Automation in industry isn’t a new concept. Mankind has constantly looked for better ways to make things at a faster and cheaper clip, and since the first industrial revolution – over two hundred years ago! – we’ve improved the basic process of mass industry in huge, mind-boggling ways.
This improvement, however, has been accompanied by massive changes to how our world operates. The introduction of new machinery-based processes transformed the job landscape and society as a whole in the 1800s, rendering entire jobs obsolete albeit creating new ones.
The current fourth industrial revolution is no different. Robotics and artificial intelligence now form the backbone of the automation sector, and the new machines of today bring with them renewed fears that they will take over our jobs.
These fears are understandable. Decades of research point to how the introduction of robots and AI into automation are transforming sectors that have traditionally supported entire families and communities for generations.
45% of current jobs can be automated, according to a study by American management consulting firm McKinsey & Company. Analysis firm Oxford Economics predicts that up to 20 million manufacturing jobs around the world could be replaced by robots by 2030, amplifying fears already dramatically echoed by notables such as Tesla’s Elon Musk and the late Stephen Hawking.
The agritech sector, for example, is a rapidly expanding USD$7.8 billion industry that makes use of drones, Internet of Things-based sensor networks, automated irrigation and AI: all handling tasks historically held by humans, but now handled and upscaled by technology to meet the needs of an exponentially-growing global population.
Is artificial intelligence really taking our jobs, though?
Understandable as these fears are, just how valid are they? As it turns out, less than we think.
The Human touch
Just as machines are replacing old jobs, they also create new ones. Boston University economist James Bessen argued this point over four years ago, pointing out that the advent of automated teller machines in the 90s, while reducing the immediate need for human bank tellers, actually led to increased overall employment as banks jumped on the opportunity to open new branches with the money they saved on hiring fewer staff per branch.
Besides the finance sector, which today sees the widespread use of AI solutions for bankers, the agritech industry is also quickly rising, as farmers make use of new AI and automation solutions to scale up operation size and efficiency. For example, German startup Plantix, an agritech company based in Berlin and Hyderabad, India, uses AI to identify plant diseases, pests, and nutrient deficiencies, via an app used by over 1.2 million farmers at least once per month, according to co-founder Simone Strey. Far from killing the agriculture industry, solutions like these create more opportunities for farmers.
Besides finance and agritech, manufacturing and factories are also being particularly transformed by automation and artificial intelligence. The workforce-intensive production lines of Henry Ford’s day have been replaced by increasingly people-free environments, a transformation heavily accelerated by the advent of data-powered automation.
Factories are now safer and more efficient, as the large amounts of data gathered and analysed in manufacturing operations, equipment and machinery, sales patterns and demand fluctuations enable strategic and safe upscaling of output. For example, IoT-enabled sensors can detect when machinery needs check-ups, preventing more serious, costly faults and disruptions.
All of this enables people to move off the company floor and onto actually managing these new systems, analysing the data gathered and operating the robots doing the heavy lifting. The robots deployed across factory floors are freeing up humans to take on higher value work; MIT researchers also found that human-robot teams working for BMW “were approximately 85% more productive than humans or robots working alone”.
Artificial intelligence is creating jobs, not replacing them.
A 2018 report by the World Economic Forum says that even as machines and algorithms in the workplace are expected to cause 75 million jobs to be displaced by 2022, they will also create 133 million new roles. The AI revolution is creating whole new areas of employment and remote workforces not confined to offices and factory floors.
Data annotation and labelling in machine learning is one of these new sectors. Artificial intelligence is driven by algorithms that still need to be fed pools of training data precisely marked and annotated by humans; image recognition systems, for example, need large volumes of clean and properly labelled data for training over multiple iterations to build a model that can accurately recognise future images.
Big companies such as Facebook, Amazon and Google still heavily rely on human input for their data labelling needs. Supahands itself employs 13,000 SupaAgents worldwide that work on data labelling projects.
Is automation changing the job landscape? Certainly. Humans, however, aren’t going to be obsolete anytime soon. Machine and man will be working hand-in-hand for the foreseeable future, and we just need to change the way we do things.