Source: Academic Headlines
When it comes to the future of intelligent robots, the first question people usually ask is: How many jobs will they make disappear? Whatever the answer, the second question is likely to be: How do I make sure my job isn't one?
Recently, a new study was published in the journal Scientific Robotics, and roboticists from the Swiss Federal Institute of Technology (EPFL) and economists from the University of Lausanne provided answers to these two questions.
By combining scientific and technical literature on robotic capabilities with employment and wage statistics, the researchers developed a method for calculating which existing jobs are more likely to be performed by machines in the near future. In addition, they have devised a methodology to advise these high-risk occupations on the transition to less risky jobs that require minimal retraining.
The results showed that for a ranking of 1,000 occupations, "physicists" were the jobs least risked to be replaced by machines, while "slaughterers and meat packers" were at the highest risk of being replaced. In general, jobs in the food processing, construction, maintenance and mining industries appear to be the most risky.
The Fourth Industrial Revolution, the competition between workers and robots
Robotics and artificial intelligence (AI) are often referred to as the core of the Fourth Industrial Revolution. Continued advances in these areas are leading to robots participating in all aspects of human society more autonomously, more dexterously, and more securely than their predecessors.
Intelligent systems have also surpassed humans in tasks that once seemed impossible for machines, such as the very complex game of Go. These advances, combined with equally important breakthroughs in high-performance computing, the Internet of Things, and new materials, have had a clear impact on manufacturing and services.
Therefore, it is expected that in the next few decades, the entire human economy and production system will undergo a wide range of transformations.
(Source: Pixabay)
While many analysts predict that the revolution will have a positive impact on overall productivity and growth, its potential impact on employment has attracted a great deal of attention. Robotics and artificial intelligence look promising to automate many of the tasks currently done by humans and reduce the need for human jobs in many sectors of the economy.
This is nothing new: the wave of automation of the past (such as the mechanization of the textile and agricultural sectors, the introduction of industrial robots in manufacturing, and the computerization of the service sector) first increased the working population in the early stages of development, and then drastically reduced the demand for human employment labor. In fact, in the past wave of automation, machines have mostly replaced humans for low-skilled, physical, repetitive work.
It has been suggested that the social impact of the Fourth Industrial Revolution will be very different, as the next wave of robotics and artificial intelligence will also affect medium- and high-skill jobs, including those with relevant cognitive and creative components, as well as areas of manual craftsmanship that require automation that has not been touched until now.
(Source: Pixabay)
While the impact on productivity and overall economic growth may still be positive in the long run, the transition can be painful.
In previous related studies, it has also predicted how many jobs will be automated by robots, but most of them are concentrated on software robots, such as speech and image recognition, financial robot advisors, chatbots, etc. In addition, these projections fluctuate wildly with job requirements and how software capabilities are assessed.
"In this latest study, we consider not only AI software, but also really intelligent robots that perform manual work, and we developed a system that compares hundreds of ways to compare the abilities of humans and robots at work." Professor Dario Floreano, Director of the EPFL Intelligent Systems Laboratory, said.
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To predict the risk of most occupations being replaced by machines, the researchers looked at europe's H2020 Robotics Multi-Year Roadmap (MAR), a strategy document of the European Commission, regularly revised by roboticists, that describes the dozens of capabilities that current robots need or may require in future robots, organized by categories such as operation, insight, perception, interaction with humans, and more.
MAR describes the dozens of capabilities that current robots need or future robots may need, organized by categories such as operation, insight, perception, and interaction with humans.
The researchers then assessed the maturity of robot capabilities through research papers, patents, and descriptions of robotic products, and used a well-known scale to measure the level of technological development, known as the "Level of Technical Readiness" (TRL).
(Source: EPFL)
For human capabilities, the researchers relied on the O*net database, a widely used resource database in the U.S. job market that categorizes approximately 1,000 occupations and covers the skills and knowledge that are most important to each occupation.
After selectively matching the human abilities in the O*net list with the robot's abilities in the MAR documentation, the team can calculate the likelihood that each existing job occupation will be performed by the robot.
For example, a job requires humans to work with millimeter-level motion accuracy, and robots are very good at this, so the corresponding ability has the highest TRL. If a job requires enough of these skills, it is more likely to be automated than a job that requires abilities such as critical thinking or creativity.
A ranking of the Automation Risk Index (ARI) of 1,000 jobs showed that "physicists" were the least risky of being replaced by machines, while "slaughterers and meat packers" were at the highest risk.
Figure | Automation Risk Index for Five Occupations (Source: Science)
Figure | Automation Risk Index by Industry (Source: Science)
The researchers then also created a way to find alternative jobs for any given occupation that significantly reduce the risk of automation and are fairly close to the original job in terms of required capabilities and knowledge, thereby minimizing the cost of retraining and making career transitions feasible.
"The main challenge facing society today is how to deal with automation," said Rafael Lalive, a professor at the University of Lausanne who co-led the study, "and our job provides detailed career advice to workers at high risk of automation, while repurposing many of the skills acquired in old jobs that will enable them to take on safer jobs." With this proposal, the government can support societies to become more resilient in response to the wave of automation."
To test how the method performed in real life, the researchers used data from the U.S. Department of Labor and simulated thousands of career changes based on algorithmic recommendations, finding that it could indeed allow workers in high-risk occupations to move to medium-risk occupations while undergoing relatively low-cost retraining jobs.
The researchers say the government can use the method to measure how many workers are likely to be at risk of automation and adjust retraining policies, companies can assess the cost of increasing automation, robot manufacturers can better tailor products to market demand, and the public can determine the easiest way to reposition themselves in the job market.
Finally, the researchers turned the new method and data into an algorithm that predicts the risk of automated replacement for hundreds of jobs and suggests a resilient career transition with minimal retraining.
(Available at: https://lis2.epfl.ch/resiliencetorobots Public Access)
As can be seen from the above figure: the risk of academic jun being replaced by robots is quite large...
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