Automobile manufacturers, long-haul pilots, coal workers, salespeople in the store – many employees are forced to face the difficult and sometimes harrowing challenge of finding a new job quickly due to technological and economic change or crises such as the COVID19 pandemic.
To make the job change process easier and increase the chances of success, researchers at the University of Technology Sydney (UTS) and UNSW Sydney have developed a machine learning-based method that can identify and recommend jobs with similar underlying skills sets person current occupation.
The system can also respond in real time to changes in job demand and provide recommendations for the exact skills required to transition into a new profession.
PhD. Nicolas Dawson and Dr. Marian Andrei Risoyu from the Institute of Data Science, University of Technology Sydney and Professor Mary Anne Williams, Professor Michael J. Crouch Chair of Innovation at the University of New South Wales Business School, based on their new research results and skill-based recommendations” for job. Transitional Skills Pathways, published in the international journal PLOS On ONE.
Benefits Of Using AI To Find A Job?
Dr. Dawson says that while workplace changes are inevitable, if we can make the job change process easier and more efficient, there will be significant productivity and equity benefits not just for individuals, but for businesses and governments as well.
“Moving into a new career can be a daunting pro-position, especially for those who have been in the same job for a long time. Successful transitions generally involve workers using their existing skills and acquiring new skills to meet the needs of the company. “he said.
Professor Williams says the new referral system can help reduce inevitable stress in times of job loss by lowering the cost of job changes and providing evidence-based recommendations that better address the needs of people with special skills that often exceed their occupation.
“By focusing this new approach on skills rather than occupations, this new approach is helping workers, organizations and businesses like re-training advisory services, discovering the new skills a person would need to acquire in order to get a new job, and assessing the investment required in related training, ”she said.
“In addition, our skill similarity measure enables companies to design entirely new or hybrid occupations that increase the likelihood of finding people with the skills they need.
“In today’s rapidly changing job market, the need to continually improve skills a challenge for individuals & organizations. Our recommendation system can help people to embrace change by making their lifelong learning path and and respond to exciting new job opportunities as they arise by determining the next best skill you want to acquire.
Dr. Rizoiu added, “If we can move to a skills-based hiring rather than defining a job by job title, then we can help people identify the specific skills they need or need to develop in order to find productive and meaningful work .
How did the job search method develop?
The researchers used valuable data from Burning Glass Technologies, an analysis software company that provides real-time information on job & labor market trends, to study and analyze the basic skills of more than 8 million advertising jobs in Australia between 2012 & 2020.
They then compared the job change predictions with data from the Household, Income & Labor Dynamics in Australia (HILDA) survey, which followed participants throughout their lives, to validate those predictions with nearly 3,000 real-world examples.
The job recommendation system accurately predicted the likelihood of a job change and could also show whether it is easier to move in one direction than another.
The methods developed in the study can be used by educators, governments & companies, possibly with data from the Australian Bureau of Statistics, to support industries & sectors experience a great up-heaval to transitional workers at scale.
As part of the study, researchers also created an early warning indicator of new technologies (such as AI) that have the potential to change labor markets. This information could enable policymakers and companies to better prepare for future structural changes.
Dr. Dawson conducted the study as part of his PhD in Computational Economics at UTS with Professor Williams and Dr. Rizoiu and now works as a Senior Data Scientist at FutureFit AI, a company that works with industry and government to provide an AI-powered tool. to help employees with professional career transitions.
“When you look back in history, it’s almost never that automation means that there are fewer jobs, but rather that new jobs are created and old ones disappear at the same time as developing necessary skills and moving seamlessly into these new jobs,” said Dr. Dawson.
“The ability to obtain micro credentials in specific skill areas based on individual needs may be an important part of the future.
The findings were published in the Journal PLOS ONE.
