In the late 1800s, humanity saw the Industrial revolution. Since then, there have been a large number of advancements, so many machines have been designed. We invented Tractors to reduce human toil and labor on farms. We designed looms and other machines for the textile industries. We made machines that replaced people in assembly lines and machines that could replace labor in mines and quarries.
Despite all these, the number of advancements in technology, the number of jobs has only gone up. What exactly has been happening?
ATM machines were designed in such a way and were supposed to remove human tellers in banks. And that did happen, the number of tellers in banks reduced by almost a third. But at the same time, the cost-cutting allowed the banks to open more branches and hence the number of branches increased by 40 percent in the same time period. That actually meant more jobs.
In 1986, the Challenger Space Shuttle crashed a few minutes after its launch. The investigation revealed that a simple rubber O-ring froze the night before and it failed drastically right after the launch; all the other mechanisms working perfectly. This led Harvard Economist Professor Michael Kremer to coin the term, O-Ring Principle. It says that every process or a mission is like a chain and individual steps and components are its links.
This leads to some very positive implications: if one link is improved then the result of improving other links is more rewarding. This improves the reliability of the entire system/process and encourages improvements in general. In other words, in the past century, despite the improvements in technology, the value of our judgment, expertise, and creativity has only gone up.
In the 1900s, around 40 percent of the adult population in the United States of America was employed in agriculture and other farm-based jobs. Today, that number is around 2 percent. That two percent now produces enough food for the other 98 percent, thanks to the technology. Back then, the introduction of tractors and other machines like harvesters caused a great deal of panic within the farms and the general population because there were no jobs for people.
But something else happened: people now started going back to school. They started learning and no longer did they have to start working at the age of 11 or 12 years. This was one of the most important and intelligent investments ever done. In fact, if we go back in time and pick a handful of the labor force from back then and bring them to the present day, they would be unemployed despite having strong backs and capability to work hard. And this indicates how important it was to allow people to improve this particular link in the process.
How is Automation different this time around?
When cars were brought to market for the first time, it was an instant success; not just because people were buying new cars. The presence of cards led to the rise of several other businesses and industries. There were more gas stations, drive-through restaurants, motels, auto-garages, and drive-through theatres. New roads were built and that created a lot of jobs.
However, despite new advancements in technology today, the rate of creation of new jobs is not keeping up with the rise in population. To add, data suggests that technology is now increasing productivity without the involvement of more humans. Take General Motors for example. In 1979, General Motors had around 800,000 employees and it generated a revenue of around eleven billion USD. In 2012, Google generated revenue of fourteen billion USD with just 58,000 employees.
Similar cases show up when we consider the rise of the internet. In 2004, Blockbuster had around 84,000 employees and generated a revenue of around six billion USD. In 2016, Netflix had just 4,500 employees and generated nine billion USD as revenue. This is true for numerous other industries. The innovation this time around is not creating new jobs.
The simple explanation for this stark difference is the fact of how innovation itself has changed this time around. Today, with artificial intelligence and things like machine learning and deep learning and neural networks we are moving towards a goal to replace some qualities that distinguish us from the machines back in the 20th Century.
Today, the software is capable of learning and predicting the behavior of human beings; and is capable of making informed decisions and educated guesses. We see this as a part of our Google searches, Youtube watch history, Spotify, Adsense, and many other things. There are things where machines are learning fast and growing at an exponential rate.
In a nutshell, AI and automation, in general, is more likely to take away more jobs this time instead of creating them. This is simply because the nature of automation itself has changed. Previously, machines were supposed to do repetitive and predictable tasks over and over again but today we are teaching them to solve more complex problems and perform more complicated tasks.
So, what do we do?
So we do know that the new advancements are taking away our jobs faster than they can create new ones. And this sounds like a crisis in the making. The solution to this looming crisis, however, doesn’t really lie in the way we develop. There are people who believe that we will work our way through it just like we did in the past. Others, who rely less on hope and believe in working towards their goals believe that the solution to this crisis would lie in the economic policies, such as a Universal Basic Income and Welfare Programs.
Both the UBI and Welfare program approaches to this crisis require a great deal of patience and research. Many governments around the world realize the gravity of the situation being faced and if something, we might be wrong about this crisis in the first place. Maybe we will find our way through. Only time will tell.