I think perhaps one of my favorite quotes of all time is by the science fiction writer Robert Heinlein, he writes:
“A human being should be able to change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take orders, give orders, cooperate, act alone, solve equations, analyze a new problem, pitch manure, program a computer, cook a tasty meal, fight efficiently, die gallantly. Specialization is for insects.”
-Robert A. Heinlein
My takeaway from this quote is that human beings are creatures of immense complexity and adaptability. Each of us possesses the ability to observe, learn, and interact with our environment and each other in countless different ways.
However over the course of recent history, our advances in technology, our relatively easy access to cheap calorie-dense foods, and our capitalistic economy. These have all made it increasingly possible to focus our individual time and energy on the pursuit of more specialized endeavors. More importantly, this societal luxury has spawned countless advances in science and medicine, led to a global increase in quality of life, and has given us great works of art.
As technology has become more and more advanced and has revealed exponentially more paths to explore, it has naturally driven us further into specialization. 200 years ago you had doctors, and maybe a few of them specialized more heavily in one aspect of medicine or another, but compared to today’s myriad of specialized fields of medicine, you basically just had doctors.
The same goes for countless other fields. In the early days of the computer revolution, there were only a handful of programming languages. A computer programmer then was just a computer programmer. Today we have hundreds of different programming languages. We have full stack, back end, and front end developers, and those are typically just within one or 2 languages.
To put it another way, it was not so long ago that it would have been laughable for the average man or woman not to know how to unclog their own toilet, fix their own sink, or cook their own meals. In today’s society, an individual can function perfectly well without knowing how to do any of those things. Yet that same individual might have spent their entire career studying one gene on one genome that unlocks a cure for cancer.
So what happens to the people who don’t specialize in today’s world? What happens to those individuals who do gravitate towards the polymath model? Whose interests are broad-ranging, whose experiences are often varied and disparate? Do they have a place? Or is it career suicide to not specialize early and often?
In his book Range, David Epstein lays out a compelling and well-researched argument for how Generalists are better suited to today’s world than those who hyper-specialize. One of the issues Epstein writes is:
“The challenge we all face is how to maintain the benefits of breadth, diverse experience, interdisciplinary thinking, and delayed concentration in a world that increasingly incentivizes, even demands, hyper-specialization”
However, Epstein published this book before functional AI tools became broadly available to the general public. While, as a Generalist myself, I am in full if not slightly biased agreement with Epstein on the advantages of a breadth of knowledge and experience. I now think that the challenges facing them will be increasingly mitigated in a world where we have tools that will specialize for us.
Will the advent of widely available AI tools help specialists? Of course, it will. However, I think the group that will benefit the most is the generalists. With tools that can code entire applications with just a few prompts, generate compelling marketing material, and parse huge amounts of data in seconds. Individuals with a wider breadth of experiences and more diverse perspectives will no longer be as reliant on specialists to build their solutions for them.
It is well documented that a wider base of knowledge, experience, and perspective leads to an overall increase in one’s ability to solve complex and novel problems. The issue prior was that those individuals who had spent the time gaining those experiences often did so at the expense of not learning specific skills that would help them implement the solutions. With the help of AI, problem solvers can now also create the solutions they devise.
The irony here is it took hyper-specialization in order to create the tools that are now going to allow us to diversify our pursuits. However, I do not want to be misunderstood. I am not advocating for everyone to stop specializing, nor do I think that those who continue to specialize will no longer have a place in the world. We still need specialists, and we will always continue to need them.
The argument I am trying to make is that as we assess talent and consider who might be best positioned to fill roles within our companies. Particularly those roles with more ambiguous functions, or ones that require a higher degree of adaptability. Try to pay less attention to what titles or specific tasks they have performed in the past, or what specific tools they have used. Instead, give more weight to their collective breadth and range of experiences.
In short, if you want to hire people who will improve your team’s overall ability to solve problems, hire the people with the least amount of similarities to those that you already have. Instead of asking who can I find that already knows how to do what I need done? Instead ask yourself who can I find that will look at my problem in a way someone who has spent too long looking at that problem can’t?
