History has taught us that technological advancements are almost never reversed — and the global push towards automation is going to be a mainstay for years to come. However, waves of automation are more like invasions, occupying the space low-skilled labour once held and making jobs obsolete.

Today, job loss due to automation is an increasingly heated topic. Self-driving cars are expected to heavily disrupt the logistics market in the US, an industry that employs about 8 million truck drivers as of 2019, 41.5% of which are from the racial minority.

Even skilled labour cannot escape the clutches of global automation. A Deloitte report predicts that 114,000 jobs within the legal industry are likely to be automated in the next 20 years due to business model changes resulting from LawTech. Even AI solutions such as AIVA and Amper Music are making music composers obsolete for small-scale creative productions.

Despite these damning case studies, will humans eventually be replaced by robots moving forward?

Too early to tell

Do note that much of the research within this area is not entirely conclusive. Most of the reports published are predictive in nature rather than descriptive, with projections extending to 2030 and beyond.

For instance, a 2017 McKinsey report states that 6 out of 10 current jobs have 30% of their workload technically automatable by 2030. It is likely that 400 million workers will have their work displaced, and 75 million needing to change career paths entirely. The figures have since increased by 25% in their latest 2021 report.

However, a large chunk of global automation was centred at the height of the pandemic in mid-2020. Many automation projects are still underway, with many change management processes taking years to complete. Thus, it is difficult to gauge the actual impact of automation on employment at this point in time.

Global Unemployment Rate (2010-2020)

For instance, the Fourth industrial Revolution (4IR) trend has driven companies to automate processes since 2016. Yet, global unemployment rates have steadily declined from 5.92% in 2010 to 5.37% in 2019. It suddenly spiked to 6.47% in 2020, but that can be attributed towards the global pandemic instead of a direct result of automation.

Rather than job loss, automation may lead to greater income inequality instead, with a report by Our World In Data confirming that this trend being more prevalent in high-income nations. However, correlation does not imply causation, and the report stresses that technology might only be one out of many explanations of growing income inequality.

More research needs to be done to provide a definite conclusion.

A look into history

Here is a neat fact — automation is not an entirely new phenomenon. 

Throughout history, humans have replaced menial tasks with tools or processes. To create fire, wood on wood has transitioned to flint and stones, and eventually modern day lighters; Trading on the stock exchanges used to be shouting matches, which turned into phone calls and eventually automated robotic trading. Yet, humans have always found new avenues to put their brains and brawns to good use.

In the 19th century, British weavers and textile workers banded together to oppose the use of mechanised looms and knitting frames. The Napoleonic Wars made textile production cheap, and artisans were being pushed out of their jobs. The group called themselves Luddites, and began breaking into factories and smashing textile machines. Some readers may find resembling news stories in recent years.

Looking deeper into history, readers may learn that periods of high unemployment rates have little to do with leaps in technological advancements.

With an unemployment rate as high as 25%. The Great Depression in the 1930s was caused by the collapse of stock market prices, a banking crisis and a whole host of other economical factors. In China, unemployment rates peaked at about 40% in 2009 due to the economic fallout of the 2008 Global Financial Crisis, affecting large swatches of rural migrant laborers who moved towards the cities for employment.

Periods of high unemployment rates are not uncommon throughout history, many of which are easily identified by their titles “The Panic of…” followed by the corresponding years, which ranges from 1837 all the way to early 1990s. High unemployment rates are usually the result of the following factors:

  • Economic Crisis
  • Infrastructure investments
  • Tax Policies
  • Healthcare costs
  • Employment policies
  • Educational policies
  • Regulatory reforms
  • Trade Policies
  • and many more

What makes robots preferable to humans?

To better understand the relationship between automation and job loss, here are the factors driving automation adoption within industries:

  • Upkeep costs

Although expensive upfront, automated solutions may save companies millions of dollars in the long run due to savings that would otherwise be channeled towards employee benefits, salaries and taxes. Automated solutions only require a few technicians to maintain and upkeep, requiring occasional firmware and hardware upgrades every few years.

  • Safety & health risks

Having employees work in the office has become a liability risk in the age of the pandemic. Fortunately, automated solutions do not sneeze, drool nor cough — making it a safer alternative.

  • Consistency & efficiency

Unlike human labor, automated solutions can operate 24/7 without breaking a sweat. As long as its core instructions are well defined, the work produced by automated solutions is consistent and reliable. Contrast this with humans who are prone to stress, fatigue and unpredictable interpersonal relations.

Why aren’t all jobs automated yet?

Business owners will soon realise that, despite all of its benefits, automated solutions do have its limitations.

  • Agility

Investing in automated solutions can be costly in terms of time and resources. While setting up a new solution, there might be newer workflows or product offerings that are superior than the ones already implemented. Employees, on the other hand, are better at adapting to the forever changing working environment and industry changes.

  • Creativity & analytical skills

Data solutions and machine learning algorithms can be programmed to run automatically, but businesses still require subject matter experts to consolidate these findings to convey meaningful, subjective insights. Automated tools, both digital and mechanical, can assist in strategy planning and execution, but it does not replace strategy itself altogether.

  • Cybersecurity and business continuity risks

Automated solutions generally rely on IT infrastructure and network connectivity, meaning more time and effort needed to be spent on ensuring its security and stability. Ransomware cases are on the rise, and companies are increasingly vulnerable to these attacks. While employees have their own unique risks, compromised automated solutions have an immediate impact on a larger scale across the corporation.

  • Data privacy issues

Many enterprise-grade automated solutions rely on third-party vendors and API providers to get the solutions up and running. A whole host of sensitive corporate data are potentially being stored and channeled through infrastructure that is largely outside of the company’s control. Unless data and processing capabilities are done entirely on-premise, there is a risk of sensitive data being leaked out or copied for nefarious use-cases.

The Innov8tif Approach

While automation can make certain jobs obsolete, there will be an endless list of high-value tasks that will always require human intervention. The most significant transitional pains are the efforts needed to reskill and upskill existing talents to fit their new roles.

While old jobs are increasingly driven towards obscurity, new jobs are mushrooming across various sectors, most of them are digitally-oriented. Employees are required to learn new skills on the fly and be more comfortable with adapting to new technological solutions in a changing environment.

With 11 years of history at Innov8tif, we are no strangers to new workflows, especially when handling cutting edge technology within the ID Verification realm. To help employees adapt to the switch we have adopted several key values:

  • Flexibility

Beyond several core functionalities, each Innov8tif department is free to utilise whichever tools needed to get the job done. By offering much needed flexibility, each department is able to evaluate its current resources, weakness and strengths, and work around automated solutions to maximise efficiency and work satisfaction.

  • Documentation

We are a fast-growing company, and it is important that new recruits are being brought up to speed. At Innov8tif, we cultivate a corporate culture of documentation, such as establishing SOPs and guidelines, so that work being delivered is consistent and replicable. 

  • Stewardship & Accountability

Great innovation needs to be backed with strong foundations and accountability. There are clear lines that could not be crossed, especially when it comes to data privacy and security related matters. While we encourage tackling challenges in unconventional ways, Innov8tif takes great lengths in educating staff members on not just technical skills, but fundamental values that are transferable across workflows, such as data management and cybersecurity awareness. 

We are hiring humans, not robots!  Join us by visiting our career page to learn more about our available job openings, or e-mail us at [email protected]!