Why recruiting algorithms are counterproductive
Audio 04:01
Jobs have been cut in the United States and more and more unemployed people are looking for work, as here at a Workforce Alliance center in Palm Beach, Fla. (Illustration) (Photo: Reuters)
By: Dominique Baillard Follow
8 mins
Millions of Americans are still unemployed as employers struggle to find staff.
The excessive use of recruitment algorithms would partly explain this paradoxical situation.
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The cause most often cited in public opinion places the blame on job seekers. If Americans are still unemployed while the economy is picking up, it is because their compensation, improved during the pandemic, dissuades them from looking for a job. A thesis that will no longer be valid since from today the boost granted by the State in spring 2020 is deleted. Many households will find themselves short of income, but this will not necessarily bring them back to work any faster. Because according to a study published this weekend by Harvard Business School in partnership with Accenture, millions of jobs remain vacant, not for lack of candidates, but especially because of the algorithms massively used today to recruit .
These tools are supposed to facilitate hiring
The use of artificial intelligence has made it possible to automate the process.
No need to spend days and days reading thousands of CVs, the algorithm takes care of it: it does a first sorting by scanning them instead of human resources managers.
It's much faster, so it's cheaper.
There are also video interviews, games that are made with the assistance of intelligent machines to decipher the behavior and qualities of a candidate.
These new tools appeared in the 1990s and are booming today.
4 in 10 American companies use them, especially those that hire heavily.
The confinement, restricting meetings a little more, has also accelerated this trend.
How do these algorithms hinder recruitment?
Employers are increasing the demands, which leads the machine to make a frenzied selection. A frequent example: the algorithm favors those who are already in employment to the detriment of all those who have too long periods without employment, without taking into account the cause of this parenthesis. This effectively eliminates, for example, women who have given up their work to take care of their children, or those who have accompanied their husbands abroad, army veterans, or even those who work in part-time. At a time when candidates are scarce, the company must on the contrary move away from these ultra-selective criteria in order to detect especially those who have the required skills. But the algorithms do not yet know how to test the competence: they are content to sort according to the school level, which, again,excludes millions of potential candidates.
Do Employers Trust Algorithms Too Much?
They are sometimes deceived by these new tools. And too complacent: few of them check the quality of their recruitment process. They know it: according to the Harvard Business School study, 9 out of 10 agree that these tools prevent them from finding the right candidate. Employers tired of not finding the expected workforce are starting to review their use of this software. Some, like Amazon, have adapted them to their needs, others are revising the criteria: the bank JPMorgan Chase, for example, has given up on discriminating against convicted persons, preferring to let its security service decide at the final stage of recruitment. And then others return to the good old human methods. As for job seekers systematically excluded from offers processed by algorithms,they try other strategies, preferring recommendations and word of mouth to get a job.
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Employment and Work
United States