Creative problem-solving, innovation, systems thinking and emotional agility are the requirements for the future, and our education system should be geared for this.
It was as a classroom game inspired by Ikigai and some psychometric tests. We wrote the abilities, talents, skills, and interests of each student on different sticky notes and asked them to visualise their future educational paths. But the exercise did not result in any clear paths; instead, it opened up uncharted roads with different skill trees and revealed new specialisations for which courses do not exist. It led to an array of looped domains for which mono-specialisations are insufficient. It spurred unexpected disciplinary connections for which our curriculum is unprepared — a realisation that our education cannot afford to remain limited to narrow specialisations.
The game evokes the old debate between specialists who have expertise in a limited area versus generalists who have divergent skills in varying areas. Mainstream society generally favours specialists over generalists, partly due to the perceived expertise and educational credentials. But the actual question is whether we have the learning choices to experiment across domains. This stems from the new debate on the skill sets that can help us navigate an uncertain future.
According to Vikram Mansharamani of Harvard University, it is not a specific skill but the sort of thinking that connects multiple domains that will get us ahead in the future. Authors like David Epstein argue for learning by doing a variety of things to develop an intellectual range — a deep generalist, a term attributed to scholar Warren Bennis and popularised by corporate leader Aytekin Tank.
Scientists like Kepler, Maxwell and Newton were polymaths. Innovators and artists always combined knowledge areas; the most significant feature of a deep generalist. Leonardo da Vinci was adept in art and engineering. Steve Jobs blended design and technology. The idea is not to discard specialisation; on the contrary, it is to blend knowledge units from different domains to make a cross-disciplinary thinker.
Tools for diversified learning
How can we develop expertise in multiple areas within a limited time? Visual artist Jake Chapman demonstrated one way. He laddered the level of expertise into five stages — layman, beginner, apprentice, journeyman and master. Let us apply the Pareto principle (which states that, for many outcomes, roughly 80% of the consequences come from 20% of the causes) and assume that mastery takes 20 years of practice. In that case, reaching journeyman status will take only 48 months and 10 months to reach the apprentice level. If we structure our learning around this approach, a learner can move across two or three domains with cross-learning possibilities in limited time.
As a beginning, if we permit youngsters to play with diverse domains, interests and passions, it will allow them to move across knowledge territories. Liberal arts education has long realised this. So, physics and philosophy go simultaneously in many institutions. From Oxford to IIMs, engaging with the Humanities finds an entry in the business curriculum.
The secret is in the learning habit, triggered by solution orientation and not grades. Learning a new language or art form, or community involvement can ignite the learning gene in novel ways. It helps to zoom-in and zoom-out of the context, on-demand.
Another tool is signal spotting. Signals are seeds of future events, discoveries and news items. A signal seeker has an interdisciplinary mind. A daily thought exercise to link unrelated developments and predict their impact in a variety of domains is yet another useful way. This will make us a theme-based or problem-centred learner. Tinkering with options and combinations is no more limited to designers.
In an age of open courses, web resources, learning communities and social networks, it is not hard to create deep generalists, even within the constraints of current syllabi. Once a broad foundation is developed, ancillary skills can be added by choice. This opens up novel forms of skill-trees and efficiency-paths
Automation continues to wipe out many jobs, and algorithms are taking over routine decision-making. This allows us to engage more with creative problem-solving, innovation, systems thinking and emotional agility. We need deep-thinking humans in addition to deep-learning AI, observes author Scott Hartley, whose extensive work shows that liberal arts and technical literacy complement each other. These are much needed to solve the problems plaguing the world, from climate change to terrorism and resource depletion to unemployment.
If students focus on specialisations with the sole objective of getting placed, they will most likely be unemployed soon after. Let us prepare them for anything they can fix their minds and hands to — as deep generalists.