Design Of Hiring Algorithms Can Double Diversity In Firms

from Fast Company We know that algorithms can outperform humans across an expanding range of settings, from medical diagnosis and image recognition to crime prediction. However, an ongoing concern is the potential for automated approaches to codify existing human biases to the detriment of candidates from underrepresented groups. For example, hiring algorithms use information on workers they have previously hired in order to predict which job applicants they should now select. In many cases, relying on algorithms that predict future success based on past success will lead firms to favor applicants from groups that have traditionally been successful. But this […]

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Supposedly ‘Fair’ Algorithms Can Perpetuate Discrimination

from Wired DURING THE LONG Hot Summer of 1967, race riots erupted across the United States. The 159 riots—or rebellions, depending on which side you took—were mostly clashes between the police and African Americans living in poor urban neighborhoods. The disrepair of these neighborhoods before the riots began and the difficulty in repairing them afterward was attributed to something called redlining, an insurance-company term for drawing a red line on a map around parts of a city deemed too risky to insure. In an attempt to improve recovery from the riots and to address the role redlining may have played in […]

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Report: Amazon’s AI Recruiter Favored Men

from Axios An algorithmic recruiter meant to help Amazon find top talent was systematically biased against women, a Reuters investigation found. Why it matters: This is a textbook example of algorithmic bias. By learning from and emulating human behavior, a machine ended up as prejudiced as the people it replaced. The details: Amazon’s experiment, which dates back to 2014, was trained on 10 years of job applications, most of which came from men, reports Reuters’ Jeffrey Dastin. * The system concluded that men were better candidates for technical jobs. * In 2015, Amazon began to realize that the system was […]

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When Traveling, Avoid The Algorithmic Trap

from kottke In a piece called The Algorithmic Trap, David Perell writes about the difficulty of finding serendipity, diversity, and “real” experiences while traveling. In short, Google, Yelp, Instagram, and the like have made travel destinations and experiences increasingly predictable and homogeneous. Call me old-fashioned, but the more I travel, the less I depend on algorithms. In a world obsessed with efficiency, I find myself adding friction to my travel experience. I’ve shifted away from digital recommendations, and towards human ones. For all the buzz about landmarks and sightseeing, I find that immersive, local experiences reveal the surprising, culturally-specific ways […]

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YouTube, the Great Radicalizer

from NYTs At one point during the 2016 presidential election campaign, I watched a bunch of videos of Donald Trump rallies on YouTube. I was writing an article about his appeal to his voter base and wanted to confirm a few quotations. Soon I noticed something peculiar. YouTube started to recommend and “autoplay” videos for me that featured white supremacist rants, Holocaust denials and other disturbing content. Since I was not in the habit of watching extreme right-wing fare on YouTube, I was curious whether this was an exclusively right-wing phenomenon. So I created another YouTube account and started watching […]

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Our Hackable Political Future

from NYTs Imagine it is the spring of 2019. A bottom-feeding website, perhaps tied to Russia, “surfaces” video of a sex scene starring an 18-year-old Kirsten Gillibrand. It is soon debunked as a fake, the product of a user-friendly video application that employs generative adversarial network technology to convincingly swap out one face for another. It is the summer of 2019, and the story, predictably, has stuck around — part talk-show joke, part right-wing talking point. “It’s news,” political journalists say in their own defense. “People are talking about it. How can we not?” Then it is fall. The junior […]

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But Where Did The Algorithm Come From?

from Seth’s Blog Imagine if the owner of the local bookstore hid books from various authors or publishers. They’re on the shelf, sure, but misfiled, or hidden behind other books. Most of us would find this offensive, and I for one like the freedom I have (for now) to choose a new store, one that connects me to what I need. The airline tickets I purchased last week are missing. Oh, here they are, in my spam folder. Gmail blames an algorithm, as if it wrote itself.  That person who just got stopped on her way to an airplane—the woman who gets […]

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Facebook Is Watching And Tracking You More Than You Probably Realize

from USAToday Whenever you’re on Facebook, do you ever get the feeling that you’re being watched? An ad pops up that’s right up your alley, or three new articles show up in your feed that are similar to something you’ve just clicked on. Sometimes it seems like Facebook knows you personally, and that’s because it does. It has algorithms that track what you like, watch and click on. Facebook uses this information to target ads to users on behalf of advertisers. Facebook itself isn’t the only culprit. Tons of companies use Facebook’s platform as a way to track you. In fact, […]

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