Virtual Augmentation: How To Remain Employable In the Age of Smart Machines

Virtual augmentation?

This is not a debate between “virtual reality” and “augmented reality,” whereas one offers a digital recreation of a real life setting and the other delivers virtual elements as an overlay to the real world. Rather, in the context of aggregating the components of the digitalized world, in order to create a seamless flow of work and productivity. Here, “virtual” is the reality and “augmentation” is the process. What I mean by this is the convergence of man and machine that ushers in a new generation of hybrid knowledge workers.

In the same way that augmented and virtual realities both leverage some of the same types of technology, and each existing to serve the user with an enhanced or enriched experience, likewise the new world of work posits new challenges and opportunities for explosive growth. However, in reality, man is somewhat threatened by the rise of the machines.

This is how James Barrat began his seminal work, Our Final Invention: Artificial Intelligence and the End of the Human Era:

On a supercomputer operating at a speed of 36.8 petaflops, or about twice the speed of a human brain, an [Artificial Intelligence] AI is improving its intelligence. It is rewriting its own program, specifically the part of it operating instructions that increases its aptitude in learning, problem solving, and decision making. At the same time, it debugs its code, finding and fixing errors, and measures its IQ against a catalogue of IQ tests. Each rewrite takes just minutes. Its intelligence grows exponentially on a steep upward curve. That’s because with each iteration it’s improving its intelligence by 3 percent. Each iteration’s improvement contains the improvement that came before.


He was writing about a project called the Busy Child, as the scientists have named the AI, whose progress showed that the artificial intelligence had surpassed the intelligence of a human! Granted, technology makes the world a better place but also brings new challenges.

We are living in truly exciting times in history that would make science fiction writers like Isaac Asimov proud. Scientists and futurists are projecting that in our lifetime, we may witness the true rise of the machines, where the robots will attack the modern office, as we know it, with nukes and machine guns heavy enough to obliterate the so-called knowledge workforce.

Errm, okay, I exaggerate a bit. But nonetheless, “The Rise of the Machines” is still a threat. If you doubt me then check out these (just a few) headlines from the last four years:

Wired (December 2012): Better Than Human: Why Robots Will — And Must — Take Our Jobs

Bloomberg Business (March 2014): Your Job Taught to Machines Puts Half U.S. Work at Risk

Business Insider (March 2014): Bill Gates: People Don’t Realize How Many Jobs Will Soon Be Replaced By Software Bots

The Telegraph (November 2014): Ten million jobs at risk from advancing technology

Mail Online (February 2015): Will robots take YOUR job? Study says machines will do 25% of US jobs that can be automated by 2025

The Atlantic (July/August 2015): A World Without Work: For centuries, experts have predicted that machines would make workers obsolete. That moment may finally be arriving. Could that be a good thing?

TIME (September 2017): Are Computers Already Smarter Than Humans?

BBC News (November 2017): Robot automation will ‘take 800 million jobs by 2030’ — report

Forbes (January 2018): Technology Has Already Taken Over 90% Of The Jobs Humans Used To Do

Phew! Artificial intelligence has arrived in the modern workplace, spawning tools that replicate human judgments that were too complicated and subtle to distill into instructions for a computer. Algorithms that “learn” from past examples relieve engineers of the need to write out every command.

Suddenly, it seems, people from all domains of life are becoming very concerned about advancing automation.

Truth be told, we should be very concerned: Unless we find as many tasks to give humans as we find to take away from them, all the social and psychological ills of joblessness will grow, from economic recession to youth unemployment to individual crises of identity.

And this is also showing up in developing economies, as well. South African billionaire Johann Rupert has warned that the country has to prepare for more civil unrest with technology advances set to cost more jobs and fuel unemployment.

“Tension between the rich and poor is set to escalate as robots and artificial intelligence fuel mass unemployment,” Bloomberg cited Rupert as saying.

This article from The Atlantic paints an even grimmer picture:

The U.S. labor force has been shaped by millennia of technological progress. Agricultural technology birthed the farming industry, the industrial revolution moved people into factories, and then globalization and automation moved them back out, giving rise to a nation of services. But throughout these reshufflings, the total number of jobs has always increased. What may be looming is something different: an era of technological unemployment, in which computer scientists and software engineers essentially invent us out of work, and the total number of jobs declines steadily and permanently.

Another more excitedly written post from Wired:

It may be hard to believe, but before the end of this century, 70 percent of today’s occupations will likewise be replaced by automation. Yes, dear reader, even you will have your job taken away by machines. In other words, robot replacement is just a matter of time. This upheaval is being led by a second wave of automation, one that is centered on artificial cognition, cheap sensors, machine learning, and distributed smarts. This deep automation will touch all jobs, from manual labor to knowledge work.

All this should compel us to ask: in a few years from now, what will you do better than a computer? Answer honestly. Keep in mind what you’re up against already: Computers that perform discovery in lawsuits better than human lawyers do, reading documents and classifying them by relevance. Trained robots that can identify and cut out cancerous tissues during surgery.

Driverless carsgiant automated production facilities that make those cars, robotic vacuum cleaners that can navigate the floor of your home, real-time language translation and even algorithms that can write news articles — is there anything that the computers can’t do, or can’t be trained to do in the future?

But let’s posit another thought here: what if we are asking the wrong questions or plainly missing a golden opportunity in the face of exponential tech breakthroughs? What if, rather than asking — What tasks currently performed by humans will soon be replaced by computers? — We ask a new one: What new feats might people achieve if they had better “thinking machines” to assist them?

This changes the game, right the very moment it is asked.

As the economy is transformed, some people will do great, and plenty of others will suffer. The winners will be those who conceive of skills and value in a fundamentally new way, different from what we’re used to.

The future of economic success rests on those who do not see machines as an enemy, but as an ally — seeing growing possibilities for employment. These are the people who will successfully reframe the growing threat of automationas a vibrant opportunity for augmentation. And this facilitates the flourishing of human work and the accomplishment of what was never possible.

Unfortunately the trap the buzz of artificial intelligences brings is to overstate the extent of machine substitution for human labour and ignore the strong complementarities that increase productivity, raise earnings, and augment demand for skilled labour.

What about the tasks that call for flexibility, judgment, or common sense? The future belongs to people who recognize the tasks that cannot be substituted by computerization and find ways to complement them. This point is as fundamental as it is overlooked.

This calls for a shift in mindsets: the romance between knowledge workers and smart machines that results in strong partnerships in creative problem solving.

So, what then, should be our strategy be to remain gainfully employable in this “race against time” world that we currently live in?

Strategy #1: Big Picture Thinking

Computers are smart, but you’re better at considering the big-picture than any computer is. Let the machines do the work that you ordinarily can surpass with increased level of education and take the opportunity to engage with higher-order concerns. Like a brand manager who can orchestrate all the activities required to positon a brand successfully or like a cancer researcher who picks up from where the math leaves off, where the machine has produced a hypothesis, and the investigation of its viability now begins.

Always step up your game by seeing an opportunity to provide a service or product offering in a new way. This takes lots of experience, insight, and the ability to understand quickly how the world is changing.

Get that MBA or PhD and constantly challenge yourself to get broader perspective on your work. Stay broadly informed and creative enough to be part of your organization’s ongoing innovation and strategy efforts.

Excellence Activators are “T-shaped experts.” Become one who is able to go really deep in your particular area of expertise, and also go really broad and have that kind of curiosity about the overall organization and how your particular piece of the cake fits into it.

Find ways to rely on machines to do your intellectual spadework, without losing knowledge of how to do it.

Strategy #2: Uncodifable Strengths

Only a few amount of the workforce can be able to “step up” exponentially and gaining a broader perspective on their field or area of expertise. But a lot of brain work is equally valuable and also cannot be codified — organized or arranged systematically. To this end, knowledge workers will have to use their mental strengths that aren’t purely rational cognition but draw on what the psychologist Howard Gardner has called our “multiple intelligences.”[1]

You might focus on the “interpersonal” and “intrapersonal” intelligences — knowing how to work well with other people and understanding your own interests, goal and strengths. The really smart comedians make people laugh at material a machine would never dream up, for instance. And I bet that they use computers in their daily work lives. But their genius has been to discover the ineffable strengths they possess and to spend as much time as possible putting them to work. Machines can perform numerous ancillary tasks that would otherwise encroach on the ability of these professionals to do what they do best.

Lawyers, accountants, architect, investment bankers, and consultants can also harness that intuitive side of their brains for the services that they render, not just artists. For instance, a brand consultant can, and should, intuit which concept will resonate with sophisticated customers. Senior lawyers are thoroughly versed in the law but are rarely their firms’ deep-dive experts on all its fine points. They devote much of their energy to winning new work (usually the chief reason they get promoted) and acting as wise counsellors to their clients. With machines now digesting legal documents and suggesting courses of action and arguments, senior lawyers will have more capacity to do the rest of their job well.

Another way of looking at this strategy is to ask: what are the activities that we humans, driven by our deepest nature, will simply insist be performed by other humans, even if computers could do them? You need to focus on your uncodifiable strengths, first discovering them and then diligently working to heighten them. In the process you should identify other masters of the tacit trade you’re pursuing and find was to work with them, whether as collaborator or apprentice.

You may have to develop a greater respect for the intelligences you have beyond IQ, which decades of schooling might well have devalued. These, too, can be deliberately honed — they are no more or less God-given than your capacity for calculus.

Strategy #3: Monitor and Modify

Computers, in my opinion, were not designed to obliterate all of humanity, but to dance with it in step a symmetrical tune that brings about innovative flourishing. In part, present-day computing may not have been developed to achieved “connected spontaneity” and achieve random bursts of brilliance because knowledge workers understand how software makes routine decisions, so that they can monitor and modify its functions and outputs.

For example, there are tax-management computer programs that help get a lot of work done. But instead of accountants getting afraid of losing their jobs, they can convert that energy into looking out for the mistakes that automated programs — and the program’s human users — often make. Still in the finance industry, a pricing expert rely heavily on computers to optimize pricing on a daily basis and should be able to intervene as necessary for special cases or experiments.

(Examples of why, when computers make decisions, we will always need people who can step in and save us from their worst tendencies).

As commerce has become increasingly digitalized, almost all functions are now automated and can be handled by computers. Ad buying in digital marketing is almost exclusively automated these days, but only people can say when some automated buy would actually hurt the brand and how the logic behind it might be tuned. So you see, it’s back to the assembly line again, where we inspect and discard products seen as factory defects.

This is the human factor: and we can thrive in this digitalized world by pursuing some STEM education and keep updating our business domain expertise.

[1] Howard Gardner’s Multiple Intelligence Theory was first published in Howard Gardner’s book, Frames Of Mind (1983), and quickly became established as a classical model by which to understand and teach many aspects of human intelligence, learning style, personality and behaviour — in education and industry.

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