New technologies create new jobs, not only destroy them, but the skills they require don’t always match old jobs. Successfully changing jobs requires making the most of your current skills and acquiring new ones .
To do this, according to a new study , a system has been developed to recommend career transitions, using machine learning to analyze more than 8 million online job ads to see which movements are likely to be successful.
Job transition
The system uses a measure that economists call ‘revealed comparative advantage’ (RCA) to identify how important an individual skill is to a job, using online job postings from 2018 . The map below visualizes the similarity of the top 500 skills. Each marker represents an individual skill, colored according to one of 13 very similar skill groups.
This new system begins by measuring similarities between the skills required by each occupation. For example, an accountant might become a financial analyst because the skills required are similar , but a speech therapist may have a more difficult time becoming a financial analyst since the skills are quite different.
The system then analyzes a large set of real-world career transitions to see in which direction these transitions typically go. Lastly, the system can recommend a career change that is likely to be successful and say what skills you may need to make it work .
The image below visualizes the similarity between Australian occupations in 2018 . Each marker shows an individual occupation, and the colors represent the risk each occupation faces due to automation over the next two decades (blue shows low risk and red shows high risk). Visibly similar occupations are closely grouped, with medical and highly skilled occupations facing the lowest risk of automation.
The occupational similarity measure is then taken and combined with a variety of other labor market variables, such as employment levels and educational requirements, to construct this job transition recommendation system . The full transition map is big and complicated, but you can see how it works below in a small version that only includes transitions between 20 occupations. On the map, the ‘source’ occupation is shown on the horizontal axis and the ‘target’ occupation on the vertical axis.
The system can also recommend skills that workers should develop to increase their chances of a successful transition . For example, for a ‘household cleaner’, the most recommended skills needed to transition to ‘elderly and disabled caregiver’ are specialized skills in patient care, such as ‘assisting with patient hygiene’.