Investing in artificial intelligence isn’t necessarily a zero-sum game in which machines win at the expense of human workers.
Today, driving a truck is just about the most commonplace job around, and its ubiquity is fueling much of the concern around what automation and artificial intelligence will do to an industry that employs millions upon millions.
But that wasn’t the case several decades ago, Grant Thornton’s leader of applied AI and advanced technology Dr. JT Kostman shared Monday at CES in Las Vegas. In fact, during his own father’s heyday the most populous employment capacity was as a…stevedore.
You’re forgiven if you’re not even remotely familiar with a word that’s dropped out of—or was never even part of—the average American’s lexicon. Scores of stevedores, also known as longshoremen, played a significant role in powering the economy, unloading tons of cargo from ships arriving at ports from around the world. But technology changed all of that, multiplying the speed at which a shipping container moves from ship to shore, decimating the ranks of stevedores worldwide but enabling new economic heights and business possibilities.
Maybe there was some hand-wringing when stevedores saw the writing on the wall all those years ago but is anyone bemoaning lost careers doing the hard labor of carrying cargo off of freightliners today? Hardly. Because where one employment path fell by the wayside, numerous others sprung up in its wake—jobs previously unconceivable.
And that, Kostman stressed, is how industries should be thinking about AI and its impact.
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It will inevitably change the world as we know it, creating a new future with possibilities our limited perspective can barely comprehend. Not only will AI take much of the dreaded grunt work out of daily lives, but it’ll also eliminate the lousy versions of jobs that humans currently do, said Cory Treffiletti, CMO for Voicea, a platform bringing voice technologies into the enterprises.
A tale of two credit card fraud alerts crystallizes the opportunity for AI to trump unpredictable humans. Kostman described receiving an alert from one credit card instructing him to dial into its call center for further instructions and assistance. After a maddening 49 minutes on hold waiting to be connected to a human operator, he finally spoke with a “sullen” customer service rep who soured his experience further. Two minutes later, the fraud issue was resolved and the nightmare call ended.
On the other hand, while traveling in Sydney, Kostman received a fraud alert related to a different card. Up popped a note from a chatbot in Australian slang asking if he was in fact using his card Down Under. In a matter of moments, an AI-powered bot understood his location and context, addressed him as such and provided an experience light years beyond the phone-call horror story.
In the right place at the right time, AI lends a helping hand where sometimes a person just doesn’t exactly add value.
At Stitch Fix, machines and humans together deliver an experience that either alone cannot, said chief algorithm officer Eric Colson. Machine learning will always be better and faster at searching through millions of styles en route to combing attributes to create a new pattern, but the insight and human touch are needed to tweak and edit that AI-created product and bring a bit of empathy into the mix.
“Sometimes algorithms do silly things,” Colson said, adding that human intervention can help to nip potential problems in the bud. “You learn by watching clothes interact with clients.”
The Netflix alum, who’s been with the Bay Area fashion-on-demand firm for six years, attributed much of the algorithmic innovation happening inside the company to the data scientists themselves, thanks to an emphasis on “bottoms up processes” that encourage employees to identify metrics-driven areas of opportunities—backed by data, of course.
Algorithms are so powerful because they require virtually no capital outlay, come with little to no risk and provide a “tremendous impact” with a use case already validated by data, Colson said. And because they’re based on proprietary data, competitors can’t copy them—providing a serious strategic advantage.
But as great as they may be, AI and algorithms for the foreseeable future need human empathy to filter through some decidedly personal complexities. Because what’s a machine to do when a Stitch Fix customer writes a heartfelt note explaining that she needs a dress to wear to her “ex-boyfriend’s wedding?” Colson said.
Only a fellow peer who can relate to that experience can navigate such delicate, anxiety-ridden territory. As Kostman put it: people are bad at what computers are good at, and vice versa.