Search
  • Hugo Menard

Why starting early and being specialised isn’t always the best thing


Have you ever thought “I wish I started learning/doing/practicing xyz sooner”? Or felt like you were behind because you didn’t have as much knowledge/experience as someone else?


There’s this assumption that the earlier we start, the more structured and disciplined training we have, the more experience we have in a specialised field, the better off we’ll be.


We are getting more and more specialised. Before we just had doctors, then there were doctors specialising in things such as cancer. But now we have doctors that are specialising in just one type of cancer. We also hear stories of people like Tiger Woods who started swinging a mini golf club before his first birthday. But is starting early and being highly specialised the best approach?


When we look at the bigger picture, it turns out it’s not quite as simple as: start early + lots of structured practice = high level performance/success.


For example, if you look at many of the top athletes, they actually tried out a few different sports to begin with. They experimented with what they might like, saw where their strengths were and didn’t begin to specialise straight away. It was only after this sampling period that they began to focus more specifically on one particular sport. It’s at this stage that they put in more hours than others and saw the results (mind you, other factors also play a role).


A good example of this is Roger Federer. In his early years he enjoyed all kinds of sports as long as there was a ball involved. Even once he started playing tennis, he actually chose not to train with people in a higher group at his tennis club because he enjoyed talking with his friends after practice. By the time he became sincere about his tennis training, other peers his age had already been working with strength and nutrition coaches for some time.


The sampling period is often seen as a waste of time, but it turns out it’s critical. Counter to what we generally think, it’s more common for top athletes to have this sampling period and then specialise than for top athletes to have specialised right out of the gate.


This shows that a more human approach really is beneficial. Rather than trying to engineer specific outcomes and grind away at it until we get there, we can relax and explore. We can follow our interests without the fear of “wasting time”.  This is because all those things we try not only help us find something that is a better fit, they can also benefit us later on. We can draw from those experiences, have more breadth, and a more enriched and unique point of view that others won’t have.


Even the idea of specialisation at any stage is over valued. It can work well for things that are unchanging, predictable and repeatable. Sports is a good example, you hit a ball with more and more accuracy, you see other players hitting a ball towards you and over time you learn to instinctually read tiny nuances that tell you where that ball will land and how it’s going to bounce.


However, this repeatable quality found in sports is not reflective of work in most areas. Rules in the real world aren’t as clear cut and not everyone plays by them. The need for adaptation and seeing things differently is often far more valuable. And with the world changing at an ever increasing pace, that ability to adapt and have a broad range of skills will likely become ever more valuable.

When more experience = worse performance


A firefighter may make decisions in fractions of a second that can save someone’s life, precisely because they recognise patterns in house fires. But if that fire is happening in a skyscraper or a situation they haven’t encountered before, that experience can hinder rather than help. They’ve gotten used to always seeing predictable, repeatable patterns, but it means that in new situations they are more likely to freeze up or make poor decisions.

This is partly because the more ingrained their patterns, the harder it is to override them and think in agile and differently ways. They may see a pattern that they instinctively recognise as meaning one thing, but because they’re in a different situation, it actually means another.


When we learn that something works (like hitting a golf ball just right) we can repeat that over and over to get the same result. But it turns out that if you need to learn something new, respond to a new situation or make a new discovery or innovation, that repetition can get in the way. Experience becomes a form or rigidity.


Studies have found that experience causes people to be less able to adapt and learn something new. People who have no experience are better able to come up with outside the box thinking (and do so more quickly), because they haven’t been positively reinforced to simply apply a learned pattern.

For example, when experienced accountants were asked in a study to use a new tax law for deductions that replaced a previous one, they did worse than novices. University students studying to be consultants who were at the stop of their class did poorly in the real world. This is because at university the problems they had to solve were well defined and they got quick feedback as to whether they were right or wrong. But in the real world, things were messier and so the patterns they had developed at university worked against them.

The different strengths between humans and robots


Seeing as technology is becoming more and more prominent in every aspect of life, it’s worth considering how this will affect us.


Robots and humans seem to have opposite strengths. You can program rules of chess and complex strategies into a robot very quickly. It can then calculate ungodly amounts of possibilities within the clear cut rules of chess, and make the best move from all those possibilities.


However, robots aren’t so good at seeing the bigger picture and adapting to new things. While as humans, it takes us a long time to learn all the patterns and rules a robot can download almost instantaneously, but we need little training to think broadly and adapt. In fact, as shown above, less training can actually be helpful for fresh ideas.


When humans work with technology, all those years of repetition and refined practice of people who are highly specialised can be neutralised seeing as any robot can calculate such things a million times for effectively. This means there is likely to be more and more value for someone who can see the big picture and adapt rather than someone who is highly specialised. Said differently, the more we get in touch with what makes us human, the more effective we’ll be.


This has been put to the test in chess championships where people work in teams with computers. In this scenario, the computers take care of the small tactical details while the humans look at the overall strategy. The winning teams of these championships tend not to be made of grandmaster chess players (in fact, they are often beaten by amateurs because robots can instantly do what took these grandmasters decades to learn). The winners of these competitions tend to be those that are good at coaching others, who have a diverse range of skills, who can see where calculations need to be made and what tactics need to be analysed by the computer so that they can make the best decision with all that information.


In other words, they’re people who can use other resources well, people who can ask the right questions. They’re not people who have all the answers. This is where curiosity trumps knowledge. This is not universally applicable. In the real world we still need people who are highly specialised. It’s just that specialisation and early starts have been overvalued while breadth has been discouraged.


The more “big picture” something becomes, the more layers of thinking, the more diverse aspects there are to integrate, the better humans are equipped for the task when compared to robots or AI (at least for now). Even when computers did win individual battles in the games, humans won the war as they adapted and learnt.

Thinking outside the box


The most impactful innovations tend to come when we think outside the box.


When we look at the top scientists, the Nobel prize winners, the ones who contributed the most to their field, we find that they are far more likely to have interest and hobbies outside of their area of expertise. Whether it’s creative writing, sculpting, acting, tinkering with electronics or any other side hobby. That breadth of interest is beneficial, it’s not a waste of time or energy.


Steve Jobs used the knowledge from a typeface class at university to inspire key elements on the mac. Claude Shannon took philosophy classes and learned about a concept that spawned the digital age by using the binary 0-1 to encode and transmit information digitally.

Said differently, if Shannon hadn’t taken that philosophy class, we probably wouldn’t have the technology we have today.


A degree in philosophy or spending time writing poems is not a waste of time, as many people often say. Just because “you can’t get a stable job writing poems”, doesn’t mean you shouldn’t follow that interest if it calls to you. It may be the very thing that allows you to think outside the box.


We’re humans, not robots. Life has complexity, it’s not a tennis game. Trying new things, doing “pointless” things, being able to draw from different disciplines while others repeat redundant patterns hoping they’ll have a breakthrough is what will make you better, not make you lag behind. It’s about opening up rather than getting more narrowly focused. It’s relaxing rather than getting more amped up. It’s breaking free from redundant patterns and becoming conscious.

Resources/references


Range: why generalists triumph in a specialised world by David Epstein

Photo by Helena Lopes on Unsplash

0 comments