The robots aren't taking your job yet, but with the increasingly adept AI systems being developed, it would be wise to understand how automation is being developed in the workplace-- and what functions it will replace first.
For as long as technology has developed there have always been concerns about the number of human jobs it will replace. We are 103 years past the first major technological turning point of the sort with Henry Ford's assembly line. This was pivotal in the development of modern society with shifts for workers in cities, moving from artisans to repetitive and relatively unskilled labor, mass production of technology, standardization practices, and dissemination of technology to the public with reduced costs.
The key to remaining viable in this shifting economy is to fill in the gaps that the new automation processes can't fulfill, and in this case, it is by doing what humans do best: thinking critically.
Opening Pandora's Box in Automation
Few innovations have proven to be as fundamentally groundbreaking as the advent of the assembly line. Almost every industry that produced goods operated by assembly line. The most important reasons for implementing it were standardization of products and increased efficiency of employees. Later, this expanded past production lines and into process improvements and automation of tasks given set parameters such as through algorithms.
Through this, the fundamental nature of economies and societal movements has shifted from one-off artisans to unskilled factory workers and ultimately to employees with diverse skill sets that make judgement-based decisions on a daily basis.
The effects of the assembly line on the Ford company were astounding. The standardization of production allowed for lower costs to produce, more reliable products, and an overall increase in the quality of the output. The time it took to produce a Model T went from 12.5 hours to 93 minutes. The marked increase in productivity meant a massive boost to profits for the company.
This also meant that there was a faster shift of people moving from rural areas to cities, and an increase in repetitive, low-skilled jobs.
The more complex and specialized the automation process became, the less skilled the labor force needed to be. As a result of this, craftsmen were no longer needed but instead 13,000 workers could produce 300,000 cars. At the height of this, the Ford factory was able to produce upwards of 1,000 cars a day- a number that could rival modern factories.
However, the extremely monotonous work led to high turnover rates. Ford responded by doubling his workers' wages to keep the assembly lines moving. He was ultimately able to offer his workers 5-day workweeks, which meant his employees were able to have the money and time to enjoy the leisure item they produced.
With the increased cost in labor, Ford was able to have an efficient enough factory to reduce the cost of the Model T from $850 to $260, ensuring the masses would be able to all buy his product.
Automation 100 Years Later: Business Process Automation to Deep Learning
As society progressed moving in to the 21st century, the needs of businesses shifted. In addition to having assembly lines for products, all tasks that include routine manual work and predictable data collection and processing are at the top of the list to be replaced by AI. With the development of the personal computer and coding technologies, the list of tasks that could be streamlined became unending. More complex algorithms were created to allow machine learning to make more realistic decisions.
Computerized librarians are able to identify misplaced books with 99% accuracy. Essay grading algorithms are able to almost perfectly match teacher-graded essays. Macros can process thousands of redundant financial transactions with little to no human interaction. There became another issue with the advancement of this technology: each system to be automated led to a more complex and cumbersome system to deal with. This led to Business Process Automation (BPA), which is in essence the use of systems to automate business based processes, not just assembly of products.
Some of the tasks that can be automated by BPA include: client management, marketing and customer support, almost all administrative tasks, website management, improved project management, document backup, people-tracking, simplifying legal work, improved forecasting, and more efficient communication. Computer algorithms are getting smarter and smarter and are able to handle almost any repetitive task or collecting data to make cut and dry decisions based on set parameters (so pretty much any entry-level job ever).
As artificial intelligence has been developed to mimic neural networking paths to mimic human learning patters, the range of tasks that can be processed by a computer are rising. Although the AI can try to do everything, the AI still needs to be supervised by the people.
The thing to remember is that automation is part of how the economy has naturally developed. It has not managed to wipe out jobs in the way that most assume. Humans are the most adaptive species, and we are able to change to meet need-gaps for positions and learn new skills to meet these new requirements.
The Flynn Effect and Staying Viable
Researchers have seen increases in IQ tests across generations and locations for the last 100 or so years. The areas of the greatest improvement have been critical thinking skills and complex problem solving. While our forefathers needed to know concrete items of knowledge like the most likely city to be a state capitol, much of the day-to-day work of modern generations revolve around emotional intelligence, managing and developing people, and applying diverse knowledge and expertise to make business decisions.
Take the argument of the librarian being automated: the position will shift to meet new requirements without the burden of the previous monotonous tasks. If the task of filing away books is able to be taken over by automation, then the need of the librarian shifts to being a research mentor. They are able to assist individuals to collect and analyze data, utilize resources available to them, and fill more person-to-person needs other than just filing books.
Develop critical thinking skills, interpersonal skills, emotional intelligence, and the ability to link disparate fields to find creative solutions to complex problems. Interdisciplinary knowledge will become more vital to viability. Soft skills are vital to develop.
- Communication Skills
- Computer and Technical Literacy
- Interpersonal Skills, Networking, and Work Ethic
- Research Skills (Finding Creative Correlations)
- Problem-Solving Skills
- Process Improvement Skills
- Project Management Skills
Expect careers to be augmented instead of being automated out of existence. As technology like this evolves, so will the tasks required, the skills, and the nature of the labor force. Those that are able to adapt their existing skills in new ways will be able to remain viable in the shifting economy without being replaced by robots.
Be excited, be inspired, create new things and solve complex problems. If you are able to go to work each day and learn something new, then it is likely you are in a position that is unsuited for automation, as least for the near future. Meta skills such as project management, personal networking, advising, and anything that requires greater emotional authenticity than a robot (literally) will take the most work to replace with automation.
Instead of asking what jobs will be taken away from automation instead ask how much more humans can achieve if lower level tasks are taken off their plates. Now employees are free to develop deeper understanding in their position, identify new skills and strengths and work on more creative, complex, and fulfilling work.
The most important way to stay viable is to stay excited to continue learning and developing yourself to take advantage of technological developments instead of competing against them. A change in mindset may ultimately be the most important thing of all.