Are you afraid of being replaced by a robot? Being a physicist • The Register

An online index of nearly a thousand jobs can be helpful in educating people about the risk of automation facing their job field.

Below the list – meaning they are most likely to be replaced – are meat packers and slaughterhouse workers, while the least likely to have their work automated are physicists. In general, those in the food services, grounds and maintenance, and construction industries are most at risk. Those in education, social services and management are less so – but not entirely so.

Scientists from the École Polytechnique Fédérale de Lausanne and the University of Lausanne in Switzerland collaborated to establish the index by considering the potential social impacts of automation. While their list targets individuals, the team said there are other uses for the methodology it developed to create the automation risk scores featured in the index and map people’s career transitions. displaced workers.

In particular, an article the team wrote about their work argues that “Governments could use [underlying methodology] to assess the unemployment risk of their populations and adjust educational policies”, and “robotics companies could use it as a tool to better understand market needs”.

Researchers have compiled a list of jobs from the Professional Information Network – a public data set of 967 jobs and their relevant knowledge, required skills and necessary abilities. The knowledge, skills, and abilities (KSA) for each job were compared to the likelihood that an AI or robot could do them, with specific robotic tasks defined by SPARCMulti-year robotics roadmap.

To add to the analysis process, the likelihood of an AI or robot taking said job was assessed using the UE technology readiness levels [PDF]who assess how close new technologies are to realization.

Automation Risks

The researchers didn’t just want to know who was at risk, they also wanted to create a method of comparing jobs to suggest more resilient careers for people at risk of losing their jobs to automation.

To understand this, a two-part formula was created with two outputs: an automation risk index (ARI) and the resilience index (IR).

For the first, human KSAs are compared to relevant robot and AI capabilities to yield a number between 0.43 (low) and 0.78 (high) automation risk.

Take journalists and correspondents, for example: our ARI is 0.58, just under half the scale. Computer programmers are a little higher at 0.59, while network and system administrators are just a little lower at 0.57.

People in the high-risk category include all of the food preparation and service industries combined – which have an ARI of 0.72 – those working in the mining industry (0.69) and jobs” aid” in the construction and service industries.

The lowest scores are found among post-secondary education (low 0.5), doctors and other medical careers, and the legal profession.

Retraining Rewards

The RI part of the equation generates a number — the lower the better — that indicates “employment transitions with better trade-offs between automation risk and retraining effort,” the paper explains. Jobs with relevant skills, at least according to how the team built their model, are sorted by ARI score and the amount of effort required to learn the relevant KSAs.

The online tool includes three career alternatives for each of the 967 occupations studied by the researchers. According to the tool, journalists and correspondents should consider becoming post-secondary law professors, physicists or mathematicians.

It’s exactly the same advice he gives to actors, poets, lyricists and creative writers, and almost the same advice he gives to musicians (just trade a law professor for a statistician). These professions may at first glance seem unlikely to be replaced by robots in the near future. Nevertheless, it is good to know that musicians can fall back on statistics if necessary. Dylan, for example, could draw a graph showing exactly how many roads a man should take. ®

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