Amazon scraps secret AI recruiting tool that showed bias against women
Amazon scraps secret AI recruiting tool that showed bias
against women
By Jeffrey Dastin OCTOBER 10, 2018 / 10:12 PM
SAN FRANCISCO (Reuters) - 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 programs since 2014
to review job applicants’ resumes with the aim of mechanizing the search for
top talent, five people familiar with the effort told Reuters.
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 realized its new system was not
rating candidates for software developer jobs and other technical posts in a
gender-neutral way.
That is because Amazon’s computer models were trained to
vet applicants by observing patterns in resumes submitted to the company over a
10-year 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 penalized 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 programs 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, which Reuters is first to
report, 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.
Some 55 percent of U.S. human resources managers said
artificial intelligence, or AI, would be a regular part of their work within
the next five years, according to a 2017 survey by talent software firm
CareerBuilder.
Employers have long dreamed of harnessing technology to
widen the hiring net and reduce reliance on subjective opinions of human
recruiters. But computer scientists such as Nihar Shah, who teaches machine
learning at Carnegie Mellon University, say there is still much work to do.
“How to ensure that the algorithm is fair, how to make
sure the algorithm is really interpretable and explainable - that’s still quite
far off,” he said.
MASCULINE LANGUAGE
Amazon’s experiment began at a pivotal moment for the
world’s largest online retailer. Machine learning was gaining traction in the
technology world, thanks to a surge in low-cost computing power. And Amazon’s
Human Resources department was about to embark on a hiring spree: Since June
2015, the company’s global headcount has more than tripled to 575,700 workers,
regulatory filings show.
So it set up a team in Amazon’s Edinburgh engineering hub
that grew to around a dozen people. Their goal was to develop AI that could
rapidly crawl the web and spot candidates worth recruiting, the people familiar
with the matter said.
The group created 500 computer models focused on specific
job functions and locations. They taught each to recognize some 50,000 terms
that showed up on past candidates’ resumes. The algorithms learned to assign
little significance to skills that were common across IT applicants, such as
the ability to write various computer codes, the people said.
Instead, the technology favored candidates who described
themselves using verbs more commonly found on male engineers’ resumes, such as
“executed” and “captured,” one person said.
Gender bias was not the only issue. Problems with the
data that underpinned the models’ judgments meant that unqualified candidates
were often recommended for all manner of jobs, the people said. With the
technology returning results almost at random, Amazon shut down the project,
they said.
THE PROBLEM, OR THE CURE?
Other companies are forging ahead, underscoring the
eagerness of employers to harness AI for hiring.
Kevin Parker, chief executive of HireVue, a startup near
Salt Lake City, said automation is helping firms look beyond the same
recruiting networks upon which they have long relied. His firm analyzes
candidates’ speech and facial expressions in video interviews to reduce
reliance on resumes.
“You weren’t going back to the same old places; you
weren’t going back to just Ivy League schools,” Parker said. His company’s
customers include Unilever PLC and Hilton.
Goldman Sachs has created its own resume analysis tool
that tries to match candidates with the division where they would be the “best
fit,” the company said.
Microsoft Corp’s LinkedIn, the world’s largest
professional network, has gone further. It offers employers algorithmic
rankings of candidates based on their fit for job postings on its site.
Still, John Jersin, vice president of LinkedIn Talent
Solutions, said the service is not a replacement for traditional recruiters.
“I certainly would not trust any AI system today to make
a hiring decision on its own,” he said. “The technology is just not ready yet.”
Some activists say they are concerned about transparency
in AI. The American Civil Liberties Union is currently challenging a law that
allows criminal prosecution of researchers and journalists who test hiring
websites’ algorithms for discrimination.
“We are increasingly focusing on algorithmic fairness as
an issue,” said Rachel Goodman, a staff attorney with the Racial Justice
Program at the ACLU.
Still, Goodman and other critics of AI acknowledged it
could be exceedingly difficult to sue an employer over automated hiring: Job
candidates might never know it was being used.
As for Amazon, the company managed to salvage some of
what it learned from its failed AI experiment. It now uses a “much-watered down
version” of the recruiting engine to help with some rudimentary chores,
including culling duplicate candidate profiles from databases, one of the
people familiar with the project said.
Another said a new team in Edinburgh has been formed to
give automated employment screening another try, this time with a focus on
diversity.
Reporting By Jeffrey Dastin in San Francisco; Editing by
Jonathan Weber and Marla Dickerson
Comments
Post a Comment