Tennis star Roger Federer dabbled with basketball, handball, skiing, wrestling, swimming, table tennis and skateboarding as a kid. 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—low risk experiments meant to organically discover what one loves doing and most wants to succeed in.
Golf legend Tiger Woods, on the other hand, specialized under his father’s tutelage before he turned three. Wood’s learning path of early specialization has become the default template for schools and colleges that want to prime students for excellence. Even in most modern workplaces, a disproportionate emphasis is paid on having narrow skills that are marketable. While there is nothing wrong in having an area of focus, one should be mindful of the perils of early specialization. There are three key reasons for that.
More than 80 per cent 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.
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.
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.’
So, if early specialization can backfire, should we all snack on an array of ideas, insights and interests? The short answer is no. The future belongs to deep generalists, a term popularized by JotForm’s 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 AI, some jobs will be automated and some would become redundant. Even highly trained and accomplished professionals— radiologists, traders, programmers, etc.—might lose their jobs to algorithms if they are over-reliant on their narrow set of specialized skills.
On the other hand, deep generalists not only will 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 of creativity and innovation in the AI era. Their competitive advantage—a unique combination of breadth and depth—will propel them to learn, unlearn and develop innovative solutions consistently.
One of the best professional decisions I took in my early twenties was to invest a year studying liberal arts at Ashoka University. I was part of the first cohort of Young India Fellowship where 57 of us learned the art of connecting ideas from different walks of life. 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 experi- ments 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 make thoughtful career decisions.
In the age of widespread automation, learning and unlearning will 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 for building lateral thinking and conducting repeated experiments to figure how they want to contribute to the ever-changing world around them.
