New digital-native companies have been relying on algorithms to supervise the operation. Their algorithmic self-servicing tools and real-time monitoring have been taking the middleman out of the equation. As automation, software bots, and AI takes away the value of experience, senior professionals get nervous about future career prospect. We all know that technology affects jobs. But does it affect all types of jobs uniformly? Unfortunately, technology progression is a blessing for some jobs, while others suffer from it. Hence, Job polarization effect like hollowing out the middle or juniorizetion has been causing uncertainty in the future of work. It has been a significant concern for many of us. The investment we make today in taking education and building a career will likely be affected by technology in the future.
Job polarization refers to the non-uniform implication of technology advancement on creating and automating demands of different categories of skills. For example, job division, specialization, and mechanization lead to the reduction of skill demand in manufacturing. Hence, low-skilled people became qualified for factory jobs. But due to it, artisans lost jobs. Similarly, due to the ease of automation of data gathering and computational jobs, skills of number crunching and solving mathematical equations have been losing demand. Due to it, jobs for developing software applications for automating those tasks are facing higher demand. On the other hand, as jobs requiring humans’ innate abilities, like dexterity, touch, and feel, are highly complex to automate, technology progression has been having relatively fewer implications on this type of jobs. Furthermore, technology progression creates jobs in one industry or country while killing jobs in other places.
Human roles at work and relative complexity of automation: Genesis of job polarization
To find root causes of polarization, we should look at human roles in jobs and the relative complexity of automating them. Human beings become qualified for jobs due to three eligibilities: (i) codified knowledge and skill, (ii) experienced earned knowledge and skill, and (iii) innate abilities. Although we spend long years getting education and training, earned codified knowledge and skill are highly amenable to automation. On the other hand, knowledge and skill that we earn through experience in the tacit form are also getting candidates for automation. To a surprise, our by-born innate abilities like empathy, imagination and idea generation are highly complex to automate.
As every job does not require each of these eligibilities to the same extent, all jobs are not equally susceptible to automation. For example, contrary to common belief, bottom layers jobs having high reliance on innate abilities have a low risk to automation. On the other hand, middle layer managers mostly rely on codified knowledge and skill. Hence, their jobs are highly vulnerable to automation. But as top layer jobs require very high level innate, tacit and codified capabilities, top management is more or less immune to automation.
Hollowing out the middle:
On average, one manager supervises 4.7 workers so that they can perform effectively and efficiently. Managers’ supervision includes monitoring employees’ work, tracking divisional performance, and ensuring compliance with organizational directives. Due to connectivity, sensors, and the internet of things (IoTs), increasingly, managers can perform these tasks without directly engaging with workers. Hence, automation, robots, and AI are taking over those jobs, as these technologies are highly efficient in collecting and analyzing data, detecting deviations, checking compliance, and offering feedback. But middle management jobs also include persuasion, empathy, communication, motivation, and strategy formulation. These roles are still difficult for technology to take over. Hence, depending on the nature of management roles, the middle layer of the organization has been suffering from varying levels of job loss.
On the other hand, bottom layer workers needing high-level innate abilities are far less susceptible to automation. For this reason, emerging technology eliminates middle management jobs while preserving low-level jobs, such as cooks, food packers, and drivers.
At the top level, managers need a high-level capability of imagination, gut feeling, and interpersonal communication for performing root cause analysis, envisioning future direction, designing strategy, fixing dysfunctional ones, pursuing resource allocation, and motivating teams to move forward. Current AI technology is not strong enough to take this role. Hence, the top layer seems to be immune to automation.
Job polarization effect at the organization level for the above reasons has created the hollowing out the middle. Statistics from different sources have been supporting this pattern. For example, according to Gartner’s prediction, by 2024, software bots will take over almost 69% of the manager’s workload in the USA. Similarly, a global survey finds: 78% of the responding executives believe that there will be a dramatic reduction in middle management roles due to AI.
Country-level job polarization:
Like organizational levels, technology has a varying effect on country-level jobs. For example, manufacturing job simplification due to job division, specialization, automation, and production line, less developed countries’ low skilled workforce became eligible for factory jobs. Hence, MNCs migrated manufacturing jobs to benefit from the low-cost labor of less developed countries. As a result, due to technology, countries like Bangladesh, Vietnam, and Indonesia got blessed with export-oriented manufacturing jobs.
But further advancement of the technology leads to the creation of high-paying innovation jobs in advanced countries. Unfortunately, the import of those solutions will lead to factory job loss in less developed ones. Furthermore, in comparison to factory jobs, data and knowledge-intensive jobs have a higher level of vulnerability. Hence, countries having a high concentration in the export-oriented service industry will likely suffer from far higher-level jobs than countries having manufacturing concentration. For example, during 2021&2022, India is expected to lose 3 million jobs in its export-oriented IT and BPO service sectors. Hence, due to the current advancement of AI, automation, and robots, less developed countries risk being net losers in jobs.
It seems that there will be a country-level hollowing-out middle effect. Countries at the top of the pyramid will benefit from jobs creation for innovating AI, automation, and software bot solutions. On the other hand, countries like Bangladesh, Vietnam, and Malaysia will have moderate job loss implications. This is because the bottom layer countries have been relying on the innate abilities of low-skilled workers. But countries having an educated workforce engaged in export-oriented service jobs will have level implications. Export-oriented jobs in IT service and BPO will likely have high-level job loss implications due to ease of automation.
Likely remedy: sharpening innate abilities and focusing on fusing technology with human competence
The advancement of technology is taking away increasing jobs is unstoppable. The typical response has been to upskill. Upon losing the management jobs, what are upskilling options? There could be a suggestion of getting into skill development to be AI programmers. But as AI solution is software, the cost of copying it is zero. Hence, a sufficient number of jobs will not be created in AI solution development for accommodating displaced and upskilled managers. Instead, managers should focus on sharpening innate abilities like empathy and motivation so that they can complement technology.
On the other hand, instead of becoming vulnerable to AI, managers should empower them. They should delegate routine data handling jobs to technology and focus on adding value out of soft abilities. Like managers, bottom layers workers can also benefit from sharpening innate abilities. On the other hand, less developed countries should have priority on being idea producers for leveraging technologies.