Every professional seeks to accumulate skills in demand to stay relevant in the job market and to the most desirable employers. The skillset – intensive in one area or wide-ranging across several domains, coupled with managerial experience or focusing on functional expertise – is the one selling point of job aspirants.
The turn of the decade brought up the question of developing the skills in demand against the tide of automation. Automation in the form of robotic co-workers or mere computer servers with repositories of code is already a part of the present world of work. Business houses take them for granted enough to say they’re “running in the background” doing what the organizations need to keep running smoothly while human workers get the work-life balance and time to spend energy on their priorities as they need.
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Shoring up skills in demand in a fast-paced tech world
Skills in demand can be summed up as “doing what humans do best”. All is not balanced in a future of work with shifting priorities and advancements. The skills in demand keep switching too and job aspirants need to keep ahead of the trends to be sought after by employers. Artificial Intelligence (AI) and Machine Learning (ML) take the efficiency of repeatable tasks and established workflows to a whole new level. “Automation” can follow several finite loops and get better in the speed, accuracy, and resource efficiency of a well-mapped-out workflow as the number of iterations it performs increases. This can mean that, ultimately, the repeated workflows and roles associated with them do not need a human worker doing the same job day in and day out. Instead, a “machine”, in this case, a computer system of a mere set of systematized instructions can take over at least a portion of the job role, freeing up the human worker’s time and energy.
This development is a double-edged sword. While it improves outcomes at the production-and-execution-end of most products and services, it can make some job roles obsolete because the skills are no longer the most sought-after and have given way to rote work by machines in non-ideal or dangerous conditions. Does that mean aspiring jobholders and working professionals are suddenly staring at an abysmal hiring outlook? Not if the skills in demand are updated routinely and with discernment. When skills in demand are examined closely, it is the decision-making and judgment-based aspects of knowledge work that do not give in easily to the proposition of automation. The writing on the wall with regard to skills in demand is clear: It requires the ability to harness the power of automation along with the unique attributes of personality.
Here is a list of skills that can buck the trend of automation and retain their prevalence well into the future:
Emotional intelligence: It is only human workers that can keep up with the “big picture” or “consider the circumstances”. While a robotic worker can work within a hair’s breadth worth of precision near dangerous machines and working conditions, it is the human operation that can judge when a team member is overworked, has an emotional complex derailing their judgment/ability, or is simply “not up for it” on a given day. HR policies framed by humans can further frame guidelines on what to do with an employee who’s having “an off day” but it’s the human manager who can tell if the emotional state to do work well is present in their team. This cannot be hardcoded in 0s and 1s and automated.
Circumstantial evaluation: No one expected to face a healthcare emergency that outlasted a year and longer. But the humans behind decisions are now able to take it into consideration while framing policies or revising them. An automated loop operating under a finite number of conditions would not be able to take into account breaking news, weather conditions, or calamities. A human with the skills in demand would oversee the finer outcomes and antecedents when automated loops are entrusted to strategic decision-making.
Brainstorming: This can be outsourced partially to automation but not fully. Automation cannot turn specific conditions on or off based on critical thinking or creative judgment. Human beings can give different answers to similar questions depending on whether they are rushed, relaxed, excited, or physically strained. This isn’t the case with machines. The sheer range of answers possible to be conceived in a human mind itself is therefore much greater than the scope that a computer-based system makes available. In a creative or critical thinking sphere where “lateral thinking” or “out-of-the-box solutions” make all the difference, jobs cannot be outsourced to robotic workers which only follow a duly defined set of known conditions.
Judgment of outcomes: We, as humans, learn a lot after the fact. So do machines. But the course-correction based on a set of outcomes in machines is not as refined as it is in human beings. Human workers, such as teachers and trainers, can offer inputs stylized to each learner in a roomful, examining each learner’s absorption potential and offering up challenges simultaneously to drive a concept home. Robotic learning assistants can, at best, do this for a single learner who might still fudge up the outcomes by answering incorrectly. The subtle communication, especially the non-verbal cues, that a human can take into account are, by far, missed out by a robotic teacher.
Repositories to be tapped: Computers can store great reserves of information. But knowing which volume and which file to pick and relate with the current need is a question of judgment and discernment that originates in the human mind. Machines with automated processes for parsing available information can only make lists of suggestions. The humans at the top of the totem pole can harness this quickness and thoroughness to make better decisions with the help of machines. The opposite is untrue. Machines cannot sift through and match scenarios to requirements. They only list the number of similarities and draw a parallel.
Comprehension and motivation: Human minds are most sought after by others in distress or in dilemmas. This is why life coaches, therapists, religious gurus, and guides are chosen based on a bond, feeling, or supranatural connection. This is entirely outside the realm of automation and simply cannot be replicated. A human manager knows the kind of activities, challenges, and motivational combinations that make their teams tick or get turned off. Personality plays a huge role in the way events and ideas are perceived. Creating an experience of depth for a workforce of human resources is a human manager’s job, while the collation of a number of such activities might be made easier by a slew of inputs from an automation stack.
All in all, these are traits and skills that humans can adopt and even combine in the required proportions. Undoubtedly, the future of work marks these out not only as skills in demand but as skills that are indispensable. When these are in place, the assistance brought about by automation fits in just right.
- Are You Developing Skills That Won’t Be Automated?|HBR|Stephen M. Kosslyn|September 25, 2019
- 15 Jobs That Will Never Be Replaced By AI|Chan Priya on medium|January 03, 2020
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