It was inevitable: When
companies made it simple to apply for a job online, applications poured in. To
wade through this ever-rising tide of resumes, human resources departments are
increasingly turning to artificial intelligence systems to pluck out the
candidates deemed to be good fits. So while applying may be as easy as a mouse
click, that resume is much more likely to be screened out into oblivion than
end up in front of a recruiter.
اضافة اعلان
To avoid getting caught by the resume sifter, job
seekers should understand the new systems, which have been spreading to more
industries and positions.
How it works
So-called predictive hiring tools evaluate resumes
by finding keywords related to categories like skills, experience and
education, and weighting them according to the job requirements and any other
factors the hiring company has specified. The system may weight applicants who
have worked at certain companies more positively. It may infer how old a skill
seems to be from where it appears in a job history.
Artificial intelligence is used to understand what
people mean to say — for example, if Carleton is a person’s name, an alma mater
or a company the applicant worked for.
The software systems can be less biased than human
screeners because they can be programmed to ignore characteristics like age,
sex, race and other protected categories.
Giving yourself the best shot
Making it through the automated screening can
require tailoring your resume, not just the cover letter, to each job you are
applying for. Greg Moran, chief executive of OutMatch, a system that screens
more than 10 million applicants a year for companies including Pepsi, Toyota
and Walmart, confirmed that the following actions would help applicants avoid
an automated rejection.
Include in your resume the same keywords, or
similar ones, that the job posting uses for the knowledge, skills, experience
and duties involved. Use the most relevant keywords in your most recent job
listed. If you mention data analytics in a job 10 years ago but not in more
recent work, the algorithm may give it less weight.
Words like “significant,” “strong” and “mastery”
in a job description can be clues that those skills will be weighted heavily,
so they should be emphasized in your resume and included on your descriptions
of your more current experience.
Quantify wherever possible.
“Managed a team of five that increased sales by 40
percent over two years” works better than “Managed a team that significantly
increased sales.”
Make sure the system can “read” your resume. In
some systems, the PDF file format can make your resume appear as a single
image, so Microsoft Word may be a better choice. Fancy formatting like columns
or added images can be less readable if the system is scanning left to right. Don’t
try to trick the software with keywords in white text — the creators have
already thought of that.
Mention all your skills. The system may scan for
specific experience with, for example, the programming language R or Tableau,
so don’t lump them together as “experienced in data analytics.”
If you are part of an underrepresented group, use
terms that will let the system identify you to companies that are trying to
diversify their workforce.
Pitfalls
The artificial intelligence used by hiring systems
can generate unintended harmful consequences, said Hong Qu, a race and
technology fellow at Stanford. He is a creator of AI Blindspot, a set of
practices that help software development teams recognize unconscious biases and
structural inequalities that could affect their software’s decision-making.
“The systems can still have their own forms of
biases and may screen out qualified applicants,” Qu said.
A company may put a priority on the resumes of
software engineer applicants who went to the same universities as successful
senior engineers in the industry. Applicants from women’s or historically Black
colleges may be more likely to be rejected, for example, if the upper ranks of
engineers in an industry are predominantly white men.
“Getting the system right is more than debugging
code and de-biasing training data, because the software is based on
values-driven decisions with historical baggage,” Qu said.
Biases engendered by the system can extend beyond
screening. For example, recruiters can be subject to “automation bias,” giving
an analysis more weight because it came from a computer system. Pooling
candidates who have all made it through the screening for their next level of
evaluation, rather than ranking them by scores bestowed by the software, can help
alleviate this effect.
Frequent audits are needed to understand whom the
system is screening in — and out. It also needs to be designed with
transparency, so humans can understand why any individual decision was made. An
opaque system makes it hard to discover problems, Qu said.
While the systems are becoming more widespread,
they are nascent, and critics say there is little market incentive or
government regulation demanding transparency. In fact, self-examination can
unearth problems that may harm a company’s reputation.
More than your resume
Increasingly, the one-click resume drop-off is
just the first step. More candidates are being asked to take skill and
personality assessments and record answers to interview questions. OutMatch’s
Moran said the additional tasks aimed to give a more complete picture to hiring
managers and let applicants “tell their story.”
Still, most applicants who are asked to submit
extra information won’t have the chance to tell that story to a human. While
percentages vary, Moran estimated that a system might typically deem 80 percent
of candidates who submitted a resume for an entry-level professional job to
have the basic skills and competency to succeed in the role, leading them to be
asked to complete one or more tests. Most test takers will then be asked to
record a video interview.
The information from the resume, the tests and a
transcript of the interview will be reviewed by artificial intelligence
software. About 20 percent of those candidates will then speak to a recruiter.
Karin Borchert, the chief executive of the hiring
software company Modern Hire, predicts that resumes will become less important
for entry-level professional jobs. Companies can evaluate qualities they are
seeking, such as tenacity or problem-solving skills, through assessments and
then incorporate feedback on new hires to improve those assessments, she said.
Don’t neglect your other tools
Moran cautioned applicants not to rely on the new
systems alone to secure a job. He advises job seekers to make sure their
LinkedIn profile is up to date and includes recommendations from managers and
colleagues. Twitter or other public social media accounts should include
“digital bread crumbs” of information highlighting skills, experience and
interests.
Candidates should also seek out people inside
their target companies that can refer them for the position, Moran said,
because those referrals can significantly lift the chance of being hired.
“The more technical things get, the more you can
get noticed by going old school,” he said.
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