{"id":389,"date":"2023-08-16T14:54:56","date_gmt":"2023-08-16T14:54:56","guid":{"rendered":"https:\/\/www.notwitsend.com\/wordpress\/?p=389"},"modified":"2024-02-28T15:18:49","modified_gmt":"2024-02-28T15:18:49","slug":"gigo-as-applied-to-ai","status":"publish","type":"post","link":"https:\/\/www.notwitsend.com\/wordpress\/index.php\/2023\/08\/16\/gigo-as-applied-to-ai\/","title":{"rendered":"GIGO as applied to AI"},"content":{"rendered":"\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"609\" height=\"349\" src=\"https:\/\/www.notwitsend.com\/wordpress\/wp-content\/uploads\/2023\/08\/1520091549026.jpg\" alt=\"\" class=\"wp-image-397\" srcset=\"https:\/\/www.notwitsend.com\/wordpress\/wp-content\/uploads\/2023\/08\/1520091549026.jpg 609w, https:\/\/www.notwitsend.com\/wordpress\/wp-content\/uploads\/2023\/08\/1520091549026-300x172.jpg 300w\" sizes=\"auto, (max-width: 609px) 100vw, 609px\" \/><figcaption class=\"wp-element-caption\">copyright James Cornehlsen <\/figcaption><\/figure>\n\n\n\n<p>The concept of &#8220;GIGO&#8221;&#8211;Garbage In, Garbage Out&#8211;has been around almost as long as computer programming itself.<\/p>\n\n\n\n<p>GIGO is the idea that, no matter how well written and definitive a computer program or algorithm is, if you feed it bad data the resulting output will be &#8220;bad&#8221;&#8211;i.e., have no useful meaning or, at worst, misleading meaning.<\/p>\n\n\n\n<p>Nothing surprising here&#8211;as programmers we are well aware of this problem and often take great pains to protect an algorithm implementation against &#8220;Garbage In&#8221;.<\/p>\n\n\n\n<p>It&#8217;s not possible to protect against all such cases, of course, human nature being what it is.<\/p>\n\n\n\n<p>Which brings us to the story behind this blog posting: the improper use of Generative AI to &#8220;make decisions&#8221; in ways that are impactful in the most damaging ways.<\/p>\n\n\n\n<p>The starting point for this story:  the state of Iowa in the United States is one of several states that have recently passed laws aimed at protecting young students from exposure to &#8220;inappropriate&#8221; materials in the school setting.<\/p>\n\n\n\n<figure class=\"wp-block-pullquote\"><blockquote><p><a rel=\"noreferrer noopener\" href=\"https:\/\/www.legis.iowa.gov\/legislation\/BillBook?ga=90&amp;ba=SF496\" target=\"_blank\">Senate File 496 <\/a>includes limitations on school and classroom library collections, requiring that every book available to students be \u201cage appropriate\u201d and free of any \u201cdescriptions or visual depictions of a sex act\u201d according to Iowa Code 702.17.<\/p><cite>The Gazette<\/cite><\/blockquote><\/figure>\n\n\n\n<p>The Gazette (a daily newspaper in Cedar Rapids, Iowa) has the <a href=\"https:\/\/www.thegazette.com\/k\/19-books-pulled-from-mason-city-school-libraries\/\">story of a school district<\/a> in its area that has chosen to use AI (Machine Learning) to determine which books may run afoul of this new law.<\/p>\n\n\n\n<p>Their reasoning for using AI?  &#8220;<em>Assistant Superintendent of Curriculum and Instruction Bridgette Exman told The Gazette that it was &#8220;simply not feasible to read every book&#8230;&#8221;<\/em><\/p>\n\n\n\n<p>Sounds reasonable, right?<\/p>\n\n\n\n<p>Well, the school district chose to generate the list of proscribed books by &#8220;feeding it a list of proscribed books [provided from other sources]&#8221; and seeing if the resulting output list presented &#8220;any surprises&#8221; to a staff librarian.<\/p>\n\n\n\n<p>See the problem here?  As noted in a blog about the news story:<\/p>\n\n\n\n<figure class=\"wp-block-pullquote\"><blockquote><p>The district didn&#8217;t run every book through the process, only the &#8220;commonly challenged&#8221; ones; if the end result was a list of commonly challenged books and no books that aren&#8217;t commonly challenged, well, there you go.<\/p><cite>Daily Kos<\/cite><\/blockquote><\/figure>\n\n\n\n<p>It appears that people who don&#8217;t understand how to use Machine Learning misused it&#8211;GIGO?&#8211;and now have a trained AI that they think will allow them to filter out inappropriate books without having a human read and judge them.<\/p>\n\n\n\n<figure class=\"wp-block-pullquote\"><blockquote><p>Regardless of whether or not any of the titles do or do not contain said content, ChatGPT\u2019s varying responses highlight troubling deficiencies of accuracy, analysis, and consistency. A repeat inquiry regarding The Kite Runner, for example, gives contradictory answers. In one response, ChatGPT deems Khaled Hosseini\u2019s novel to contain \u201clittle to no explicit sexual content.\u201d Upon a separate follow-up, the [Large Language Model] affirms the book \u201cdoes contain a description of a sexual assault.\u201d<\/p><cite>Popular Science<\/cite><\/blockquote><\/figure>\n\n\n\n<p>This misuse of AI\/ML is not uncommon&#8211;we&#8217;ve seen cases where law enforcement has trained facial recognition programs in a way which creates serious racial bias, for instance.<\/p>\n\n\n\n<p>We, as IT professionals, need to aware of and on the lookout for such misuses, as we are in the best position to spot such situations and understand how to avoid them.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The concept of &#8220;GIGO&#8221;&#8211;Garbage In, Garbage Out&#8211;has been around almost as long as computer programming itself. GIGO is the idea that, no matter how well written and definitive a computer program or algorithm is, if you feed it bad data the resulting output will be &#8220;bad&#8221;&#8211;i.e., have no useful meaning or, at worst, misleading meaning. [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-389","post","type-post","status-publish","format-standard","hentry","category-sogetilabs-posted"],"_links":{"self":[{"href":"https:\/\/www.notwitsend.com\/wordpress\/index.php\/wp-json\/wp\/v2\/posts\/389","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.notwitsend.com\/wordpress\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.notwitsend.com\/wordpress\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.notwitsend.com\/wordpress\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.notwitsend.com\/wordpress\/index.php\/wp-json\/wp\/v2\/comments?post=389"}],"version-history":[{"count":12,"href":"https:\/\/www.notwitsend.com\/wordpress\/index.php\/wp-json\/wp\/v2\/posts\/389\/revisions"}],"predecessor-version":[{"id":404,"href":"https:\/\/www.notwitsend.com\/wordpress\/index.php\/wp-json\/wp\/v2\/posts\/389\/revisions\/404"}],"wp:attachment":[{"href":"https:\/\/www.notwitsend.com\/wordpress\/index.php\/wp-json\/wp\/v2\/media?parent=389"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.notwitsend.com\/wordpress\/index.php\/wp-json\/wp\/v2\/categories?post=389"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.notwitsend.com\/wordpress\/index.php\/wp-json\/wp\/v2\/tags?post=389"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}