Now Algorithms Are Deciding Whom To Hire, Based On Voice : All Tech Considered If you're trying out for a job, the one judging you may not be a person — it could be a computer. Algorithms are evaluating human voices to determine which ones are engaging, calming and trustworthy.

Now Algorithms Are Deciding Whom To Hire, Based On Voice

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And now, All Tech Considered.


SIEGEL: If you apply for certain jobs, the way you present yourself - how you sound - may be considered. And soon in some industries, computers may be making that consideration. Job recruitment is the newest frontier where algorithms are choosing who's the right fit to sell food or handle angry cable customers. NPR's Aarti Shahani reports.

AARTI SHAHANI, BYLINE: Let's take a voice you know and play a few samples of it. Clip number one...


AL PACINO: (As Don Michael Corleone) My offer is this - nothing. Not even the fee for the gaming license.

SHAHANI: Clip two...


PACINO: (As John Milton) He gives you this extraordinary gift and then what does he do? I swear, for his own amusement...

SHAHANI: And number three...


PACINO: (As Tony Montana) I'd kill a communist for fun, but for a green card, I'm going to carve him up real nice.

SHAHANI: This is Al Pacino in "The Godfather," in "Devil's Advocate" and in "Scarface" - three different characters, three different accents at different ages. The movies were years apart. But in every version, Pacino's voice has a biological, inescapable fact.

LUIS SALAZAR: His tone of voice is - generates engagement, emotional engagement with the audiences.

SHAHANI: Luis Salazar is CEO of Jobaline.

SALAZAR: It doesn't matter if you're screaming or not. That voice is engaging for the average American.

SHAHANI: Years and years of scientific studies and focus groups have dissected the human voice and categorized the key of emotions of the person speaking. Jobaline has taken that research and fed it into algorithms that interpret how a voice makes others feel and cross-checks its judgment with real human listeners.

SALAZAR: We're not analyzing how the speaker feels. That's irrelevant.

SHAHANI: Regardless of whether you're happy or sad, cracking jokes, your voice has a hidden, complicated architecture with that intrinsic signature, much like a fingerprint. And through trial and error, the algorithms can get better at predicting how things like energy and fundamental frequency impact others, be they people watching a movie or cancer patients calling a help line.

SALAZAR: What is the emotion that that voice is going to generate on the listener?

SHAHANI: So far, Salazar says, the Jobaline secret formula can pinpoint if a voice is engaging, calming and/or trustworthy. And note - it's not a lie detector test. You could be a big liar, but just sound like someone honest. Salazar plays me a clip of a woman applying for a job.


UNIDENTIFIED WOMAN: So one person that motivates me every day is my son because I'm trying to make a better life for him.

SALAZAR: So this is an answer to this - question what motivates you?

SHAHANI: Big companies pay Jobaline to help them sift through thousands of applications to find the right workers for their hourly jobs. The startup says it's processed over half a million voices for hotel receptionists, call-center staff.

SALAZAR: In the hospitality industry, in the retail industry, you want people engaged. The average span of attention these days is four seconds. In four...

SHAHANI: I'm sorry, can you repeat that?

SALAZAR: (Laughter).

SHAHANI: And the benefit isn't just efficiency, cutting costs. We humans can get tired by the time applicant number 25 comes through the door. We can discriminate. But algorithms have stamina, and they do not factor in things like age, race, gender, sexual orientation.

SALAZAR: Correct. Math is blind, basically, right? That's the beauty of math - it's blind.

SHAHANI: Now, of course, as a woman who's built a career on talking, I'm curious what the algorithms have to say about me. My friends say I've got two voices - the inviting, empathetic hey, how-you-doing, come-on-over voice, and the don't-mess-with-me, I'm-getting-work-done voice. Salazar ventures to guess the intrinsic quality.

SALAZAR: I'll say it's engaging and trustworthy. I don't think it will make the bar for calming, (laughter) but we'll see.

SHAHANI: The algorithms agree. They say with 95 percent certainty that my voice is engaging to three-quarters of Americans, so I'm a good fit for radio.


That was NPR's Aarti Shahani, who was hired by humans, not algorithms. And we'd like to see what the algorithms have to say about you. NPR's tech team is collecting vocal samples. Go to to submit your voice clip.

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