Robots and AI are coming to a lot of workplaces, and they may disrupt jobs in many areas. That’s why a new tool has been created to help people decide what to do when their current job is no longer secure.
The tool ranks jobs from lowest risk to highest. For instance, physicists are the safest from automation, while meat packers and slaughterhouse workers are most at risk.
Disruption to jobs in many areas
Robots are transforming work in a variety of ways, affecting jobs and the way we do them. They can perform tasks that were previously done by humans, and they can be more cost-effective and less prone to error than human employees.
But if automation takes over a large proportion of jobs in an economy, it can have a significant impact on employment overall. The effects vary based on the type of job, where it is located, and who performs it.
As a result, it is important to consider the entire picture when assessing how job automation will affect the economy. It is also important to understand the potential impacts on a variety of groups, including those with low educational attainment, minorities, and women.
Researchers at Oxford University used a machine-learning algorithm to assess how many different kinds of jobs are likely to be automated in the next decade or so. It then created a ranking of occupations based on their automatability.
The report found that while most occupations are susceptible to automation, certain types of work are particularly vulnerable. These include routine manual labor and lower- and middle-income jobs, especially in rural areas and the Rust Belt.
While automation may have a negative impact on some workers, it can also create positive spillovers into the broader economy. It reduces the price of goods, and generates shared capital income gains.
In addition, automation could lead to job reskilling in some industries. For example, it could allow accountants and other professionals to move into higher-value roles if they no longer need to do repetitive tasks.
Similarly, it could help lower-wage earners find new ways to make a living. In the fast-food industry, for example, computers can order food and pay for it, allowing them to focus on serving customers rather than on the mundane tasks of preparation and cleanup.
These findings provide a valuable perspective for companies and government agencies that must consider the future impact of AI and other technological changes on the workforce. They can use these insights to design policies that will protect the most vulnerable and ensure that AI does not cause more harm than good for the economy.
Many observers believe that recent developments in robotics and artificial intelligence (AI) may lead to unprecedented waves of automation-related job losses. They claim that the new technology improves at an accelerating rate and substitutes for a much wider range of job tasks than earlier waves of computing technologies. This may cause millions of workers to lose their jobs.
This view has been widely cited in the media and by governments as a basis for concern about future job losses. However, a closer look at employment trends in the past and projections suggests that many fears have been overstated.
Even within specific occupations cited in the automation literature, there are often large percent declines but few jobs that have seen their share of employment fall to levels that would suggest a broad trend. In addition, these losses are generally more than offset by growth elsewhere.
For example, a group of 81 occupations that experienced a 45-percent drop in employment between 1999 and 2018, equivalent to a 47-percent drop over two decades, only accounted for 3.8 percent of all jobs in that time. This means that if these occupations had been unaffected, they would have added only 3.3 percent to the overall total in 2018.
A much smaller group of 17 occupations that have been cited as examples in the automation literature also had relatively low rates of actual or projected job loss between 1999 and 2018 that were very similar to those foreseen in the automation literature. These 17 occupations are expected to decline or grow by at least half a percentage point below average from 2019 to 2029, and they were the only group of this size to show negative growth in both periods.
In this group, the BLS projects that technological substitution will have a stronger influence on employment than trade or offshoring, although it may not reach levels that would indicate a general trend toward widespread job loss. Table 3 shows that this group grew more slowly than average from 1999 to 2009 but grew faster than average from 2008 to 2018.
The BLS predicts that most of the occupations in the group accounted for less than 47 percent of all jobs in 1999 and have not been predicted to grow much faster than average for this period. Despite these results, the automation literature implicitly claims that technological substitution will be so great as to dominate any offsetting forces, producing unusually large job losses.
As machines continue to automate tasks, a growing number of employees will need to reskill. This could include those who were displaced from their jobs by automation, as well as employees who are already in new roles that require different skills than they had before.
Reskilling is a crucial part of preparing for the future of work. It helps companies avoid losing valuable staff when they need to transition quickly. It also keeps them competitive in the job market by attracting candidates who are looking to expand their skill set.
When reskilling employees, it’s important to gain their buy-in. It may take time for them to adapt to their new role, so it’s important to make sure they have the right training and support from management.
Employees who are reskilled are happier in their new position, and they will be more productive because they have the skills they need to perform their job duties efficiently. They may even be able to move up within the company.
Another benefit of reskilling is that it reduces the cost of hiring and onboarding employees. It also frees up resources to help existing employees get the skills they need for their next job.
In addition to reducing costs and easing recruitment, reskilling can improve employee morale. It shows that a company cares about its employees and is dedicated to their personal growth and development. This can increase loyalty and retention, which is crucial for businesses who want to retain their best talent.
By reskilling, companies can maintain their workforce when they need to change their business model or evolve into new markets. For example, a company that is shifting from a DVD-by-mail to streaming service will likely need to reskill their sales staff to sell directly to customers through live chats instead of over the phone.
As automation changes the way we think about work, workers who are reskilled in new ways are better off. They have more skills and experience to complement the new automation, and they often enjoy higher compensation than their counterparts who are displaced by automation.
Automation, also known as robotic process automation (RPA), changes how jobs are made. It reduces the costs of labor and increases productivity by automating tasks that previously required human inputs such as manufacturing, assembly, and maintenance. Its benefits include lower prices and fueling demand for products and services. But it also can eliminate a lot of jobs and change the skill sets required for them.
As a result, some people worry that automation could lead to massive unemployment, similar to what happened in the 1950s and 1960s when computers and industrial automation were feared to destroy American jobs. The question is whether the same thing could happen with AI, which may be able to do even more to change the way work is done.
One of the key arguments in favor of job automation is that it can help boost economic growth by making the economy more productive. In addition, automation can increase the number of jobs and increase their pay.
It can also improve the quality of some types of jobs. It can make people more effective, for example, by allowing them to perform complex tasks that are difficult to do efficiently or safely without specialized knowledge.
A study in 2018 from MIT found that it was possible to build new relationships between machines and humans that allow them to complement each other. The researchers concluded that if smart policies and practices were used, automation would be able to help create jobs instead of eliminating them.
But a study from Oxford Martin School’s Programme on the Impacts of Future Technology, which has been widely cited as an authoritative account of how automation will impact employment, estimates that 47% of American jobs are at risk of being automated in the next two decades.
The researchers based their calculations on gender, age, education level, and income. They argued that, if these factors are taken into account, only 9% of the nation’s jobs are at high risk of being replaced by robots.
The BLS projects occupational employment trends on a 10-year cycle, so it is natural to ask whether the recent projections suggest that some occupations are at particular risk of being overtaken by automation and whether the projections and trend data indicate that those occupations are large enough to be vulnerable. This article examines the employment projections for the current year and the previous decade, as well as trends since 1999-2009, for a sample of occupations that are commonly cited in recent works on automation.