Amazon scraps gender-biased secret AI recruiting tool
SAN FRANCISCO: Amazon.com Inc’s machine-learning specialists uncovered a big problem: their new recruiting engine did not like women.
The team had been building computer programmes since 2014 to review job applicants’ resumes with the aim of mechanising the search for top talent, five people familiar with the effort said.
Automation has been key to Amazon’s e-commerce dominance, be it inside warehouses or driving pricing decisions. The company’s experimental hiring tool used artificial intelligence to give job candidates scores ranging from one to five stars — much like shoppers rate products on Amazon, some of the people said.
“Everyone wanted this holy grail,” one of the people said. “They literally wanted it to be an engine where I’m going to give you 100 resumes, it will spit out the top five, and we’ll hire those.”
But by 2015, the company realised its new system was not rating candidates for software developer jobs and other technical posts in a genderneutral way.
That is because Amazon’s computer models were trained to vet applicants by observing patterns in resumes submitted to the company over a 10year period. Most came from men, a reflection of male dominance across the tech industry.
In effect, Amazon’s system taught itself that male candidates were preferable. It penalised resumes that included the word “women’s,” as in “women’s chess club captain.”
And it downgraded graduates of two all-women’s colleges, according to people familiar with the matter. They did not specify the names of the schools.
Amazon edited the programmes to make them neutral to these particular terms. But that was no guarantee that the machines would not devise other ways of sorting candidates that could prove discriminatory, the people said.
The Seattle company ultimately disbanded the team by the start of last year because executives lost hope for the project, according to the people, who spoke on condition of anonymity. Amazon’s recruiters looked at the recommendations generated by the tool when searching for new hires, but never relied solely on those rankings, they said.
Amazon declined to comment on the recruiting engine or its challenges, but the company says it is committed to workplace diversity and equality.
The company’s experiment offers a case study in the limitations of machine learning. It also serves as a lesson to the growing list of large companies including Hilton Worldwide Holdings Inc and Goldman Sachs Group Inc that are looking to automate portions of the hiring process.