To Thrive in Change, Reinvent Yourself

Meet Pete. At school, Pete was a star rugby player. He was scouted and joined the training programme for the Under 19s at the national academy. For the last seven years, he has played professional rugby. Now, because of an injury, his career as a professional rugby player is coming to an end. Pete is financially comfortable for now but he is only 29 and has a family. What options does Pete have to ensure that he and his family live comfortably for the rest of his life?

Explore the Adjacent

Leveraging the experience he has gained as a professional rugby player, Pete can look at work opportunities that are, so to speak, adjacent to where he is. These would include becoming a coach, or a commentator, or a journalist, or a rugby video analyst for a TV channel.

Leapfrog

Alternately, Pete could consider leveraging the core dispositions he has acquired playing professional rugby – team player who is good at empathetic collaboration, good leadership skills, quick decision making, determination, resilience, grit, stamina to put in hard work and ability to remain calm under pressure. Having the mindset of a sports person – who knows he has to play to win but if he loses he should accept defeat gracefully and strive to do better next time – will give him the gumption to venture into unchartered waters ever ready to bounce back even if he faces failure.

Of course, in the new pursuit, he will have to learn new skills and acquire knowledge in new domains. Say Pete applies to a hotel for a middle-management job. His people skills, ability to inspire juniors, ability to remain calm under pressure and ability put in tonnes of hard work will be big positives. However, Pete will also have to make sure he becomes a self-motivated learner who can learn at an accelerated pace about his new responsibilities, which could be related to marketing, catering, HR, customer relations, event management, or other functions required for the smooth running of a hotel.

Learning Missions and Personal Learning Networks

To climb the career ladder in the hotel towards more general management roles, Pete will have to gain experience in different functions in the hotel. For this, not having the luxury of taking long sabbaticals, he will have to acquire the ability to learn on the job, fast.

It will help if Pete sets Learning Missions for himself, to quickly gain expertise in any field or area. The first requirement of a Learning Mission is understanding what are the key concepts that need to be learnt in order to gain mastery of a particular domain and then setting clear learning goals to learn these fundamental concepts (and more) in a given time frame. Learning Missions also include formulating questions that lead to deeper comprehension and creating Personal Learning Networks of resource people, both online and offline, who can answer these questions and give expert guidance.

As Pete becomes better at learning new things fast, he will realise that being a self-directed learner means answering three questions:

-        What is worth learning? (related to desired outcomes in the given context)

-        How will I learn this? (using online and offline learning resources and building Personal Learning Networks)

-        How will I know I have learnt this well? (creating performances of understanding to check level of knowledge in the new domain, which could be real-world application of knowledge in Pete’s case)

As Pete climbs the corporate ladder that requires going on more and more Learning Missions, he will become a better learner, who is self-directed, intrinsically motivated and learns-to-learn at an accelerated pace

Reinventing Yourself

Much like Pete, with technology and other disruptors constantly changing the economic landscape, and in such a scenario looking for promotions, job hopping, becoming a freelancer in the gig economy, or becoming an entrepreneur, you too need to learn to constantly reinvent yourself in order to thrive. Such reinvention of self requires work at two levels:

Intrinsic

On the one hand, reinvention includes working on your mindset, dispositions and changing the way you think, and on the other, it implies acquiring new knowledge, skills and competencies. Ability to accelerate the rate at which you learn, unlearn and relearn dispositions, skills and knowledge are the key factors, for which you need to first set for yourself Learning Missions and then pursue them with military-like focus and zeal.

External

Besides working on yourself, successful reinvention also includes the ability to create a meaningful network that helps open doors (not collecting a stack of name cards but establishing meaningful relationships) and finding the right mentors who can give you judicious guidance.

Some would argue that luck, chance and fate also play a role in your success. Even if that be the case, the point is that you have no control over these factors. You can only address that which is in your control. So keep working on your dispositions, keep acquiring new knowledge, skills and competencies, keep reinventing yourself and there is a high probability you will flourish even in fast changing times.

Remote Mentoring for Students of SDSN School, Dariyapur village, Raebarely

The Amazing History of the Universe - in Hindi

Arvind, a software engineer by profession and a lifelong physics enthusiast, and I have collaborated under the ‘Timeless Lifeskills’ banner, to produce a video series in Hindi titled, “Brahmand Ka Adbhut Itihaas”. Over 13 episodes we narrate the history of the universe from its creation to the expansion of intelligent life on planet earth. 

There are plenty of resources available online in English on ‘Big History’, a term generally used for the 13.8 billion years scientific history of the universe, but similar resources are woefully lacking in Hindi (and in other languages). Filling this gap was our primary motivation in creating this series.

While these videos are only a beginner’s introduction to the important events that shaped our universe and our planet, we hope that they will inspire our young audience to take that next step and dwell a little deeper into this fascinating story. We start this 13-episode journey with an introduction to the series: https://youtu.be/cjekAfX-THA  

The formal subjects one studies at school are often organised into neat packages that don’t seem to have much to do with each other. This story touches on a variety of disciplines like cosmology, physics, chemistry, biology, geology, anthropology and more, and we hope that by the end of this series our audience would’ve learned that these syllabus and exam-driven boundaries are superficial, and there is an amazing continuity in the human scientific endeavour. Moreover, the ability to connect the dots between different disciplines, to find an innovative solution to a complex problem, is a Timeless Lifeskill!

Over the last 4-5 years that I have been conducting workshops in rural/remote schools, I have observed that the lack of good quality learning resources in Hindi and regional languages puts the students at a disadvantage. This video series is a small step towards bridging this content divide. So please help spread the word about availability of this video series and let anyone in your circle, whom you think will directly or indirectly benefit (students, teachers, parents, school/college principals…), know about the availability of this learning resource by sharing this post, sending the YouTube link as an email or as a Whats App message, tweet about it, subscribe to our YouTube channel, or in any other creative way!

The RGB Life Skills

What makes a student future-ready: O-level or GCSE? IB Diploma or A-Level? Academies, Grammar schools, or Faith schools? These issues seem to be the focus of debate about education today.

However, instead of focusing on ‘how’ should education be imparted, isn’t it a lot more important to first  ponder ‘what’ education should be imparted, given the fast changing contours of the 21^st century, when mechanisation, automation, and now robots and AI are changing the very fabric of employment and entrepreneurship? Isn’t it worth wondering if, like the primary colours Red, Green and Blue, which can be mixed to create millions of colours, are there some core skills and competencies, that when learnt, will prepare students to shine, whatever be the shape of things to come?

The 19^th and 20^th century paradigm of stockpiling knowledge, usually in the form of a University degree, that almost guaranteed lifelong employment is no longer viable, and while the focus of formal education is on ‘vertical skills’ like math, science, history, or marketing and finance, people who excel in different fields have an additional set of ‘horizontal skills’ which are often described as 21^st century skills. For example, UNESCO’s report ‘Learning the Treasure Within - Education for the Twenty-first Century’ describes the four pillars of education as – Learning to Know, Learning to Do, Learning to Live Together, and Learning to Be.

Researching, creating online learning content in multiple formats and conducting regular workshops in remote, rural schools in India to impart life skills to make students future-ready has given me the unique opportunity of interacting with many hues of learners and closely observing challenges of education in a multitude of situations, from metropolitan London to hinterland India. Based on the insights gained I think the RGB life skills are:

Yearning to Learn: how to fire up the learner within, remaining curious, taking ownership of own learning, and being able to answer four questions for yourself: What is worth learning? How will you learn it? How will you know you have learnt it well? How will you become better at learning new things?

Learning to Think: deep and independent thinking, critical, creative and computational thinking, being able to formulate insightful questions, pattern recognition, understanding complexity, ability to solve unstructured problems, ability to innovate and judicious decision making.

Learning to Be: understanding the construct of your emotions, ability to rewrite the script that plays inside your head and determines how you interpret and react to life situations, setting goals that go beyond self-interest, deep self-awareness and living a joyful life.

Once you have awareness and clarity about the RGB life skills, you can chart the ‘how’ of the learning journey for yourself, or for your loved ones, not relying just on formal education but also making the most of the tonnes of informal learning experiences now available, many of them online for free.

Get ThinKING!

In the late 18th century, steam led to the First Industrial Revolution; in early 20th Century, electricity led to the Second Industrial Revolution; in late 20th century, ICT led to the Third Industrial Revolution; and now, Blockchain, Big Data, Robots, Drones, Machine Intelligence, Nanotech, Biotech and other technologies are ushering in another new era. If one ingredient, steam, electricity or ICT, so completely changed the global landscape, just imagine the upheaval that could be caused by the combined onslaught of all these emerging technologies.

Widening hiatus between the rich and the poor, massive displacement in the job market, and super opportunities for those who are future-ready, it's all on the cards. As the global contours shift massively, will you become a mere cog, or will you thrive? It will depend on how you think.

The importance of critical thinking – ability to make rational and reasoned judgments, and creative thinking – ability to create something novel that is useful, is already well established. However, to flourish in the world that is now fast emerging, you need to add more dimensions to your thinking ability. These include,

Abstract Thinking: correctly formulating the problem after looking at the big picture and asking insightful questions that lead to pattern recognition and generalisation. This is very different from solving an MBA Case Study where a pre-formulated problem is presented!

Computational Thinking: algorithmically solving problems of scale. This starts with pattern recognition and abstraction so that the problem can be represented in new ways, then breaking the problem into smaller parts, and finally, recasting the problem to solve it in steps (i.e. algorithmically).

Ability to Innovate to Solve Unstructured Problems: the economic, social, political and other issues we face today are not complicated. They are complex! A complicated problem is difficult to solve but it has a unique solution, like a 1000-piece jigsaw puzzle. A complex problem is not only difficult to solve, its solutions are fluid and need constant updating, like forecasting the weather. The challenges we face today – clean energy, poverty, terrorism, climate change, water crisis, financial crisis, health and well-being… are all very complex. Amazing value-creation opportunities lie ahead for people who are keen to tackle ‘wicked’ problems – problems that are difficult to solve because of incomplete, contradictory and changing requirements.

Evolving the way you think is the only way to navigate and shine in a future that is VUCA – Volatile, Uncertain, Complex, and Ambiguous. You need to shape your thinking such that you connect the unconnected dots, and connect the already connected differently. To do this, you need to not only ask why, what and how but also why not, what if and how else.

Full STEAM Ahead!

At the recently concluded Brexit referendum in the UK, it is estimated that only 36 percent of people aged 18-24 voted, when the decision to leave or remain in the EU impacts the youth most. Young people who did vote, did so overwhelmingly for ‘Remain’ while the overall outcome was in favour of ‘Leave’ begging the question if the voting age should have been lowered to 16, as was the case in the 2014 Scottish referendum. This is anecdotal but on BBC news I heard some young people say that they didn't think through their choice as they figured how could their one vote matter!

Low voter turnout of 50% - 60% has become the norm in most national elections today and voter apathy is especially high amongst the youth. But democracy works only when its citizens vote, and vote with some clarity of consequences of their choice. So how to get more people to cast their vote, sensibly?

One option for a democracy is to adopt a law akin to the Australian law that makes it mandatory for eligible citizens to register and vote in all elections, by-elections, and referendums. If they fail to do so they have to pay a fine and if they fail to pay the fine they can be convicted and jailed. Does this work? Well, in the 2013 Federal Elections in Australia the voter turnout was over 93%

But compulsory voting does not necessarily mean voting with awareness of consequences of choice. Another option that addresses the issue of voting with awareness is educating citizens of a democracy on why and how they should practice their franchise. And, this brings me to STEM and STEAM.

Over the last decade, STEM has become a popular acronym in the educational rhetoric. It stands for the study of Science, Technology, Engineering, and Maths and is often quoted as a panacea, a ‘tabeez’ that will magically solve the problem of unemployability in the age of intelligent machines. But now a new term is slowly coming into fashion – STEAM, which is STEM, with an ‘A’ added for Arts and its advocates want Art & Design to be the centrepiece of STEM education in order to add the element of innovation to STEM.

I personally think that the ‘A’ in STEAM education should stand for a very inclusive definition of Arts – study of Liberal Arts that include languages, music, aesthetics, philosophy, psychology, history, and humanities. You could argue that with such a broad definition of Arts in a STEAM curriculum what is left? Nothing!

And, that is my point. Education means preparing a student for life, not a subset of life.

The Latin phrase for Liberal Arts is ‘artes liberales’ and ‘liberales’ means, ‘worthy of a free person’. In classical antiquity, Liberal Arts meant subjects and skills essential to ‘know’ so that a free person could take an active part in civic life. Today Economics and its still more limited dimension 'learn to earn' has hijacked the education agenda. Imagine the future of STEM only education – students grow up to be highly employable but incapable of sensibly taking part in the civic life of a democracy, and worse, incapable of deep self-awareness hence raising the probability of leading a stressed and unhappy life.

Referendums also point to another possibility – a move away from Representative Democracy to Direct Democracy. Representative Democracy, when an election is held once every 4 or 5 years and people choose their representative to the Parliament who in turn make policies, is a sensible choice when holding elections is an expensive proposition. But taking a cue from the hunt for talent competitions on television, where people vote using their mobile phones, it is not hard to imagine a future where all important legislation is decided by referendums, with voters casting their vote using a mobile phone – Direct Democracy.

If you think Direct Democracy is a dangerous idea just consider the, not very hard to guess, reason for voter apathy – voters don't find a leader worthy of representing them. Like right now in London people over at The Globe Theatre are crying foul. All the Shakespearean drama has shifted to Westminster. And, we the people are wondering what Mr. Gove, Mr. Johnson, Mr. Corbyn and many others in politics are doing in Westminster. They should be in the West End. Given a choice between leaders who are driven by personal ambition or dogmatic beliefs, or a Parliament that is more often than not disrupted, as in India, and Direct Democracy, I would vote for the latter.

The increasing use of referendums, lowering of voting age, voter education and sensitisation, these factors alone make a case for adding Liberal Arts education to a STEM curriculum. Add to that the role education in the Liberal Arts plays to foster the basic human spirit – to learn and to know (including Know Thyself), I think there is a strong case for taking education full STEAM ahead.

‘Flip’ Your Job with AI

Search Engine Optimiser was not in the job lexicon a decade ago and a decade hence, probably earlier, Blockchain Validator might become a sought after job. Artificial Intelligence (AI), or computers that can learn themselves are changing the complexion of employment by becoming capable of doing tasks that could earlier be done only by a human, for example, driving a car in traffic. 

AI is disrupting jobs all across the skills ladder. According to a McKinsey study, this is happening because, be it a low skill or a high skill job, if you deconstruct the tasks needed to be done for the successful performance of a job, you will find that in almost every job there is a component that can be done better by AI. In such a scenario people who have the skills that complement AI will thrive. Think of a good surgeon who can become great by using AI-based Augmented Reality glasses that overlay useful information while the surgeon is performing surgery.

I think the Flipped Classroom model, where teachers curate online learning resources for delivering the didactic part of teaching and use precious classroom time on learning activities like discussions and debates that ensure students have a deeper understanding of the topic of study, can also be applied to the use of AI in jobs. Ability to use AI to ‘flip’ a job will distinguish a good professional from a great professional. For example, doctors could use IBM’s Watson AI machine for better and faster diagnostics and use the time they save in solving more complex cases.

You may not realise it but AI is already very much a part of your life. It lives in your email spam filters, it is present in your smartphones, it drives Apple’s Siri, Amazon’s recommendation system and soon it will impact many more areas. Many tasks being performed by humans today will be better done by AI machines and in the coming decades, this will change the nature of employment. Just like you may not know how your smartphone works but you know how to make the most of it since AI is becoming an integral part of your life, it is better you understand it and know how to complement it with your skills instead of competing against it.

AI is a computer that can learn by itself. It does so by using Machine Learning, which is different from traditional rule-based programming and uses computers' ability to analyse the big amount of data and decipher patterns from it.

Pedro Domingos, the author of the book The Master Algorithm, explains that traditional programming involved inputting data and an algorithm (an algorithm is a detailed sequence of steps or operations that tell the computer what to do with the data), the computer then processes the data based on the algorithm and outputs the result. In Machine Learning, the data is input along with the output and the computer generates the algorithm.

For example, we may input thousands of x-ray images of lungs and tell the computer which x-ray images reveal cancer and which are normal. The computer takes both these inputs and teaches itself how to detect cancer. If it makes a mistake in its diagnosis this data is again fed back and the iterative process helps the computer enhance its cancer detection algorithm. Computers taking data and figuring out the algorithm themselves is called Machine Learning. 

Domingos explains that there are different approaches to Machine Learning. Some computer scientists take inspiration from first order logic to derive the AI algorithm. In this method the data that is input are specific facts and the computer works out the general principle. This approach, for example, is used in drug discovery like finding a new drug for malaria. Another group of computer scientists takes inspiration from the way the brain and the neurons work and create Neural Networks to extract rules and patterns from a set of data. This AI approach, also called Deep Learning, for example, is used by Facebook’s Deep Face facial recognition system, which identifies human faces in digital images. It has a nine-layered neural network and used four million images uploaded by Facebook users to train itself.

In another AI approach, uncertainty decides the probability of different possible outcomes and based on actual outcomes this probability is updated and iteratively the system performance improves. This AI approach is used, for example, in Google’s self-driving cars, and in email spam filtering. Another AI approach takes inspiration from ‘reasoning by analogy’ and uses what is called the ‘nearest neighbour algorithm’. Recommendation Systems (‘if you liked this song you may also like…’) and Collaborative Filtering uses this approach.

We can distinguish between two types of AI.

Weak or Narrow AI: is AI that is good at doing only one task. In 1997, IBM’s Deep Blue computer beat the world chess champion, Gary Kasparov. In 2011, IBM’s Watson computer beat the human champions of the American television game show, Jeopardy. Earlier this year Google’s AlphaGo AI machine beat the world champion of Go, a really complex strategy board game. These and other areas like spam filtering and recommendations systems are all examples of Weak AI and can do only one task. IBM’s Deep Blue computer was very good at learning and improving its chess playing technique but it was not much good at anything else, not even playing another type of game.

Strong AI or Artificial General Intelligence: is, as yet, a hypothetical machine that can think, learn and perform any intellectual task that a human being can perform. Strong AI can improve its performance by itself using what is called ‘recursive self-improvement’. Natural Language Processing and Computer Vision are examples of strong AI.

Some computer scientists believe that sometime in the future, not certain when, there will be a moment of ‘singularity’ when AI will exceed human intelligence. We could also come to a point where AI machines will create even more intelligent machines themselves – what is described as Artificial Super Intelligence. Although when this will happen is not certain, many prominent people like Bill Gates, Elon Musk and Stephen Hawking are of the view that we need to put safeguards in place because the ‘maker’ (us humans) will no longer be in charge of such machines. Swedish philosopher, Nick Bostrom, believes that Artificial Super Intelligence poses ‘existential risk’ meaning such machines pose the danger of annihilating humans.

Whether in the long run Strong AI poses an existential threat or not, what is certain is that in the shorter term Weak AI itself is disrupting our socio-economic future. Some experts argue that AI will lead to mass unemployment (leading to massive social unrest) while other experts are of the opinion that adoption of AI will lead to the emergence of new jobs, like repairing robots.

We don't know which of this prognosis will come true but one thing is certain – the skills, competencies and dispositions needed to flourish in the age of intelligent machines will be very different. Creativity, ideation, large-frame pattern recognition, ability to solve unstructured problems, fine dexterity, and complex communication, along with the ability to complement these skills with the use of AI, such that the human-machine alchemy allows you to do tasks that were not possible earlier, will greatly enhance your employability and entrepreneurship potential.