Typical Australians will change careers 5-7 times According to some estimates, during their professional life. And this could increase as new technologies automate labor, move production abroad, and the economic crisis strikes.
Losing work isn’t a new phenomenon – have you seen an elevator operator lately? – However, the pace of change is accelerating and can unemploy and unemploy a large number of workers.
New technologies also create new jobs, but the skills they need do not always match old jobs. To successfully move between jobs, you need to make the most of your current skills to acquire new skills, but if the gap between your old and new skills is too large, these transitions can fail. there is.
By using machine learning to analyze over 8 million online classified ads to see what moves are likely to succeed, we have built a system that encourages career transitions.Detail is Release At PLOS ONE.
Our system begins by measuring the similarity between the skills required for each profession. For example, an accountant can be a financial analyst because of the similar skills required, but a speech therapist may find it difficult to be a financial analyst because of a completely different skill set. ..
Next, we looked at a large set of real-world carrier transitions to see in which direction these transitions usually go. Accountants are more likely to be financial analysts than vice versa.
Finally, our system recommends career changes that are likely to be successful and teaches you the skills needed to make them work.
Measure occupational similarity
Our system uses indicators that economists call “apparently comparative advantage” (RCA) to use 2018 online classified ads to identify how important individual skills are to the job. increase. The map below visualizes the similarity of the top 500 skills. Each marker represents an individual skill, colored according to one of 13 clusters of very similar skills.
Once you know how similar different skills are, you can estimate how similar different professions are based on the skills you need. The figure below visualizes the similarities between Australian occupations in 2018.
Each marker indicates an individual profession, and the color indicates the risk that each profession faces over the next 20 years of automation (blue indicates low risk, red indicates high risk). Visibly similar occupations are closely grouped, with medical and highly skilled occupations facing the lowest automation risk.
We then measured occupational similarities and combined them with various other labor market variables such as employment levels and educational requirements to build a career change recommender system.
Our system uses machine learning technology to “learn” from past actual work transitions and predict future work behavior. Not only does it achieve a high level of accuracy (76%), it also considers asymmetry between job migrations. Performance is measured by how accurately the system predicts if a migration has occurred when applied to a migration of past jobs.
The complete transition map is large and complex, but in a smaller version that contains only transitions between 20 professions, you can see how it works below. In the map, the horizontal axis shows the “source” occupation and the vertical axis shows the “target” occupation.
Looking at a particular profession at the bottom of the map, the square column shows the probability of moving from that profession to the profession listed on the right. The darker the square, the more likely it is to transition.
Recommendations for work that utilizes artificial intelligence
You may need to develop new skills in a new career, which skill? Our system helps identify them. Let’s take a look at how it works with “household cleaners”, a profession whose employment has dropped significantly during COVID-19 in Australia.
First, use the migration map to see which occupations household cleaners are most likely to migrate to. Colors divide occupations by status during the COVID-19 crisis. The blue profession is a “mandatory” job that allows you to continue working during the blockade, and the red is a “non-mandatory” job.
Identify the top recommended occupations, sorted in descending order of transition probabilities, as shown on the right side of the flow diagram (bottom half of the image). The width of each band in the figure shows the number of openings available in each profession. The color of the segment indicates whether demand has increased or decreased compared to the same period in 2019 (before COVID).
The first six migration recommendations for all are “non-essential” services and, of course, are experiencing a decline in demand. However, the seventh was “caregivers for the elderly and disabled”, which was classified as “essential” and demand increased significantly at the beginning of the COVID-19 period.
In this example, we select “caregivers for the elderly and disabled” as the target profession, as it is more likely that you will find a job if you move to a more demanding profession.
What skills to develop for a new profession
Our system can also recommend the skills that workers need to develop to increase the chances of a successful migration. We argue that workers are of paramount importance to their new profession and should invest in the development of skills that differ most from the skills they currently have.
For “domestic cleaners”, the most recommended skills needed to transition to “caregivers for the elderly and disabled” are specialized patient care skills such as “patient hygiene support”.
On the other hand, there is less need to develop skills that are not important or that are very similar to those in the current profession. Skills such as “business analysis” and “finance” should not be prioritized as they are less important to “caregivers of the elderly and disabled”. Similarly, new jobs require skills such as “ironing” and “laundry”, but “household cleaners” may already have (or are easy to learn) these skills.
Benefits of smoother job migration
The future of work remains uncertain, but change is inevitable. New technologies, economic crises and other factors will continue to shift labor demand, causing workers to move between jobs.
Efficient workforce migration has great productivity and fairness benefits for everyone. If the migration is slow or unsuccessful, it can be very costly to both the individual and the state and the individual. The methods and systems proposed here have the potential to significantly improve the achievement of these goals.
We would like to thank Bledi Taska and Davor Miskulin of Burning Glass Technologies for generously providing classified advertising data for this research and valuable feedback. We would also like to thank Stijn Broecke of the OECD and other colleagues for the ongoing input and guidance in developing this work.
This article Nick Dawson, Honorary scholar, Council of Technology Sydney; Marian Andrey Resoiu, Computer science instructor, Council of Technology Sydney, When Mary Ann Williams, Michael J Crouch Chair in Innovation, UNSWWill be reissued from conversation Under a Creative Commons license.read Original work..
https://thenextweb.com/news/how-ai-can-help-choose-next-career-stay-ahead-automation-syndication How AI can help you choose your next career and stay ahead of automation