Think Deeply to Keep Your Job in the Artificial Intelligence Future
The winners of the coming age of Artificial Intelligence will be those who can choose between what’s meaningful and what’s not.
The future of knowledge work, such is the general perception, will entail a shift from processing mundane chores to performing high-value tasks that require creativity and strategic thinking. Machines will take over repetitive, easy-to-replicate, often administrative jobs while we lucky humans can finally focus solely on developing visions of how to bring good to the world.
If we can, that is.
From what I can tell, we’re doing well training the machines to do the dumb stuff. But how well are we training ourselves to do the smart, high-value stuff?
I’m not referring to education, but to the difference between work and busyness. Back when I first joined a large company I was fascinated with the idea of remote work.
“But how does the boss know,” I asked a colleague, “that you’ve actually been working the whole day?”
“Well,” he answered, “she trusts me, of course. But even if she didn’t, I guess I could always prove that I’ve been working constantly by showing her my sent items in Outlook.”
Although I didn’t realize it at the time, something is fundamentally wrong with this scenario, even though it may seem perfectly reasonable at first. Your sent items prove that you’ve been writing and answering emails constantly.
You’ve been busy, all right, but have you been productive? You’ve been focusing on low-attention tasks for eight hours when you could have tackled something big, something that requires deep thoughts. Or maybe you actually meant to have a go at the high-value work, but every other minute you were startled from your concentration by an incoming email or instant message. And as if that weren’t bad enough for your focus already, you might have also been actively looking for distraction by surfing the web or tweeting.
It’s hard to stop fragmenting your attention once you’ve become accustomed to it. As Daniel Levitin describes in The Organized Mind, multitasking creates a dopamine addiction feedback loop: the brain is rewarded for losing focus, so we constantly search for external stimulants.
Let’s assume what’s just been described are our normal eight hours in theworkplace, with a meeting or two (or more) in between. Let’s imagine we do this day after day for weeks or months.
What does this mean for our brains, for our ability to focus? What will happen when we try to actually take on a task that requires undivided concentration for hours on end? Will we still be able to pull it off?
The promise of Artificial Intelligence is an enduring break for us humans from the mundane activities that stuff our brains and keep us from work that matters: design the desirable, make cyberspace secure, work out strategies for the good of humanity, and so on.
How can we ensure we’re able to fulfill our part of the bargain? Most of us focus on multiple easy, mundane tasks, instead of one big thing that could really make a difference. Why?
Well, for one it’s easier to write a bucket-load of emails or tweets compared with working out a new marketing strategy. Also, knowledge workers are often missing a concrete sense of accomplishment when their contributions to a company’s results are not always observable or measurable. Hitting the send button 700 times or being in meetings all day are measureable. Thinking deep thoughts while staring into space for an hour is not.
To me, this is an explanation why in my generation (I’m turning 35 this year) I hear so many stories about managers, investment bankers and other knowledge workers who – helped along in some cases by a little burnout – decided to leave the office world to bake cupcakes or grow organic apples or restore old violins. At the end of the day, you can count your cupcakes, your apples, or your violins. You have an actual physical proof of what you’ve been doing with your time.
In the office, what’s the equivalent of baking cupcakes? It’s sending emails.
And here’s the catch: it won’t be long now until this kind of low-level, but visible activity will be assumed by machines in industries from advertising to retail. Chatbots will take over answering customer requests up to a certain level of complexity, and virtual assistants will schedule our day and do our travel arrangements. When that happens, we humans will be thrown back on ourselves and our attention spans that have been constantly hacked over the past years by network tools such as twitter, instant messaging and, of course, the ever-present emails.
In his book “Deep Work. Rules for Focused Success in a Distracted World,” Georgetown University professor Cal Newport claims network tools are to blame for many of us being no longer capable of enduring, focused thinking. “Spend enough time in a state of frenetic shallowness and you permanently reduce your capacity to perform deep work,” he says.
Newport defines Deep Work as “Professional activities performed in a state of distraction-free concentration that push your cognitive capabilities to their limit.” As opposed to Shallow Work: “Noncognitively demanding, logistical-style tasks, often performed while distracted.” He points out a growing necessity for the ability to perform deep work and prognosticates a career advantage for those who have this ability, as it’s increasingly becoming very rare.
Newport goes on to suggest behaviors and strategies to work (more) deeply while still considering the use of collaboration when appropriate – for individual knowledge workers as well as for organizations. The first step would obviously be to wean your mind from the distraction it’s craving.
Long-term undivided focus can be learned. And we need to train our minds with this skill or we won’t be up to the tasks machines famously cannot do because they require creativity, emotional intelligence and strategic thinking. These skills have something in common: they are difficult to measure and difficult to connect to indicators of productivity. We’re applying all of them already but it’s hard and often unsatisfying, because we’re not used to it and we’re not giving it priority.
True knowledge work might just not require constant connectivity with its overwhelming flood of distracting information, but rather large chunks of time being disconnected. The crux of Artificial Intelligence might not be that there will be no jobs for humans left – but only a few of us might be have the skills to fill them.
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