<?xml version="1.0" encoding="UTF-8"?>
<rss xmlns:npr="https://www.npr.org/rss/" xmlns:nprml="https://api.npr.org/nprml" xmlns:itunes="http://www.itunes.com/dtds/podcast-1.0.dtd" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:media="http://search.yahoo.com/mrss/" version="2.0">
  <channel>
    <title>NPR: algorithms</title>
    <link>https://www.npr.org/templates/story/story.php?storyId=177072836</link>
    <description>algorithms</description>
    <language>en</language>
    <copyright>Copyright 2024 NPR - For Personal Use Only</copyright>
    <generator>Story API Shim 1.2.24</generator>
    <lastBuildDate>Sun, 15 Jun 2025 00:25:23 -0400</lastBuildDate>
    <image>
      <url>https://media.npr.org/images/podcasts/primary/npr_generic_image_300.jpg?s=200</url>
      <title>NPR: algorithms</title>
      <link>https://www.npr.org/tags/177072836/algorithms</link>
    </image>
    <item>
      <title>COMIC: How a computer scientist fights bias in algorithms</title>
      <description>Computer scientist Joy Buolamwini is on a mission to fight bias in algorithms. In this comic, Buolamwini discusses the way biased algorithms can lead to real world inequality — and what we can do.</description>
      <pubDate>Mon, 14 Mar 2022 05:00:00 -0400</pubDate>
      <link>https://www.npr.org/2022/03/14/1085160422/computer-science-inequality-bias-algorithms-technology</link>
      <guid>https://www.npr.org/2022/03/14/1085160422/computer-science-inequality-bias-algorithms-technology</guid>
      <content:encoded><![CDATA[<img src='https://media.npr.org/assets/img/2022/03/08/joy04_custom-6e6cf272e8d9b45a897bfbb0713cd900a954b038.jpg' alt='undefined'/><p>Computer scientist Joy Buolamwini is on a mission to fight bias in algorithms. In this comic, Buolamwini discusses the way biased algorithms can lead to real world inequality — and what we can do.</p><img src='https://media.npr.org/include/images/tracking/npr-rss-pixel.png?story=1085160422' />]]></content:encoded>
      <dc:creator>Christina Cala</dc:creator>
    </item>
    <item>
      <title>Matchmaker, Matchmaker, Make Me An Algorithm: STEM Contest Winner Pairs Data</title>
      <description>The world of matchmaking won&apos;t have to rely on luck as much as math, thanks to Yunseo Choi. The 18-year-old came up with a matching theory that can be applied to people looking for a life partner.</description>
      <pubDate>Thu, 18 Mar 2021 14:11:33 -0400</pubDate>
      <link>https://www.npr.org/2021/03/18/978721494/matchmaker-matchmaker-make-me-an-algorithm-stem-contest-winner-pairs-data</link>
      <guid>https://www.npr.org/2021/03/18/978721494/matchmaker-matchmaker-make-me-an-algorithm-stem-contest-winner-pairs-data</guid>
      <content:encoded><![CDATA[<img src='https://media.npr.org/assets/img/2021/03/18/yunseo-choi-cb99144fdc69645b6e08aff8e5c74ac373c96b4d.jpg' alt='Yunseo Choi won first place Wednesday in this year's Regeneron Science Talent Search STEM competition.'/><p>The world of matchmaking won't have to rely on luck as much as math, thanks to Yunseo Choi. The 18-year-old came up with a matching theory that can be applied to people looking for a life partner.</p><img src='https://media.npr.org/include/images/tracking/npr-rss-pixel.png?story=978721494' />]]></content:encoded>
      <dc:creator>Reena Advani</dc:creator>
    </item>
    <item>
      <title>When Computers Collude</title>
      <description>Companies are increasingly using algorithms to set their prices, but is that giving them too much power over consumers?</description>
      <pubDate>Tue, 02 Apr 2019 07:30:20 -0400</pubDate>
      <link>https://www.npr.org/sections/money/2019/04/02/708876202/when-computers-collude</link>
      <guid>https://www.npr.org/sections/money/2019/04/02/708876202/when-computers-collude</guid>
      <content:encoded><![CDATA[<img src='https://media.npr.org/assets/img/2019/04/01/gettyimages-1072225648-afe3b3d939aebc71282619a3c749af5326f743f1.jpg' alt='undefined'/><p>Companies are increasingly using algorithms to set their prices, but is that giving them too much power over consumers?</p><img src='https://media.npr.org/include/images/tracking/npr-rss-pixel.png?story=708876202' />]]></content:encoded>
      <dc:creator>Greg Rosalsky</dc:creator>
    </item>
    <item>
      <title>Will Algorithms Erode Our Decision-Making Skills?</title>
      <description>The advancement of algorithms may result in the loss of human judgment, a new report says. Experts on the subject weigh the pros and cons of computer code that aims to make our lives easier.</description>
      <pubDate>Wed, 08 Feb 2017 17:11:00 -0500</pubDate>
      <link>https://www.npr.org/sections/alltechconsidered/2017/02/08/514120713/will-algorithms-erode-our-decision-making-skills</link>
      <guid>https://www.npr.org/sections/alltechconsidered/2017/02/08/514120713/will-algorithms-erode-our-decision-making-skills</guid>
      <content:encoded><![CDATA[<img src='https://media.npr.org/assets/img/2017/02/08/istock-450298579-edit_custom-1380a5c6d9042f6b9d632322a7107fc185f9ec7e.jpg' alt='undefined'/><p>The advancement of algorithms may result in the loss of human judgment, a new report says. Experts on the subject weigh the pros and cons of computer code that aims to make our lives easier.</p><img src='https://media.npr.org/include/images/tracking/npr-rss-pixel.png?story=514120713' />]]></content:encoded>
      <dc:creator>Cecilia Mazanec</dc:creator>
    </item>
    <item>
      <title>Building, And Losing, A Career On Facebook</title>
      <description>What a meme-maker and an investigative journalist teach us about the power of the Facebook empire, and how its opaque decisions harm real people.</description>
      <pubDate>Fri, 03 Feb 2017 11:50:00 -0500</pubDate>
      <link>https://www.npr.org/sections/alltechconsidered/2017/02/03/512473383/building-and-losing-a-career-on-facebook</link>
      <guid>https://www.npr.org/sections/alltechconsidered/2017/02/03/512473383/building-and-losing-a-career-on-facebook</guid>
      <content:encoded><![CDATA[<img src='https://media.npr.org/assets/img/2017/01/31/padula_npr_fb_finaledit_custom-a58912601ce6042d7376722a7d7f0561b394d173.jpg' alt='Facebook has become so powerful that, for some people, having a Facebook account is more important than a driver's license. But when you lose that account, there's no recourse.'/><p>What a meme-maker and an investigative journalist teach us about the power of the Facebook empire, and how its opaque decisions harm real people.</p><img src='https://media.npr.org/include/images/tracking/npr-rss-pixel.png?story=512473383' />]]></content:encoded>
      <dc:creator>Aarti Shahani</dc:creator>
    </item>
    <item>
      <title>Pundits Vs. Machine: Who Did Better At Predicting Campaign Controversies?</title>
      <description>We pitted two political pundits against an algorithm to compete at predicting the biggest issues to arise over a month in the presidential election. Now we find out who won.</description>
      <pubDate>Mon, 17 Oct 2016 17:40:00 -0400</pubDate>
      <link>https://www.npr.org/sections/alltechconsidered/2016/10/17/498280965/pundits-vs-machine-who-did-better-at-predicting-campaign-controversies</link>
      <guid>https://www.npr.org/sections/alltechconsidered/2016/10/17/498280965/pundits-vs-machine-who-did-better-at-predicting-campaign-controversies</guid>
      <content:encoded><![CDATA[<img src='https://media.npr.org/assets/img/2016/10/17/clinton_high_res_custom-e0e772ed04fa00f3282e451e9a8f784f9dcd3871.jpg' alt='Quid found 228,912 English-language stories in the news and on the blogs about Clinton's health between Sept. 12 and Oct. 12.'/><p>We pitted two political pundits against an algorithm to compete at predicting the biggest issues to arise over a month in the presidential election. Now we find out who won.</p><img src='https://media.npr.org/include/images/tracking/npr-rss-pixel.png?story=498280965' />]]></content:encoded>
      <dc:creator>Laura Sydell</dc:creator>
    </item>
    <item>
      <title>Pundits Vs. Machine: Predicting Controversies In The Presidential Race</title>
      <description>How well can a computer program predict which controversies around Hillary Clinton and Donald Trump are likely to re-emerge in the coming weeks? Two human pundits agree to compete against the machine.</description>
      <pubDate>Mon, 19 Sep 2016 16:57:00 -0400</pubDate>
      <link>https://www.npr.org/sections/alltechconsidered/2016/09/19/494279204/pundits-vs-machine-predicting-controversies-in-the-presidential-race</link>
      <guid>https://www.npr.org/sections/alltechconsidered/2016/09/19/494279204/pundits-vs-machine-predicting-controversies-in-the-presidential-race</guid>
      <content:encoded><![CDATA[<img src='https://media.npr.org/assets/img/2016/09/19/quid-screen-a14d63c225358eda056f28856fb6d6571f70e35d.png' alt='Quid, a data analytics firm, uses proprietary software to search, visualize and analyze text.'/><p>How well can a computer program predict which controversies around Hillary Clinton and Donald Trump are likely to re-emerge in the coming weeks? Two human pundits agree to compete against the machine.</p><img src='https://media.npr.org/include/images/tracking/npr-rss-pixel.png?story=494279204' />]]></content:encoded>
      <dc:creator>Laura Sydell</dc:creator>
    </item>
    <item>
      <title>In Effort To Curb Violence In Chicago, A Professor Mines Social Media</title>
      <description>Desmond Patton is studying how gangs in Chicago use social media to communicate. Now he is helping to create an algorithm to predict when a social media threat might spark real life violence.</description>
      <pubDate>Fri, 09 Sep 2016 18:04:00 -0400</pubDate>
      <link>https://www.npr.org/sections/alltechconsidered/2016/09/09/493319076/in-effort-to-curb-violence-in-chicago-a-professor-mines-social-media</link>
      <guid>https://www.npr.org/sections/alltechconsidered/2016/09/09/493319076/in-effort-to-curb-violence-in-chicago-a-professor-mines-social-media</guid>
      <content:encoded><![CDATA[<img src='https://media.npr.org/assets/img/2016/09/09/gettyimages-524310122_slide-dc306b1ff40904d7fd28d37c6583cb954654fa8d.jpg' alt='Police crime tape marks the scene where a 16-year-old boy was shot and killed and an 18-year-old man was wounded in April in Chicago. The grim milestone of 500 homicides already passed this year in Chicago.'/><p>Desmond Patton is studying how gangs in Chicago use social media to communicate. Now he is helping to create an algorithm to predict when a social media threat might spark real life violence.</p><p>(Image credit: Joshua Lott)</p><img src='https://media.npr.org/include/images/tracking/npr-rss-pixel.png?story=493319076' />]]></content:encoded>
      <dc:creator>NPR Staff</dc:creator>
    </item>
    <item>
      <title>He&apos;s Brilliant, She&apos;s Lovely: Teaching Computers To Be Less Sexist</title>
      <description>Algorithms teach computers how to process language. But because they draw on human writing, they have some biases. Researchers are trying to weed out those problematic associations.</description>
      <pubDate>Fri, 12 Aug 2016 08:01:12 -0400</pubDate>
      <link>https://www.npr.org/sections/alltechconsidered/2016/08/12/489507182/hes-brilliant-shes-lovely-teaching-computers-to-be-less-sexist</link>
      <guid>https://www.npr.org/sections/alltechconsidered/2016/08/12/489507182/hes-brilliant-shes-lovely-teaching-computers-to-be-less-sexist</guid>
      <content:encoded><![CDATA[<img src='https://media.npr.org/assets/img/2016/08/10/word-embeddings_custom-afbd9ff7b1bd8397c300380187e97f5e9069623e.jpg' alt='Words classified according to their gender, as the word embedding sees it. Words below the line are words that (generally) should be gendered, while words above the line are problematic if gendered.'/><p>Algorithms teach computers how to process language. But because they draw on human writing, they have some biases. Researchers are trying to weed out those problematic associations.</p><img src='https://media.npr.org/include/images/tracking/npr-rss-pixel.png?story=489507182' />]]></content:encoded>
      <dc:creator>Byrd Pinkerton</dc:creator>
    </item>
    <item>
      <title>The Reason Your Feed Became An Echo Chamber — And What To Do About It</title>
      <description>It often feels as if social media serve less as a bridge than an echo chamber, with algorithms that feed us information we already know and like. So, how do you break that loop? We ask some experts.</description>
      <pubDate>Sun, 24 Jul 2016 07:01:00 -0400</pubDate>
      <link>https://www.npr.org/sections/alltechconsidered/2016/07/24/486941582/the-reason-your-feed-became-an-echo-chamber-and-what-to-do-about-it</link>
      <guid>https://www.npr.org/sections/alltechconsidered/2016/07/24/486941582/the-reason-your-feed-became-an-echo-chamber-and-what-to-do-about-it</guid>
      <content:encoded><![CDATA[<img src='https://media.npr.org/assets/img/2016/07/23/gettyimages-520745029_mini-4779fd629b1f5b8d0e40bb91b47547429a2dd92f.jpg' alt='The algorithms that serve up what you like can often create closed loops of their own, packed only with people who agree with you already.'/><p>It often feels as if social media serve less as a bridge than an echo chamber, with algorithms that feed us information we already know and like. So, how do you break that loop? We ask some experts.</p><p>(Image credit: Hiroshi Watanabe)</p><img src='https://media.npr.org/include/images/tracking/npr-rss-pixel.png?story=486941582' />]]></content:encoded>
      <dc:creator>NPR Staff</dc:creator>
    </item>
  </channel>
</rss>