The Race Between Countries to Accumulate the Most Technically Skilled Work Force
According to a 2019 study by Indeed, machine learning (ML) engineer ranked #1 on the job site’s best jobs, with ML growing 344% between 2015 and 2018. A total of nine jobs in the tech realm were included on the list, with full-stack developer ranking #3, robotics engineer ranking #11 and data scientist ranking #22. With tech jobs in demand around the world, countries often find themselves in competition for the highest skilled workforce.
A Diffbot report from 2018 “identified more than 720,000 people skilled in machine learning across the globe,” writes Alison DeNisco Rayome for TechRepublic. The report also showed that 62% of machine learning graduates in China left for jobs in the United States.
The report lists the United States with the greatest concentration of skilled machine learning employees, with about 31% of the global share of the workforce. India, the United Kingdom, Canada, and China rounded out the list.
However, China has been more successful in raising funding for artificial intelligence (AI) startups, raising a half a billion dollars more than the US in 2017. The Chinese government has set a policy to become the world’s primary artificial intelligence innovator by 2030. To accomplish this goal, China will need employees knowledgeable in ML and AI.
The nature of machine learning work means that it is portable—employees can work on projects from anywhere. This also means that countries can bring in ML employees to fill gaps, such as microchip and semiconductor production. China has taken advantage of this by importing employees and business, particularly from Taiwan.
“All of China’s leading AI chip players are signed up with TSMC for production—Taiwan’s semiconductor prowess is China’s secret weapon in the coming semiconductor and AI chip wars,” reports Paul Triolo and Graham Webster for civic think tank New America. Taiwan Semiconductor Manufacturing Corporation (TSMC) is a leading producer of AI-optimized semiconductors.
However, many US firms have been doing this type of work for years, and there will be difficulties for China to make up that difference. The process of successfully developing and iterating complex hardware designed to run AI algorithms can be very difficult.
“It remains unclear if Chinese firms, including large and well-funded players such as Alibaba and Baidu can attract and keep sufficient numbers of design engineers to break into a significant market share for areas such as GPUs,” says Triolo and Webster.
As competition continues between the US and China, and as other countries enter into the mix, the need for employees skilled in machine learning, artificial intelligence, and other computer science fields is only going to increase.