{"id":66182,"date":"2019-02-13T09:37:08","date_gmt":"2019-02-13T14:37:08","guid":{"rendered":"http:\/\/danielschristian.com\/learning-ecosystems\/?p=66182"},"modified":"2019-02-13T09:37:08","modified_gmt":"2019-02-13T14:37:08","slug":"the-real-reason-tech-struggles-with-algorithmic-bias-eisenstat","status":"publish","type":"post","link":"https:\/\/danielschristian.com\/learning-ecosystems\/2019\/02\/13\/the-real-reason-tech-struggles-with-algorithmic-bias-eisenstat\/","title":{"rendered":"The real reason tech struggles with algorithmic bias [Eisenstat]"},"content":{"rendered":"<p><a href=\"https:\/\/www.wired.com\/story\/the-real-reason-tech-struggles-with-algorithmic-bias\/\" target=\"_blank\" rel=\"noopener\"><strong>The real reason tech struggles with algorithmic bias<\/strong><\/a> &#8212; from wired.com by Yael Eisenstat<\/p>\n<p><em>Excerpts:<\/em><\/p>\n<p style=\"padding-left: 30px;\">ARE MACHINES RACIST? Are algorithms and artificial intelligence inherently prejudiced? Do Facebook, Google, and Twitter have political biases? Those answers are complicated.<\/p>\n<p style=\"padding-left: 30px;\">But if the question is whether the tech industry doing enough to address these biases, the straightforward response is no.<br \/>\n&#8230;<br \/>\nHumans cannot wholly avoid bias, as countless studies and publications have shown. Insisting otherwise is an intellectually dishonest and lazy response to a very real problem.<br \/>\n&#8230;<br \/>\nIn my six months at Facebook, where I was hired to be the head of global elections integrity ops in the company\u2019s business integrity division, I participated in numerous discussions about the topic. I did not know anyone who intentionally wanted to incorporate bias into their work. But I also did not find anyone who actually knew what it meant to counter bias in any true and methodical way.<\/p>\n<p>&nbsp;<\/p>\n<blockquote><p><span style=\"color: #ff6600;\"><strong>But the company has created its own sort of insular bubble in which its employees&#8217; perception of the world is the product of a number of biases that are engrained within the Silicon Valley tech and innovation scene.<\/strong><\/span><\/p><\/blockquote>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The real reason tech struggles with algorithmic bias &#8212; from wired.com by Yael Eisenstat Excerpts: ARE MACHINES RACIST? Are algorithms and artificial intelligence inherently prejudiced? Do Facebook, Google, and Twitter have political biases? Those answers are complicated. But if the question is whether the tech industry doing enough to address these biases, the straightforward response [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[113,435,356,817,387,45,210,403,816,63,353,269,204,480,454,195,321,367],"tags":[],"class_list":["post-66182","post","type-post","status-publish","format-standard","hentry","category-21st-century","category-analytics","category-artificial-intelligence-agents-llms-and-related","category-bots","category-business","category-computer-science","category-emerging-technologies","category-ethics","category-facebook","category-google","category-moralsvalues","category-professional-development","category-programming","category-society","category-the-downsides-of-technology","category-tools","category-united-states","category-vendors"],"_links":{"self":[{"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/66182","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/comments?post=66182"}],"version-history":[{"count":2,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/66182\/revisions"}],"predecessor-version":[{"id":66184,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/posts\/66182\/revisions\/66184"}],"wp:attachment":[{"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/media?parent=66182"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/categories?post=66182"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/danielschristian.com\/learning-ecosystems\/wp-json\/wp\/v2\/tags?post=66182"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}