The key to your future? Do the work only humans can do
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With each passing day, new technologies are automating more of the work that humans have done for generations. And the capacity of those technologies to do a human’s work is growing exponentially. According to a Silicon Valley research group called Open A.I., the capacity of artificial intelligence is doubling every 105 days or so. In fact, it has grown by more than 300,000 times since 2012.
How are we supposed to stay relevant in a world like that?
I can think of two ways.
The first is to try to master the work that these technologies are doing. Lots of folks in our profession apparently are expecting accounting and finance pros to do just that. According to the folks at Bloomberg and LinkedIn, the number of job listings in our profession that require training in artificial intelligence, machine learning, and data science grew by almost 60 percent in the past year. Here's what CNBC's Jennifer Liu writes:
"According to Glassdoor data, 'some of the most common job openings in A.I. and finance are for machine learning engineers and data engineers, among other highly specialized software engineering roles,' Glassdoor senior economist Daniel Zhao tells CNBC Make It. 'We’re also seeing job openings for workers who can help navigate the A.I. landscape, including consultants and researchers. As companies establish the foundations for their A.I. functions, we’re seeing employers hire more senior candidates to lead these new teams.'”
Here's my problem with this approach: Given the exponential rate at which these technologies are advancing, how long will it be before they learn to do these high-tech functions themselves? Competing with the machines on their own turf seems like an exercise in futility.
A better strategy might be to learn the skills that these new technologies can't master. As futurist Peter Sheahan says, "Humans should only do work that only humans can do." Anything else will probably be automated at some point down the road.
So what can only humans do?
Harvard Business Review's Stephen M. Kosslyn breaks it down into two areas:
- Emotion: "Emotion is not only complex and nuanced, it also interacts with many of our decision processes," Kosslyn writes. "The functioning of emotion has proven challenging to understand scientifically and is difficult to build into an automated system."
- Context: "Humans can easily take context into account when making decisions or having interactions with others. Context is particularly interesting because it is open ended — for instance, every time there’s a news story, it changes the context in which we operate. Moreover, changes in context can change not just how factors interact with each other, but can introduce new factors and reconfigure the organization of factors in fundamental ways. This is a problem for machine learning, which operates on data sets that by definition were created previously, in a different context."
Great thoughts there, but my colleagues at the Business Learning Institute believe there are at least five other uniquely human skills that machines will have difficulty mastering. Those skills are part of a model that we call the T-Shaped Professional.
The vertical part of that T is made up of deep technical knowledge that all CPAs must master — the table-stakes accounting and finance skills that form the foundation of a CPA's expertise.
The much wider, broader, horizontal part of that T are where our future-focused skills reside. Study after study have identified some variation of these skills as being critical to our future success. BLI officials have boiled that research down to these five critical future-ready skills:
- Anticipating and serving evolving needs
- Strategic and critical thinking / synthesizing intelligence to insight
- Integration and collaboration
The more of these skills we can master, the more future-ready we will become. Master these skills and we'll be able to do the things the machines cannot. That will be our competitive advantage in an age of automation.
Learn more about the skills you'll need to become future-ready by visiting MACPA.org.