AI helps job seekers proofread resumes

Opinion
AI helps job seekers proofread resumes

Job seekers have a better chance of landing a job if they run their resumes through an artificial intelligence (AI) service first, according to a new study.

Candidates who tapped into AI to fix spelling and grammar errors on their resumes had an 8% increase in the probability of getting hired, according to an MIT working paper that fielded the experiment with nearly a half-million job seekers.

The workers who had AI help also had 7,8% more job offers over the experimental period than those in the control group, according to the findings, and their hourly wages were 8,4% higher.

“This could be employers interpreting better writing as a signal of workers’ attention to detail or effort level,” said Emma van Inwegen, who conducted the study along with Zanele Munyikwa and John J Horton. “Or better writing could simply make it easier for employers to understand the skills a worker has and their ability to do the job at hand.”

The findings could help counteract the prevailing AI problem that jobseekers regularly face — employers that use AI tools to pare down online job applicants, often ghosting qualified candidates.

“If AI can help in that first step — and the MIT research seems to show it can help to some degree — then bravo,” Ramona Schindelheim, WorkingNation editor-in-chief, told Yahoo Finance. “Removing that barrier opens the door to at least being taken seriously.”

 Employees who communicate well

The new research makes the case that AI can be your friend when it comes to polishing up your resume. It bears repeating because it happens all the time — your resume must be error-free.

“Whether it is written directly by a job seeker or written with the help of an AI programme, it comes down to this: Employers put a premium on employees who communicate well and show attention to detail,” Schindelheim said. “Mistakes in grammar, capitalisation, or spelling, or misuse of like-sounding words — there, their, or they’re — sends a signal to the hiring manager. It often derails the job seeker’s chances of advancing to the interview stage.”

For the MIT study, the resume help was provided by a company the researchers call the “Algorithmic Writing Company,” which offered suggestions on how to improve writing, not simply spelling corrections.

Words and phrases which are spelled wrong or used incorrectly are underlined by the Algorithmic Writing Service. By hovering a mouse cursor over the underlined word or phrase, the user could see suggestions for fixing spelling and grammar errors, the researchers explained.

The tool also offered recommendations on punctuation, word usage, phrase over-use, and other factors related to "clarity, engagement, tone, and style,” according to the researchers. The feedback, for instance, points out if a phrase is “a bit bland” or “unclear,” or if the delivery “slightly off,” according to the report.

“Our results suggest that giving workers the option to let an algorithm make their writing better helps them to more clearly describe their abilities,” van Inwegen said. “This is tremendously useful for people applying to English-language jobs for whom English is not their first language. Using this algorithmic writing assistance could help to put them on more equal footing with native English speakers, without changing the quality of work that gets done.”

What the AI doesn’t do is help ill-suited candidates get a job. Helping jobseekers have better-looking resumes helped them get hired, but the researchers found no evidence that employers were later disappointed.

“The main surprise was I was expecting that the algorithmic writing assistance was causing some people to get hired that otherwise wouldn't have been hired, in a way tricking employers into hiring someone worse in the skills to do the job just because they had quality writing ability,” van Inwegen said.

That didn’t happen, she said.

An inevitable consequence

Roughly 9 of 10 executives surveyed said they know the software they use stops them from seeing potentially great candidates, according to a Harvard study. (Getty Creative)

AI is not new to the hiring process. It’s just usually utilised on the employer side, often to job seekers’ detriment.

The most widely used AI tool, the automated-hiring technology known as Applicant Tracking Systems (ATS), has been calibrated to cull out the droves of applications and resumes employers often receive electronically for a single open position.

More than 90% of employers surveyed use this screening to filter or rank potential candidates, according to a study by Harvard Business School's Project on Managing the Future of Work and the consulting firm Accenture of 8,000 workers and more than 2,250 executives.

But it’s not a perfect system. For example, one factor that causes ATS to spit out applications: gaps in a resumé. That's a problem for many family caregivers who left the workforce during the pandemic because of caregiving duties.

Nearly nine out of 10 US workers surveyed said they believe employers' hiring practices discarded their applications when they could successfully perform the jobs they applied for but didn't fit the exact criteria in the job descriptions.

Employers know what’s up, too

Roughly 9 of 10 executives surveyed said they know the software they use stops them from seeing potentially great candidates. According to the study, this practice results in more than 10 million workers from even being asked to interview with a human being.

It’s no wonder that some job applicants might seek a bit of AI help themselves.

“The development of AI tools to assist applicants is an inevitable consequence of the use of AI to evaluate and screen candidates,” Joseph B. Fuller, a professor of management practice at Harvard Business School, co-author of the report, and co-head of the Managing the Future of Work Project, told Yahoo Finance.

“As AI comes within reach of people broadly, employers will have to revisit the efficacy of the ATS systems in ranking candidates,” he said. “This may speed the deployment of machine learning and data engines to make much more refined choices, as bigger and bigger data sets about skills requirements, credentials, and career paths become available.”

Hannon  is a senior reporter and columnist at Yahoo Finance. — Twitter @kerryhannon.

 

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