In the age of automation, learning and unlearning should be a lifelong pursuit
Tennis star Roger Federer dabbled in basketball, handball, skiing, wrestling, swimming, table tennis and skateboarding while growing up. When he began to gravitate towards tennis, his parents cautioned him against taking the sport too seriously. Essentially, when they discovered his love for sports, they encouraged him to have what author Dave Epstein calls “sampling period", which includes low risk experiments meant to organically discover what one loves doing and wants to succeed in.
Golf player Tiger Woods, on the other hand, specialized under his father’s tutelage before turning three. Wood’s learning path of early specialization has become the default template for schools and colleges who want to prime students for excellence. Even in the most modern workplaces, a disproportionate emphasis is paid on having narrow skills that are marketable. While there is nothing wrong having an area of focus, one should be mindful of the perils of early specialization. There are three key reason for that.
First, we tend to specialize without knowing why. More than 80% of people work in areas that have nothing to do with their field of study. In India, for example, most students first graduate from courses like engineering and then figure out what they want to do with their lives. Spending four years of one’s life getting deep into a subject one doesn’t particularly care about is a colossal waste of time, energy and money.
Second, it hinders lateral thinking, a problem-solving approach that draws upon seemingly disparate concepts and domains. Most innovators are lateral thinkers. Their lateral thinking is a direct result of combining different strands of thoughts and learning from different contexts. Leonardo Da Vinci combined art and engineering, Steve Jobs built upon the interconnectedness of design, fashion and technology, and Richard Feynman, a Nobel laureate in physics, is known to draw upon references from music.
Third, people with a narrow set of skills tend to approach every problem through the same lens. This not only ignores loopholes in one’s hypothesis but also amplifies biases. As investor Charlie Munger puts it, “To a man with a hammer, everything looks like a nail."
Challenging the norm
If early specialization can backfire, should we all snack on an array of ideas, insights and interests? No. The future belongs to deep generalists, a term popularized by JotForm CEO Aytekin Tank. These are people who combine two or more diverse domains and integrate them into something defensible and unique.
In the 21st century, with the mainstreaming of automation and artificial intelligence (AI), some jobs will become automated and some, redundant. Even highly trained professionals, radiologists, traders, programmers, might lose their jobs to algorithms if they are over-reliant on their narrow set of specialized skills.
On the other hand, deep generalists will not only keep their jobs but also be able to demand a premium for what they bring to the table. These are the professionals who will push the boundaries for creativity and innovation in the AI era. Their competitive advantage will propel them to learn, unlearn and develop innovative solutions consistently.
One of the best professional decisions I took in my early 20s was to invest a year studying liberal arts at Ashoka University. Studying anthropology, philosophy, history, literature, art and economics after a couple of years of work experience helped me understand what I wanted to do and why. Most importantly, it set me on the path to becoming a deep generalist by strengthening my lateral thinking ability. This is, of course, clearer in retrospect. I didn’t pursue the fellowship to become a generalist or a specialist. I was simply following my curiosity.
I chose to take a year out to study before heading for my MBA but there are many other ways to achieve the same goal.
As long as we can figure out a way to build or be a part of diverse learning communities, we can conduct several low-risk professional experiments to sample various options and double-down on ones that interest us. I am not saying that sampling will make all of us like Roger Federer or Richard Feynman but it will position us to take thoughtful career decisions.
In the age of widespread automation, learning and unlearning will be, and should be, a lifelong pursuit. Tools and technologies will constantly change. While this might unsettle those with a narrow set of skills, it will empower deep generalists to create new opportunities they have nurtured over years of building lateral thinking and conducting repeated experiments to figure how they want to contribute to the changing world around.
Utkarsh Amitabh is founder of Network Capital, a global peer mentoring community and a WEF Global Shaper.