. For the Third Industrial Revolution, the lynchpin was the transistor: the ability to encode vast flows of data and coax that information into processing itself. Now, in the Fourth Industrial Revolution, economies are evolving to handle and process our enormous mass of accessible information. With so much information available and so many methods of analysis, access to knowledge is no longer the challenge.
Everything is connected, and these connections happen instantly. The challenge of the Fourth Industrial Revolution becomes interpretation, reflection, and innovation. How do we create new value out of our hyperconnected knowledge?
As Schwab says, this has staggering implications for how we live, work, and relate to one another and the world around us, not to mention how we govern, teach, learn, and exchange ideas. These changes in our midst breed more questions than answers. How will leaders manage this explosion of progress and efficiency so it doesn’t vacuum up the planet’s resources or exacerbate global inequality, what Schwab calls the gap between returns to capital and returns to labor?
What is the future of work, labor, and workforce training? What new ways of thinking, what new skills, and what new habits can we teach to ensure people find shelter in these storms of change? And how can we make sure that our answers to these questions form a cohesive story, one that rings true for both local communities and global connections? In short, how do we take all this change and make from it opportunity?
The Skill of Meaning
First, let us emphasize that a conversation about skills is a conversation about inequality. Globalized supply chains, advances in connectivity, and automation have grown the demand for high skill/high pay workers and shrunk demand for low skill/low pay workers. Less relevant middle skills result in a hollowed out middle class. And all this leads to apprehension and community fractures. Inequality is a tricky subject, because it’s easy to tell different stories about the same facts and figures, albeit those from different regions. Certainly, for example, median wages for workers compared to productivity have stagnated in the U.S. since the 1970s. And the gap between the wealthiest and the poorest citizens in the U.S. has widened.
But the story changes when you pick a different protagonist. In Japan and some European countries, for example, that same gap has narrowed over that same timeframe. Many economists agree that global income levels have actually risen over the last several decades. And Charles Kupchan
Georgetown University Professor of International Affairs, reports that the collective GDP of Brazil, Russia, India, and China is likely to match that of today’s leading Western nations by 2032, according to a prediction by Goldman Sachs.
If we aim for a fair depiction of the entire scene, what appears true is that globalization has led to increased spending power across the globe, which in turn has led to new generations of consumers picking up middle class habits like buying more entertainment, buying more leisure, buying more health in short, buying more depth and meaning for their time.
Technology is the Spell; Creativity is the Wizard
And this is where creativity comes into play. Oceans of information generate currents and patterns, and machines are great at making sense of patterns. But while machines are great at patterns, human beings are uniquely capable of making meaningful experiences out of those patterns. Meaningful is the key word. If something crazy happened in last night’s game, a computer’s recap can provide the facts and figures, but none of the clutch shot’s excitement, or its relevance to the game.
When computers attempt that kind of meaning making, they have a hard time knowing where to stop. In 2017, research scientist Janelle Shane created an artificial neural network to invent new paint colors and names. The result was a sludgy mix of browns, beiges, and grays with nonsensical monikers like “clardic fug” and “stargoon”. If this is artificial intelligence’s idea of creativity, it might be trying a little too hard.
Nor can pattern-crunching solve problems outside of the pattern. Diagnostics can measure known associations to make sure a truck doesn’t break down in the usual ways, but it has a harder time realizing that spotting an error in design can actually become a pathway to a better truck. Machines might beat us at pattern application and replication, but we still beat machines at pattern rearrangement and disruption.
Frank Barrett, jazz pianist and professor of management at the Naval Postgraduate School, defines this as a person’s ability to dislodge their routines so that they pay attention. Creative thinking begins with an embrace of the world’s chaos, inviting us to reconsider challenges, assets, and opportunities in a new light. When we’re evocatively startled, we can make startling new connections and new solutions. We can root out lost memories.
In a 2017 New York Times essay about humanity’s unique habit of thinking about the future, psychologist Martin E.P. Seligman and science writer John Tierney sum up this concept rather beautifully: We learn not by storing static records but by continually retouching memories and imagining future possibilities. Those connections and memories allow us to understand and solve complex problems and deepen our relationships. In an essay for 2013’s The Handbook on the Experience Economy, Albert Boswijk cites the example of tomorrow’s pacemaker supplier who needs to focus not only on improving his device but also enlarging the user’s world and make it possible for the patient to feel safe no matter where he goes.
This requires a deep understanding of humanity’s daily routines and experiences, which requires creativity that data alone can’t muster. As computers use big data to smooth out so many little mysteries, the big ones continue to perplex our day-to-day lives with even more ferocity.
Our need for novel experiences and innovative solutions will only sharpen. Creativity fuels innovation even outside the domain of the creative economy. In 2008, Beijing university students built atomic force microscopes out of LEGOs. The inventors of Lotusan, a self-cleaning paint, got their idea from butterfly wing topography. J.mtkraft, a Swedish utility company, built an energy storage model based on cloud computing principles. At the Eastman Chemical Company’s Innovation Lab, a graphic designer is in charge of material science innovation, and she is the brain trust behind serious inventions like using synthetic rubber and acetate yarn to build guitars out of cellulose which might just save an entire species of Brazilian rosewood.
In all these cases, we see creativity: play, rambles, collaboration, new angles for old tricks, breakdowns of categories and hierarchies, weird questions, strange connections, odd bedfellows, and spiky dreams. The technology to help develop and implement these sorts of creative solutions is cheaper and more widely available than ever. But technology even at the frontiers of machine learning and quantum computing is hard-pressed to look at a wet butterfly wing and think Oh, paint! Engineers can write the cleanest code in town, but that won’t matter much if that code is executing tired, outdated ideas.
Technology might be the spell, but creativity is the wizard.