RPT-INSIGHT-Amazon scraps secret AI recruiting tool that showed bias against women

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    By Jeffrey Dastin
    SAN FRANCISCO, Oct 10 (Reuters) - 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
    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. (For a graphic on
gender breakdowns in tech, see:
    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.
    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.
    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
    "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
    "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)