I often think about what skills people need to succeed in their careers. And this generally leads me to inquire whether educational institutions teach their charges the right skillsets in order to prepare them for an increasingly uncertain world. By and large, I think most fail on this count.
The average grade school or university is business as usual today: teach specified curricula the way they’ve always been taught (barring major discoveries in or additions to the field), usually in preparation for an exam at the end of the term. I believe this way of educating young people is becoming rapidly outdated.
We have infinite access to content at our fingertips, and the machines that we use to that end have better memory and faster processing than our brains. This is not to say that we should give up on education altogether; instead, my argument is that we must train people to think in ways that machines cannot.
Today, and hopefully for a while longer, humans are uniquely capable of achieving both breadth and depth in their learnings. Narrow AI is able to process massive amounts of data to develop specific expertise; for example, the AlphaGo AI trounced the best human Go player in the world earlier this year. Thus, telling people that they should aim for specific expertise strikes me as problematic. While we believe that knowledge work is currently safe from the advance of AI, a Japanese insurance firm actually laid off claims workers because an AI could do their work better, faster, and cheaper.
Therefore, we need to teach people to become expert-generalists. Orit Gadiesh, chairman of Bain & Co, who coined the term, describes the expert-generalist as:
“Someone who has the ability and curiosity to master and collect expertise in many different disciplines, industries, skills, capabilities, countries, and topics., etc. He or she can then, without necessarily even realizing it, but often by design: (1) Draw on that palette of diverse knowledge to recognize patterns and connect the dots across multiple areas and (2) drill deep to focus and perfect the thinking.”
Sounds like a good deal in exchange for breaking with academic tradition, but Gadiesh’s words portray expert-generalism as something of an innate trait. I instead think that it can be inculcated through a specific curriculum. The question is how to teach it.
The presentation embedded above (link here) explains my views on how we can teach expert-generalism. The renowned VC Marc Andreessen explains that one must be in the top 25% for a few skills in order to become world class.
I believe people need at least 3 skills, and that value lies at the intersection of those 3. For example, Elon Musk combines programming, reading, and existential philosophy. Warren Buffett combines value investing, consumer psychology, and humanities. Marissa Mayer combines computer science, management, and linguistics.
By generalizing the above cases, we can see a framework for expert-generalism emerging. One must combine a hard skill, a soft skill, and a perspective to become an expert-generalist. By merging different skill-sets in this way, one becomes much tougher to replace, because machines can only currently master one skill at a time. In my view, schools should re-orient their curricula around this model in order to create a new class of educated people who can outlast and even grow from the inevitable automation that is coming to the workplace.