Spend 20 minutes exploring a cool climate change data visualization. Search for the release date of Google’s self-driving car.
Check how many “circles” you’ve completed on your Apple watch. This is just a typical day for many in today’s data-heavy world. It’s also a paramount moment in culture. Data has never been such a ubiquitous part of our lives and our work. Although it seems like we already have enough data for two lifetimes, all signs are pointing to more, more, more. In fact, using data to inform business decisions is becoming more prevalent every day.
A recent Duke University survey of 288 chief marketing officers found that brands are expected to nearly double their marketing analytics budgets by 2018. Why? Because big data is now seen as an essential component for competitive growth.
A study by Accenture and GE found that 74 percent of enterprises say their main competitors are already using big data analytics to successfully differentiate their competitive strengths with clients, media and investors. More than 90 percent of enterprises are seeing new competitors in their market using big data analytics as a key differentiation strategy.
These increases could mean good things for data science majors. Positions that require data analysis are expected to grow at a pace of 14.5 percent between 2012 and 2022, about 10 percent faster than the expected rate for non-data jobs.
Does this mean “analysis” should be in everyone’s job title in the future? Not exactly. As businesses take up arms in the data race, they’ll quickly find that not all data is created equal. Currently, there are just as many limitations as opportunities. In fact, so much data is collected that analysts spend much of their time separating the “good” data from all the junk.
But framing this “good data” as truth is a dangerous idea, especially when it attempts to quantify the theoretically unquantifiable. Take beauty, for instance. The first International Beauty Pageant judged by robots is making headlines. To enter, it requires participants to take selfies that will be judged by an algorithm. Although this could mean big things for the beauty business, it means dystopian things for human worth. We all know that perceptions of beauty are influenced by factors beyond the mathematical proportions of facial features. We don’t fall in love with someone just because their features follow the golden ratio. Despite that, it will be harder to believe that beauty is in the eye of the beholder when a data point tells you you’re in the bottom percentile.
Data can also be misattributed or skewed to tell a story. Watch the comments and articles that follow a presidential debate and some headlines will proclaim one candidate the winner, while others will say the same candidate lost. And yet, they all have the data to back up their conclusions.
Scientists know this all too well. Data-based research that was once lauded suddenly becomes marred because the experiment wasn’t set up correctly or the data wasn’t truly conclusive. Based on this scientific propensity for inconsistencies, Stanford biologist John Ioannidis went as far as saying that most scientific research findings are false.
Not even altruistic companies that vow to change the world are safe from data folly. Food startup Hampton Creek recently came under firefor overhyping a vast data analysis of 4,000 species of plants at the core of the company’s innovation plans. Former employees told a different story with some saying the number tested was “closer to 400.”
At this rate, data insights may become the new snake oil: something that everyone promises but few can actually deliver.
Ready or not, the automation of everything is on the horizon. As humans, we’ve moved beyond using data for simple knowledge and insights; it’s becoming a gateway into artificial intelligence. If you think IBM’s Watson is impressive, then you should read up on The Master Algorithm. Once successful, the algorithm will be able to learn anything from a given set of data points. According to Pedro Domingos, the author of The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, the algorithm will, for example, discover Newton’s Laws if given data about the planets’ motions, inclined planes and pendulums. Give it DNA crystallography data and it discovers the double helix.
Many distinguished thought leaders are against this techno takeover (ahem, Stephen Hawking). One of the primary concerns is that data and automation have the power to disrupt our economy. An Oxford University survey suggests that 47 percent of the world’s jobs could be taken by machine learning in the coming decades.
And the jobs that are most at risk may surprise you. Some theorists believe jobs that require intense mental work, like practicing law or medicine, will be the easiest to automate, while jobs that interact with the physical world and use common sense, like being a custodian, will be much more difficult.
Common sense is defined as sound judgment derived from experience rather than study, making it extremely difficult for machines to acquire. It’s what makes you avoid the shortcut through the alley because it looks spooky and you’ve watched too many horror movies. A computer can’t pick up on that. A computer relies on patterns to make decisions and choices. It’s our humanity that allows us to glean insight without a pattern.
Being human is what allows us to turn against all the mounting data that tells us we’re wrong. And some of the smartest people in the world think it’s necessary. Electric car tycoon and soon-to-be Mars colonizer Elon Musk says it best: “If something is important enough, even if the odds are against you, you should still do it.”
Why wait until the next decade when you can start using your humanity now? Several brands are already leading the charge.
JetBlue’s focus on humans instead of data has brought it huge success in air travel. Since 2007, even during the worst of the Great Recession, it has stood by its “Customer Bill of Rights” and has chosen to offer a human-centric compensation plan instead of blindly following data that would have led it to cut costs. This commitment behind JetBlue’s purpose of “bringing humanity back to air travel” has fueled its continued success. In its most recent earnings report, net income was up 151 percent.
Tribeca Shortlist is a new human competitor to Netflix. Instead of using an algorithm, the site is curated by both celebrities and influential “shortlisters” who showcase their favorite films. The creators believe that human curation will lead to a better viewing experience.
Rickshaw Bagworks is a human-centric messenger bag company started by Stanford grad Mark Dwight. The company isn’t driven by the bottom line, but instead something more. Dwight strives for a low-volume output that he refers to as “human- powered operation.” “We’re not here to make as many bags [as] possible,” he says. “We’re here to make as many bags [as] necessary to run the business we want to run.”
There’s a growing and powerful trend of making human-first business decisions. What is often forgotten is that behind every app notification, business-lift statistic and website cookie is human intelligence. It takes people to make technology possible. As data rises, so do humans. Instead of praising big data, it’s time to praise big humanity. If we trust our instincts, there’s no limit to how far we can go.
Here are five ways to start:
- Have a purpose and follow it, no matter what. Logic be damned—if you think it’s worth doing, it probably is.
- Look for human loopholes. User-experience designers are great at this. Sometimes the best way to solve a problem is just by approaching it in a more human and empathetic way.
- Embrace more opportunities to be data-free. Put the devices down and let your mind wander. Let it make connections to new solutions that defy pattern and logic like only humans can.
- Invest in accruing more common sense. Ask questions. Try something new just to see what happens. Make friends with more children—they’re full of it.
- Collaborate whenever possible. Robots work alone. But as humans we know it’s more productive, creative and enjoyable to work as a team. What do you have to lose? Plus, humanity has the benefit of drinks—celebratory or sympathetic.