Man faces a unique challenge in the era of smart machines. The threat, in the form of artificial intelligence, is even more acute for knowledge workers. Knowledge work accounts for a large proportion of jobs in mature economies, and requires college education, is more mental than manual, and involves consequential decision-making. The fears aren’t unfounded really, with automation insidiously encroaching upon every walk of life, bringing with it the social and psychological ills of unemployment, identity crises, and economic recession. Even Gartner predicts many regular functions of today’s executives would be automated, especially the less cognitive tasks, in the foreseeable future.

This then begs the question, which of the functions currently performed by humans is likely to be imminently replaced by machines that offer a cheaper, faster, and more productive option? A way around this unsettling issue, however, is to give it an easy positive spin – that people will achieve more incredible feats with better thinking machines coming to their aid. Thus, the threat of automation can be countered by discovering newer opportunities of augmentation and identifying employment possibilities in evolved roles and functions. Even today, as automation is making incursions into the traditional workplace, there are instances of knowledge workers widening their bandwidth and discovering possibilities of doing things that neither would accomplish on their own.

While automation proceeds with a baseline of what people do in a certain job and subtracts from that, augmentation on the other hand begins with what humans currently do and identifies how greater use of machines can enhance and not diminish it. Smart machines thus set man free from the bidding of robots and create opportunities for tasks that are superior and more suited to his strengths. Augmentation strategy prepares man to redefine their roles and reengage in five distinctive ways.

Step Up: Especially suited for people with higher degrees and engaged in intellectual pursuits or innovation efforts, this strategy requires that they orient themselves around the big-picture, think more synthetically, and head for still higher intellectual ground leaving the intellectual spadework to machines. Niven Narain, cancer researcher and co-founder of Berg in Massachusetts, for instance, applies artificial intelligence to discover new drugs. While his high-throughput mass spectrometers run around the clock, producing trillions of data points from their analysis of blood and tissue, and powerful computers look for molecular patterns, his biochemists proceed from where the machines leave off producing a hypothesis and begin their investigation of its viability.

Step Aside: While a small section of the workforce has scope of stepping up, this strategy builds on what renowned psychologist Howard Gardner calls our “multiple intelligences”. Many wonder why legendary thoroughbred trainer D. Wayne Lulas never could articulate how he managed to spot potential in a yearling. Nor could Apple’s master designer Jonathan Ive download his vision to a computer. The same holds for many legal experts, top-notch investment bankers, architects, and creative wizards. While it is best left to smart machines to accomplish the ancillary tasks that impinge on their seamless functioning, their genius lies in channelizing the ineffable strengths they possess. As an augmentation strategy, it helps its practitioners to identify and develop “multiple intelligences’’ beyond IQ and conventional processes, and explore opportunities to apprentice or collaborate with “other masters of the tacit trade.”

Step In: In 1967 Peter Drucker declared of the computer “It’s a total moron”, witnessing the early attempts at automating knowledge work. That was then. Not so long ago, a man in US had applied to refinance his mortgage after just changing jobs. He was turned down despite having held a steady government job for eight years, with 20 years of teaching experience before, on the grounds that his new career was fraught with uncertainty. The gentleman in question is none other than Ben Bernanke, former chairman of US Federal Reserve for two terms. His new assignment that the smart systems found skeptical comprised signing of a book contract for more than a million dollars and an innings at the lecture circuit.

The message is not lost on us – when machines fail us, man must step in and prevent its relentless logic and mindless functioning from creating havoc. In an augmentation environment, people must be adept at monitoring and modifying the worst tendencies of a smart system.

Step Narrowly: This strategy encourages professionals to identify specialties within their craft which wouldn’t be cost-effective to automate or yield results that would fall far short of human output. A Johns Hopkins Magazine sites the work of French authority on paper Claire Bustarret’s work to illustrate this. Clair “made a career out of knowing paper like other French people know wine”, with her uncanny ability to determine from a sheet’s texture, feel, and fibre when and where the paper was made. Her wisdom is extremely valuable to historians and art authenticators. While her analytical techniques could be automated or knowledge suitably captured in databases, her fame and fortune accrue from hands-on training, hard work, and discipline of focus. Those who step narrowly “are hedgehogs to the stepping up foxes among us”.

Step forward: Finally, birthing the next generation of computing and A1 tools calls for a step forward initiative. No new automation idea or its construction can do without human genius– his knowledge of artificial intelligence, computer science, and analytics. Stepping forward

is premised on sensing the next automation need or opportunity, perceiving the gaps, and envisioning tools and utilities that do not even exist in the horizon. “Stepping forward means bringing about machines’ next level of encroachment, but involves work that itself is highly augmented by software.”

Each of these five strategies is effective, though identifying and adopting the appropriate one depends upon the industry and the individual. In essence, smart workers don’t allow automation to displace them, rather collaborate with smart machines to enhance their prowess and broaden their repertoire.