{"id":18448,"date":"2022-04-16T09:11:41","date_gmt":"2022-04-16T16:11:41","guid":{"rendered":"https:\/\/www.kith.org\/words\/?p=18448"},"modified":"2022-04-16T10:37:42","modified_gmt":"2022-04-16T17:37:42","slug":"ai-has-a-long-way-to-go","status":"publish","type":"post","link":"https:\/\/www.kith.org\/words\/2022\/04\/16\/ai-has-a-long-way-to-go\/","title":{"rendered":"AI has a long way to go"},"content":{"rendered":"\r\n<p>Twitter just recommended for me a tweet that it labeled as being on the topic \u201cfilmmaking.\u201d<\/p>\r\n<p>It was a tweet by Ana Mardoll about a doctor behaving badly. It had nothing to do with filmmaking.<\/p>\r\n<p>But it did include the phrase \u201cright before he wrote the script.\u201d<\/p>\r\n<p>Dear Twitter: Words have multiple meanings. In this case, the word <i>script<\/i> is short for <i>prescription<\/i>.<\/p>\r\n<p>More generally, recommended-for-you systems continue to be terrible at guessing what might be of interest to a reader, and part of the reason for that is that those systems aren\u2019t always even correctly analyzing the topics of the recommended posts.<\/p>\r\n<p>In this case, I <em>was<\/em> interested in the tweet in question. But not for the reasons that Twitter\u2019s algorithm thought.<\/p>\r\n<p>\u2026Edited to add an even better example, an hour later:<\/p>\r\n<p>Twitter showed me a post from someone I\u2019ve never heard of. Its explanation\/label for why it was showing it to me? \u201cAstrology.\u201d<\/p>\r\n<p>I have a strong antipathy for astrology. I have less than no interest in being shown astrology tweets.<\/p>\r\n<p>But the reason this particular tweet is such a great example is that it has <em>nothing to do with astrology<\/em>.<\/p>\r\n<p>But it uses the phrase \u201cthree-star Michelin restaurant.\u201d<\/p>\r\n<p>So Twitter\u2019s inept AI saw the word \u201cstar\u201d in the tweet, decided it was a tweet about astrology, and showed me the tweet because it thought I was interested in astrology.<\/p>\r\n<p>At this point I\u2019m almost inclined to think that Twitter\u2019s AI is intentionally trolling me.<\/p>\r\n\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":5,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[127],"tags":[],"class_list":["post-18448","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.kith.org\/words\/wp-json\/wp\/v2\/posts\/18448","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kith.org\/words\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.kith.org\/words\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.kith.org\/words\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kith.org\/words\/wp-json\/wp\/v2\/comments?post=18448"}],"version-history":[{"count":4,"href":"https:\/\/www.kith.org\/words\/wp-json\/wp\/v2\/posts\/18448\/revisions"}],"predecessor-version":[{"id":18452,"href":"https:\/\/www.kith.org\/words\/wp-json\/wp\/v2\/posts\/18448\/revisions\/18452"}],"wp:attachment":[{"href":"https:\/\/www.kith.org\/words\/wp-json\/wp\/v2\/media?parent=18448"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.kith.org\/words\/wp-json\/wp\/v2\/categories?post=18448"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.kith.org\/words\/wp-json\/wp\/v2\/tags?post=18448"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}