How to thrive and survive when our educations systems are screwed
Current industrial-age classroom teaching methods and systems adopted by many developed and developing countries have not yielded the positive outcomes that they were hoping for. After spending millions of dollars, countries like the US and Australia are still asking the question, “What went wrong?”
It is easier to kill the messenger than to fix the root cause of the problem. Many experts give reasons (or excuses) as to why there were no improvements in student performance despite massive amounts of investment money – testing was not ‘right’, or our students did not take these tests seriously, to name the few.
Students are incurring a significant amount of study debts at alarming rates as education cost increases. They are also in debt much longer even until retirement. Rising debt levels are impacting debtors’ ability to live normally, buy a house and even start a family.
The key problem
Technology is significantly impacting the way we acquire and search for information. It will continue to disrupt the way we think about acquiring and using knowledge.
Humans acquire knowledge in a linear progression over time, whereas technology generates data exponentially.
Moore’s Law refers to Moore’s perception that the number of transistors on a microchip doubles every two years, though the cost of computers is halved. The law states that we can expect the speed and capability of our computers to increase every couple of years where this growth is exponential.
Buckminster Fuller, the architect who invented the geodesic dome, later became a futurist and systems theorist. In his book Critical Path, he came up with the “knowledge doubling curve.” He estimated that if you could measure the cumulative knowledge of human civilization, from the year of Jesus birth, it took 1,500 years for it to double. But from there, it doubled again by 1750. From there, it doubled every hundred years, up until WW2. After the way, it doubled in 25 years. By the 80’s, it was every 12 months. Some current estimates put the number at every twelve hours.
So, if you’re born today, it’s doubled twice before dinner.
Advances in technology have, therefore, given us the ability to generate or collect vast amounts of data and information exponentially.
Unfortunately, humans will not have the capability and capacity to store all this new information for future use. More so on a just-in-case basis or just for knowledge’s sake.
When all the worlds’ information is instantaneously at your fingertips, why try and remember everything we need to know? Why not treat the Internet as an extension of our memory?
We have already passed the point of no return – knowing how to search for the relevant information (know-how) is now more important than knowing what it is (know-what). There’s too much information to take in and remember.
Based on Moore’s Law, the gap between knowing what and knowing how will exponentially increase due to advances in technology.
A different education and learning approach is, therefore, urgently needed to cost-effectively equip our future generations with employable and future-ready skills and experience.
The differences between the past and the future are summarised in the table below.
| Previously | Future (and now) |
| Industrial-based (post-world wars) | Information/knowledge-based |
| Manual; physical; lower-level work | Machine-base; intellectual; higher-level work |
| Teacher driven; one-size-fits-all mass learning in classrooms; faculty focus; specific times and place | Self-driven; customised learning as individuals; learner-centric; on-demand / instantaneous – anytime and everywhere |
| Information intake – What other knowledge should I acquire? | Information embodiment – What will I now do with what I have learned? |
| Just-for-knowledge learning | Just-for-work learning (employability, securing a job); just-for-you learning; just-in-time learning (on the job learning) |
| Content-driven; accumulation of just-in-case knowledge that may not be used; rote learning | Context-driven; hands-on application of just-in-time information, skills, or tools; experiential or experimental learning |
| Focus on hard, technical skills and competencies | Focus on soft, social skills and competencies |
| One-off exams and test of accumulated knowledge | Continuous verification of how information is applied in a different context |
| For the privileged few | Commoditised and universal for everyone |
| Becoming costly; increasing student debt | Affordable and sustainable; enhance well-being and self-management |
Technology is the key driver of change
Technology has significantly increased the collection and availability of data and information. It has exponentially improved and advanced the way data and information are acquired, linked, stored, analysed, and reported.
Technology has enabled, allowed, or even forced us to move from information intake (i.e., What other knowledge should I acquire?) to information embodiment (i.e., What will I now do with what I have learned?)
Information overload
With this immense amount of available data and information, no one can gain, learn, and store these ever-increasing masses of knowledge.
What’s more, as humans age, the information storage, and recall ability will also deteriorate over time.
Market forces have dictated informational services
Many decades ago, doctors and lawyers, for example, were commanding huge salaries. They went to university, acquired their professional knowledge, and applied the knowledge that they have learned and memorised.
In return, they had the privilege of charging premium prices for their professional services. Customers were willing to pay for these services, keeping prices high, and naturally encouraging professional exclusiveness.
The lack of available information created a natural monopoly for many professions to command higher salaries and wages.
People are more educated
As more and more people are being educated through colleges and universities, these natural monopolies are being diluted with the help of technology. People are becoming more than capable to adopt a do-it-yourself (DIY) approach to researching and analysing information.
This has led to the growth of self-management, self-care, and self-determination.
Information is being codified by AI
Knowledge is constantly being increasingly codified and handled by sophisticated cognitive and automation technologies as the amount of available information and data exponentially grows.
Artificial intelligence (AI), for instance, is ever more adept at analysing data, categorising information, recognising patterns, and making decisions based on the knowledge it gained.
From journalism to medical diagnosis, from HR to audit, from logistics to manufacturing, AI and machine learning will continue to encroach on what has been a human territory.
It is challenging how we think about data and how education can support future generations.
Free information everywhere!
Information is being commoditised and is freely available.
We need to know where, when, and how to look for the appropriate information.
For those who have computers and Internet access, they will naturally jump onto the Internet (the platform) and use Google (the tool) to ask the right questions (the search term) when they need information on demand.
With over 1.72 billion websites in 2019, this number will only grow, as shown in the diagram below. With the current world population at 7.7 billion, there’s roughly one website for every five persons!
People can freely search online for any information, answers, or solutions to their problems. There is no need to pay premium prices anymore. Many people have become DIY enthusiasts as they self-manage themselves.
When demand for monopolistic information drops, so do prices. Economically, this is what we are seeing across many information-based occupations. Salary and wage stagnation have become a common occurrence.
Knowing what questions to ask
Rather than acquiring just-in-case or just-for-knowledge information, we are pivoting or have transformed into the acquisition of just-in-time information. This acquired information will be used for specific purposes, bounded by time, and its context and circumstances.
To do so, we must first understand the problem and its root causes. When we know the exact problem to be solved, finding the solution or searching for the required information becomes easier.
Based on a framed problem statement, we can then formulate the right questions to ask based on our prior experiences.
Knowing when to ask the questions
Thereafter, we need to know when to ask these questions and in what order.
Our goal is to develop an accurate and complete picture of the solution required.
Applying the appropriate search terms in the right sequence and time will be vital for us to find the right information that will solve our problems or give us the ability to make informed choices.
Asking the wrong questions and in the wrong sequence will only result in gaining the wrong answers.
Once we know the sequence and timing for asking the right questions, we must determine which platforms that contain the best available information to meet our requirements.
Knowing which platform to use
Information is available on a variety of platforms – digitally via the Internet, print, humans, etc.
We need to know which platform contains the relevant information that we are seeking. This will be vital in finding the right answers to our questions.
Knowing which tool to use on a platform
The Internet is always my go-to platform for gaining free information.
Google is my preferred search tool for that platform when conducting an Internet search. There will be a variety of tools that function similarly to Google.
The choice will come down to personal preferences and competencies.
It is also about your ability, attitude, and behaviour to use or learn the tool.
The skill gained in using one tool is transferable to other tools that may have similar functionalities. It also boils down to the specific context for using the tool.
Knowing the right kind of tools and context to use on platforms will be another key to finding the right answers.
Discernment helps us connect the dots
Work is being increasingly digitised and automated. This will result in the constant creation of new or the reshaping of old tools and platforms. When this occurs, we may not be able to make the connection between the problem and the tools and platforms, as previously experienced.
We may mistakenly frame the issue as a problem stemming from a lack of knowledge or skills instead. But this may not be the case.
Instead, what we’re seeing is not a lack of skills, but perhaps a lack of discernment. It is the ability to read the environment and make sharp judgments about how we can apply ourselves in that environment.
Being a digital native
As more people grow up with digital technology, they become comfortable around various tools and platforms.
Unfortunately, familiarity does not prevent us from using the wrong tools or platforms for the job at hand.
We tend to over-estimate our skills in unpacking the problem. This could include using the wrong tools and platforms at the wrong time to solve the problem.
Discernment is the secret ingredient for the future of work
Discernment, which is learned through experiences not taught in classrooms, is the secret ingredient for us to succeed in the future of work. It enables us to use the right tools and platforms at the right time to find solutions and solve problems.
Discernment helps us frame the problem in such a way that it helps us understand the impact of using specific tools and platforms in context or situation. It helps us identify and evaluate the opportunities and limitations within the unique context and circumstances we find ourselves in.
Discernment also helps us fully understand what, when, and why different tools could be used on which platform to solve different types of problems.
Importance of contextual understanding and learning
We need to have a contextual understanding of making informed decisions. This is done by constantly exploring various issues and problems in a different context to discover when we can use specific tools and on which platforms.
It boils down to learning from experiences in applying various tools on different platforms to solve different types of problems in various contexts and occasions.
Curiosity, experimentation, and risk-taking are key elements for enabling us to learn from our experiences.
Why remember what you can Google?
When we use Google to conduct our intended search for answers to our problem, we will unconsciously draw upon our mental library of questions to ask and strategies to try that could be used to contextualise our problem-solving to make better decisions.
We are tapping into a bank of potential questions to ask based on previously learned or experienced outcomes, good or bad.
Something must be done previously to build that mental library for us to draw upon. The quality of our mental library will depend on many factors – our commitment, attitude, behaviour, etc.
We can only improve the quality of our questions, strategies, and outcomes by having a comprehensive mental library to refer to.
Importance of a well-equipped mental library
The ability to build, access, and curate our mental libraries will become more important after we have increased our knowledge, skills, and competencies to the expected level.
Skill is our ability to do something well. Competence is the application of skill in a specific context.
If we are starting from ground zero (especially for young people), then we need to start to build up our skills and competence first. This will be the role of formal education – schools, colleges, and universities.
Beyond a certain point, we must focus on building up our ability to discern and distinguish what questions to ask in reference to what we have in our mental libraries. This will be our competitive edge over machine learning and artificial intelligence.
Humans must develop and maintain our unique strategies and human competitive advantage over increasingly sophisticated technologies.
Contextual understanding is our competitive edge over machines
“Robots are taking our jobs” or “robots are coming to take over our jobs.”
These media-hyped headlines can sometimes paralyse us to think that we don’t have any competitive edge over machine-learning or the application of artificial intelligence.
The good news is that machines suck at contextual understanding.
It is reported that the software inside the Uber self-driving SUV that killed an Arizona woman was not designed to detect pedestrians outside of a crosswalk.
Machines need humans to program. But it is not possible to codify every possible situation and context – different weather, different road conditions, etc.
It is no surprise that less than 30% of people surveyed felt very safe or even somewhat safe as a pedestrian in a city with self-driving cars, as shown in the diagram below.
This is where humans have the contextual understanding that is far superior over machines. Until machines can fully contextualise their environment without human intervention or programming, we have a strong competitive edge over machines.
The ability to respond appropriately to different contexts or circumstances is dependent on the quality and completeness of our mental library, which helps us navigate from one environment to another.
The good news, therefore, is that it is difficult to codify contextual experience and learning using technology. But who knows!
The value creation equation
Putting it all together, we have a value creation equation:
| Tools and platform | + | Skills, competencies, and knowledge | + | Discernment, mental library, and contextual understanding | = | Value creation |
Skills can be further broken down into:
(1) Functional and digital skills – Expertise (or technical).
(2) Emotional and entrepreneurial skills – Social (or human).
There will be different types of skill acquisition processes that we need to embark upon to bring us to a certain level of competence.
Value can only be created when we have the appropriate or adequate level of skill, knowledge, and discernment using the appropriate tools and platforms to make informed choices or solve problems.
Thriving in the brave new world
It is much easier to teach people how to use tools like Google to search the Internet for information where we use the Internet as an extension of our memory.
The key challenge for our education systems is to teach what questions to ask, what strategies to apply, what the purpose is, and when it is appropriate to ask the questions or apply the selected strategy within a given context and circumstance.
The ability to discern our context and apply what we know is our competitive edge over machine learning.
Having more skills may not be the answer
It is common to hear this narrative – “To close the gap between what skills employers want and what skills workers have is to have more skills training” or “We need to learn more skills to prepare us for the future of work.”
The good news is that skills are transferable across jobs and contexts. Skills are more portable or transferable than we realise.
Research tells us that when a person trains or works in one job, they acquire skills for 13 other jobs. As such, we should be focusing on our skills acquisition by developing a portfolio of skills that are common to one of the seven job clusters identified in the research – ‘The Generators’ ‘The Artisans’, ‘The Coordinators’ ‘The Designers’ ‘The Technologists’, ‘The Carers’ and ‘The Informers’.
Perhaps for a young person, rather than asking, What is your ‘dream job’? it may be more useful to ask, What is your ‘dream job cluster?
The bottom line is that we need to identify whether we have a skills deficiency issue or a lack of contextual understanding and application.
We may already know how to use various tools and platforms. But we may not know specifically how to apply them when we are placed in a different or unfamiliar context and circumstance.
As technology changes or evolves existing tools and platforms, it does not mean that ‘old’ skills are no longer relevant. These skills may only need to be repositioned differently and applied in a new context. Learning when and how to apply these tools in the new context is all we need, in some instances.
Some skills are not ‘skills’
Skills can be interpreted differently over time. It is unfortunately built on shifting sands.
The reality is that many of the things we are trying to measure aren’t simply ‘skills’ when we define skills as our ability to do something well.
Some may argue that ‘creativity’ or ‘critical thinking’ are not skills that could be acquired and competently demonstrated.
Is it up-skilling or re-skilling?
We know that the half-life of a learned skill is about five years or possibly even shorter. This means that workers must constantly be re-skilling (or updating) rather than up-skilling to be continuously relevant in their workplaces.
Re-skilling occurs when rapid changes in workplaces and technology require us to constantly update our existing skillset. This keeps our skills ‘fresh’ in line with changes or advances in the subject matter.
Contrast this with up-skilling, which occurs when new technologies or business processes require us to acquire different or new sets of specialised skills on top of what we already know before we are allowed to perform the new task.
Up-skilling refers to a comprehensive initiative to convert or expand people’s capabilities and employability to fulfil unmet talent needs or moving them into new jobs and excel at them. This involves identifying the skills that will be most valuable in the future.
Minimum skills level required
Workers need to acquire or have the appropriate or minimum level of skills to competently perform their jobs.
When a person does not have the skills to perform the job competently, then that person is considered incompetent.
There is an expectation that formal education in schools or colleges should, in theory, equip young people with the right employable skills that will enable them to secure jobs upon graduation and perform in them.
What is the problem we are trying to solve?
When we say that someone “lacked the required skill” to perform their current job or get hired for a potential job vacancy, are we talking about one of the following scenarios:
(1) A worker who is incompetent due to their lack of skill to perform the job competently and effectively.
If so, then that worker should acquire the appropriate skills and to an acceptable pre-specified level. This situation may apply mainly to young people or job seekers.
(2) A worker who has outdated skills that require updating.
If so, then that worker needs to be re-skilled to get the work done.
Reskilling will become a life-long endeavour for many workers as the half-life of knowledge and skills gets even shorter.
(3) An experienced worker who needs specific skills to perform a new or different task or job competently.
If so, then that worker needs to be up-skilled with new or different skill-sets.
Upskilling will become more prominent as more new technologies are being introduced into workplaces.
(4) A worker who only needs to understand how to apply (or transfer) their existing skills and competence into a new, different, or unfamiliar context or situation.
If so, then that worker needs to pair up with an experienced colleague for a few hours to help them discover how to apply what they already know into the new context or workplace.
The worker needs to update their mental library related to their new environment that they find themselves in without the need for any new skills acquisition.
This usually occurs when workers change jobs, industry, or career. Or it could be a situation when there are new work tools, platforms, and business processes.
(5) Some skills required are technically not ‘skills’ especially when we define skills as our ability to do something well.
These four possibilities (not counting point (5) above) present different learning and development challenges for us to thrive and survive.
We must appreciate and understand the problem that we are trying to solve. Then find the root cause of the problem.
Thereafter, embark on the appropriate steps to address or mitigate the problem. “We need more skills” can be an ineffective solution when we don’t understand the problem.
A tailored approach to learning is required
Each one of us is created differently. Cater to different personalities, different learning challenges, and different contextual situations and influences (mainly from technology). Take a personalised or customised approach to skills acquisition and updates to our mental library.
Selectively target our learning and development opportunities to achieve the best and appropriate outcome (i.e., value creation).
Always enhance the quality of our mental library
It is virtually impossible to keep up with all the latest information and new skill-sets needed – mainly due to the impact of technology.
As workplaces become more digitalised, sophisticated, and complex, our mental libraries must also move in tandem and significantly improve in quality.
To thrive and survive in the future, apart from constantly re-skilling and up-skilling, we must also constantly update the bank (i.e., mental libraries) of questions we can ask and strategies we can try or apply. This will enable us to excel in different situations or when presented with a different set of problems.
It may be as simple as reading a book, watching TED talks, or interacting with other people.
Always focus on our strengths
Our well equipped mental libraries will be our competitive edge over machines. It’s our uniquely human ability to understand the context we find ourselves in. We can ask the appropriate questions to find the right solutions that are linked to well-defined problems. This allows us to apply the right strategies, tools, platforms, and processes to give us the desired outcomes.
We need to help people connect with what they already know to what seems unfamiliar. Pairing a new hire with an experienced colleague for a few hours for on-the-job training or coaching can help the new hire discover how to accomplish the same tasks with different tools and strategies.
Discernment is the key ingredient that can only be acquired through experience, experimentation, and time. It cannot be taught but caught. And it cannot be rushed.
To build, maintain, and curate healthy mental libraries, we need to constantly immerse ourselves in trial-and-error experimentation, risk-taking, and reflection.
Having positive attitudes and behaviours will help us thrive in a highly digitalised world and survive the future of work.
Learning-by-doing, experimentation, and risk-taking
Get on the front foot of technological change, disruption, and ambiguity. Immerse in new technologies, tools, platforms, and strategies.
Develop ingenuity and be creative.
Practice learning agility and experimentation.
Make mistakes and learn from them.
Take risks and never stop being curious.
Create a plan. Define the steps, training, and development necessary to get the work done.
Be in charge and be in control of your success. No one else can do this for you. Be a master of your destiny and identity.
Career advice, coaching, and mentorship can give you the focus.
Constantly update your mental library through continuous self-directed learning, development, and experimentation. Perhaps you don’t need more skills but more discernment and contextual understanding and learning.
In short, re-skilling, up-skilling, and development of mental libraries will become commonplace for anyone who wants to thrive and survive.