The HR 4.0 revolution: Are AI-driven algorithms excluding qualified workers?
In this edition, we tell you how AI-driven software used by companies to help them recruit talents is actually having the opposite effect, increasing the number of "hidden workers". We speak to Harvard Professor Joseph Fuller about how these algorithms are eliminating candidates based on criteria disconnected from reality.
Nearly 75 percent of companies in the United States rely on some degree of automation to fill vacancies. They deploy AI-driven software to source candidates and manage the application process or perform background checks. The same trend is gaining ground in China, where first-time applicants are finding the process quite impersonal.
But according to a new Harvard Business School study, in the US, these AI-driven algorithms that sort through applicants are excluding as many as 10 million candidates from consideration, increasing the number of so-called "hidden workers". We speak to the author of the report, Harvard Business School management professor Joseph Fuller, about what can be done to correct AI bias.
Our tech editor Peter O'Brien also tells us why AI systems replicate and even exaggerate human biases.
In Test 24, we bring you a selection of gadgets designed in Benin, highlighting the city of Cotonou as it looks to become one of Africa's leading tech hubs.
We also show you three devices designed by Richard Odjrado, a tech entrepreneur and the creator of the AsWatch.
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