More than a year ago, in the very early days of the electoral race for U.S. president, an artificial-intelligence startup called Emotient — since acquired by Apple — decided to have some fun and apply its facial-expression-analyzing, emotion-reading algorithms to the Republicans vying for the GOP nomination.
The results? Ted Cruz “almost exclusively expressed ‘sadness.'” Jeb Bush conveyed a mixture of “neutral,” “surprise” and “joy.” And the eventual nominee, Donald Trump, predominantly expressed “anger”… which likely came as little surprise to either his supporters or critics.
While subjecting public figures on the campaign trail to AI-powered scrutiny isn’t likely to raise many eyebrows, applying such technologies to average people in contexts where they might not expect it is another matter. But that’s increasingly what organizations — governments and businesses alike — are doing.
Speech-analytics technologies, for example, are being increasingly deployed in settings like call centers, contact centers and other operations to provide insights — often in real or near-real time — to support and service professionals fielding customer calls. At least one market research company says these applications have become “must-have” technologies for businesses that want to “mind the wealth of information freely shared with them during customer service conversations.” But how freely would people really share their thoughts if they realized how closely their every word and inflection was being scrutinized?
Nicholas Carr, the U.S. writer famous for — among other works — a 2008 article asking, “Is Google Making Us Stupid?” has a word for such tech applications: “creepy.”
Carr uses that word in the title of his new book, “Utopia is Creepy: And Other Provocations,” which his publisher calls, “a freewheeling, sharp-shooting indictment of a tech-besotted culture.” Carr argues that, despite the undisputed benefits of so many IT innovations, these technologies have also resulted in “little real empowerment” and “a culture or distraction and dependency.”
“What I want from technology is not a new world,” Carr writes. “What I want from technology are tools for exploring and enjoying the world that is — the world that comes to us thick with ‘things counter, original, spare, strange,’ as Gerard Manley Hopkins once described it.””
Esteban Kolsky, an ex-Gartner analyst who now leads ThinkJar Research, expresses similar reservations about how many technologies are applied — or, often, not applied — to customer service in particular.
“Fifty-five percent of requests in social and social channels get ignored,” Kolsky recently told Small Business Trends. “Ignored! Imagine if you don’t pick up more than half the phone calls that you get… What about half the people that come to your store. You ignore them. You don’t talk to them. You don’t ask them what they need.”
Kolsky says that many so-called “solutions” for customer service simply don’t deliver because organizations aren’t using them in the right ways. They’re not responding to most questions and requests on social channels. They’re not providing easy-to-find answers to the questions customers have. And they’re not really providing smart, effective communications across channels.
“Basically the bottom line is if you have good interactions with customers over time you form a relationship,” he said. “If you have a relationship with customers over time and it generates trust, then that turns into engagement. Engagement is an outcome it’s not a metric. There’s no way you can measure it. So don’t try. If I know you well enough and I generate enough trust, and you know me well enough and generate enough trust, over time that turns into engagement. That’s what I can do about engagement.”