In last year’s World Economic Forum (WEF) Annual Meeting, one of the major themes that emerged from the discussions was the future of work. Davos experts were particularly keen on the influence of artificial intelligence (AI) and machine learning (ML) on today’s shifting employment landscape.
IBM chief executive Ginni Rometty stated that the hiring model that companies still use needs to evolve as automation spreads into new industries. Rometty called for new education and job models to develop a new breed of workers who can mitigate the current skills gap.
LinkedIn co-founder Allen Blue, meanwhile, focused on the role of women in training ML systems. Blue stressed the importance of female AI designers after many algorithms demonstrated biases in test environments.
New Job Creation and Displacement
The points above represent the main concerns that most movers and shakers have about AI. People will hear more of them in the wake of new job market forecasts.
A previous WEF report reveals that AI will create 133 million new positions by 2022, but would have to displace 75 million workers for lack of related skills. Do the math, and you’ll get 58 million new jobs.
At the rate automation is going, these forecasts could very well become a reality. WEF data shows that in 2018, the division of labor between humans and machines are still pretty much in the normal range. In three years’ time, however, this will all change with human labor slipping down from 71% to 58%.
By contrast, machine “labor hours” will jump from 29% in 2018 to 42% by 2022. In 2025, machines will be performing 52% of the work compared to humans whose share will decline to 48%.
3 New Jobs Requiring AI-Relevant Skills
While it’s true that some people will be displaced due to AI, opportunities await those who are willing to adapt. These jobs, for instance, have resulted from AI advancements:
- Business Intelligence Analysts
One post with a low barrier to entry is that of a business intelligence analyst. Business intelligence specialists or engineers analyze data sets to improve a company’s operations or marketing efforts.
The job description for this position may vary depending on the company. Some may focus solely on marketing analytics, which may not require coding skills, while others may require technical skills for data visualization and modeling.
Skills required: Entry-level positions may require some knowledge in using popular data analytics platforms and handling statistical data. Engineers are usually required to demonstrate some expertise in SQL.
Salary estimate: The average annual salary for this job is US$100,984 annually in the U.S. The figure could go higher or lower, depending on the worker’s location.
- Chabot Copywriters
Chatbot copywriters write the response chatbots provide. The job made it to this list because its barrier to entry is relatively low. Writers and marketing professionals, for instance, can easily do chatbot copywriting as a side gig or a primary job.
Skills required: This job requires basic writing skills and an understanding of how marketing and AI work. People with a business or communications degree would do well in this post.
Salary estimate: The full-time salary for this position starts at US$42,000 a year. We found this rate consistent in other countries as well. The rate could go higher in tech workplaces than in digital marketing companies.
- ML Engineers
ML engineers are on the other end of the spectrum, as the position has the highest barrier to entry among the three. The job is also the most in-demand. ML engineers are programmers with a background in data science and ML. They create and implement ML algorithms using programming languages, such as Python, C++, Java, and Javascript, to name a few.
Skills required: As mentioned, ML engineers should possess in-depth experience in programming. As their work overlaps with those of software engineers and data scientists, they must demonstrate all-around knowledge of hardware and software engineering.
Salary estimate: The average yearly salary for ML engineers is US$121,488. This rate could vary depending on the state and industry. The finance industry offers higher rates for ML engineers.
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These are just some of the jobs that came up on our radar. More jobs, for sure, will crop up as we inch forward into the new year. In the meantime, let’s keep our fingers crossed that business and institutional leaders are working on helping displaced workers find new jobs. Hopefully, more people will gain access to AI training resources so they can maintain their edge in today’s workforce.