The idea that automation and machine learning will take over all jobs by 2050 is over simplifying. A closer look at the impacts of Artificial Intelligence on human resources – including recruitment and monitoring performance – reveals a more complex picture.
Artificial Intelligence and Recruitment
The days of reading CV’s and covering letters before holding interviews will be revolutionised by AI-led candidate assessments. Job-seekers will be sifted by algorithms and face tests on things like problem-solving skills, creativity and how they respond to stress.
An early indication of how this could work can be seen in Catalyte, an Artificial Intelligence-driven employment platform. First conceived in the late 1990’s, founder Michael Rosenbaum saw the opportunity to utilise the internet and new tech. He wanted to find people with a natural ability, but lacked the means to train in software development.
The company started by developing a database to identify the aptitude of candidates, asking them questions designed not to count correct answers but to measure tenacity, grit and creativity under pressure.
This tech looks at factors such as whether candidates open multiple browsers or refer back to other questions to solve a problem. Rather than penalising candidates, it factors in this capacity to find alternate solutions to a problem they can’t solve alone.
Automation & Machine Learning
Machines will also change the type of jobs humans apply for, though hopes of early retirement might not come to fruition. “Automation and machine learning are more likely to radically change what people do in jobs, rather than replace work completely” says Ksenia Zheltoukhova, a Director at Nesta, the UK innovation foundation.
Beyond recruitment, algorithms are also giving bosses the ability to monitor and measure employees’ productivity.
Fabian Wallace-Stephens, a researcher in the Future Work Centre at the Royal Society for the encouragement of Arts, Manufactures and Commerce, says Artificial Intelligence is already used to allocate shifts and collect data to rate employees in lower-paid sectors in the same way passengers rate drivers on Uber.
“If you add wearable devices to measure individual performance, you start to get supercharged capitalism, powered by data.” he says.
He gives the example of the consumer retail app Percolata, which combines footfall sensors in stores with data on sales per employee to calculate the productivity of a shop worker, allowing managers to rank assistants and offer high-performing employees more shifts during peak hours.
As Artificial Intelligence infiltrates all corners of the world of work, Mr. Wallace-Stephens says people may come to realise that applicants and workers are worth more than just the measurable data they produce.