{"id":165,"date":"2020-08-24T11:26:09","date_gmt":"2020-08-24T15:26:09","guid":{"rendered":"https:\/\/www.macloo.com\/ai\/?p=165"},"modified":"2020-08-24T12:10:47","modified_gmt":"2020-08-24T16:10:47","slug":"what-is-called-ai-but-really-isnt","status":"publish","type":"post","link":"https:\/\/www.macloo.com\/ai\/2020\/08\/24\/what-is-called-ai-but-really-isnt\/","title":{"rendered":"What is called \u2018AI\u2019 but really isn\u2019t"},"content":{"rendered":"\n<p>Because &#8220;artificial intelligence&#8221; and &#8220;AI&#8221; have become such potent buzzwords in business \u2014 and so many firms are trying to sell some kind of &#8220;AI&#8221; system or software or strategy to every business possible \u2014 we should all take a step back and evaluate <em>whether there is actual AI<\/em> operating in some of these systems.<\/p>\n\n\n\n<p>That won&#8217;t always be easy to discern. If a company claims there is &#8220;AI&#8221; in its product, they are not going to divulge exactly how it works. If they want to convince you, their literature or their engineers will likely throw out a tangled net of terms that, while accurate, might not help anyone but another engineer understand what&#8217;s inside the black box.<\/p>\n\n\n\n<p>I was thinking about this recently as I worked on assignments for <a rel=\"noreferrer noopener\" href=\"https:\/\/cs50.harvard.edu\/ai\/2020\/\" target=\"_blank\">an online computer science course in AI<\/a>. One of the early projects was to program a tic-tac-toe game in which a human can play against &#8220;an AI.&#8221; Just like most humans, the AI can force a tie in every tic-tac-toe game <em>unless the human makes a mistake, <\/em>and then the human will lose. I wrote the code that enables the AI to play \u2014 that was the assignment. But I <em>didn&#8217;t<\/em> invent the code from nothing. I was taught in the course to use an algorithm called <a rel=\"noreferrer noopener\" href=\"https:\/\/en.wikipedia.org\/wiki\/Minimax#Pseudocode\" target=\"_blank\">minimax<\/a>. Further, I was encouraged to make my program faster by using another algorithm called <a rel=\"noreferrer noopener\" href=\"https:\/\/en.wikipedia.org\/wiki\/Alpha%E2%80%93beta_pruning#Improvements_over_naive_minimax\" target=\"_blank\">alpha-beta pruning<\/a>.<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1000\" height=\"507\" src=\"https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/AB_pruning_wikipedia.png\" alt=\"\" class=\"wp-image-168\" srcset=\"https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/AB_pruning_wikipedia.png 1000w, https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/AB_pruning_wikipedia-300x152.png 300w, https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/AB_pruning_wikipedia-768x389.png 768w\" sizes=\"auto, (max-width: 1000px) 100vw, 1000px\" \/><figcaption><em>Illustration of alpha-beta pruning (Wikipedia, by <a rel=\"noreferrer noopener\" href=\"https:\/\/commons.wikimedia.org\/wiki\/File:AB_pruning.svg\" target=\"_blank\">Jez9999<\/a>, <a href=\"https:\/\/commons.wikimedia.org\/wiki\/Commons:GNU_Free_Documentation_License,_version_1.2\" target=\"_blank\" rel=\"noreferrer noopener\">GNU license<\/a>)<\/em><\/figcaption><\/figure><\/div>\n\n\n\n<p>There is no machine learning involved in those two algorithms. They are simply a time-tested way for a computer language to direct a certain kind of look-ahead in a two-player game (not only tic-tac-toe). <\/p>\n\n\n\n<p>Don&#8217;t despair or tune out \u2014 look at the diagram and understand that the computer, through instructions in my code, is able to rapidly advance through <em>every possible outcome<\/em> in tic-tac-toe and see how to: (a) prevent a win for the opponent, and (b) win if a win is possible. <\/p>\n\n\n\n<p>There is no magic here.<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"768\" src=\"https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/my_tictactoe-1.png\" alt=\"\" class=\"wp-image-174\" srcset=\"https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/my_tictactoe-1.png 1024w, https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/my_tictactoe-1-300x225.png 300w, https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/my_tictactoe-1-768x576.png 768w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption><em>Tic-tac-toe with &#8220;AI&#8221; playing X, human playing O.<\/em><\/figcaption><\/figure><\/div>\n\n\n\n<p>Another assignment in the same course has the students programming &#8220;an AI&#8221; that plays Minesweeper. This game is quite different from tic-tac-toe in that there is only <em>one<\/em> player, and there is <em>hidden knowledge<\/em>: The player doesn&#8217;t know where the mines are. One move at a time, the player builds knowledge about the game board.<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"479\" src=\"https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/my_minesweeper.png\" alt=\"\" class=\"wp-image-177\" srcset=\"https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/my_minesweeper.png 1024w, https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/my_minesweeper-300x140.png 300w, https:\/\/www.macloo.com\/ai\/wp-content\/uploads\/2020\/08\/my_minesweeper-768x359.png 768w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption><em>Completed Minesweeper game, with AI playing all moves.<\/em><\/figcaption><\/figure><\/div>\n\n\n\n<p>A human player doesn&#8217;t click on a mine, because she chooses squares that are next to a 0 (indicating no mines touch that square) and <em>marks<\/em> a mine square when it becomes obvious that a mine is hidden there.<\/p>\n\n\n\n<p>The &#8220;AI&#8221; builds knowledge in a way that it is programmed to do (that is the assignment). In this case, there is no pre-existing algorithm, but there are principles of logic. I programmed &#8220;knowledge&#8221; that was stored in the program each time the AI clicked a square and a number was revealed. The knowledge is: (a) that number, and (b) the coordinates of all the surrounding squares. Thus the AI &#8220;knows&#8221; that, for example, among eight specified squares there are two mines.<\/p>\n\n\n\n<p>If among eight specified squares there are zero mines, my code tells the AI to mark all eight of those squares as <em>safe<\/em>. My code also tells the AI that if there are <em>any<\/em> safe moves left to be made, then make a safe move. If not, make a random move. That is the only time when the AI can possibly set off a mine.<\/p>\n\n\n\n<p>Once again, there is no magic here. <\/p>\n\n\n\n<p>In contrast to these two simple examples of a computer successfully playing a game, AlphaGo (which <a href=\"https:\/\/www.macloo.com\/ai\/2020\/08\/10\/ai-programs-that-play-games\/\">I wrote about previously<\/a>) uses <em>real<\/em> AI and could not have beaten a human Go master otherwise. Some games can&#8217;t be programmed with only simple algorithms or logic \u2014 if they are to win, they need something akin to <em>intuition<\/em>. <\/p>\n\n\n\n<p>Programming a computer to develop and use an approximation of human intuition is what we have in today&#8217;s machine learning with deep neural networks. It&#8217;s <em>still<\/em> not magic, but it&#8217;s a lot more complicated than the kind of strictly mapped-out processes I wrote for playing tic-tac-toe or Minesweeper.<\/p>\n\n\n\n<p><a rel=\"license\" href=\"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/\"><img decoding=\"async\" alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https:\/\/i.creativecommons.org\/l\/by-nc-nd\/4.0\/88x31.png\"><\/a><br>\n<small><span xmlns:dct=\"http:\/\/purl.org\/dc\/terms\/\" property=\"dct:title\"><strong>AI in Media and Society<\/strong><\/span> by <span xmlns:cc=\"http:\/\/creativecommons.org\/ns#\" property=\"cc:attributionName\">Mindy McAdams<\/span> is licensed under a <a rel=\"license\" href=\"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/\">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License<\/a>.<br>\nInclude the author&#8217;s name (Mindy McAdams) and a link to the original post in any reuse of this content.<\/small><\/p>\n\n\n\n<p><\/p>\n\n\n\n<p>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Because &#8220;artificial intelligence&#8221; and &#8220;AI&#8221; have become such potent buzzwords in business \u2014 and so many firms are trying to sell some kind of &#8220;AI&#8221; system or software or strategy to every business possible \u2014 we should all take a step back and evaluate whether there is actual AI operating in some of these systems.&hellip; <a class=\"more-link\" href=\"https:\/\/www.macloo.com\/ai\/2020\/08\/24\/what-is-called-ai-but-really-isnt\/\">Continue reading <span class=\"screen-reader-text\">What is called \u2018AI\u2019 but really isn\u2019t<\/span> <span class=\"meta-nav\" aria-hidden=\"true\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[43,7,5],"tags":[41,11,44],"class_list":["post-165","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-games","category-machine-learning","tag-definitions","tag-learning","tag-not-ai"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.macloo.com\/ai\/wp-json\/wp\/v2\/posts\/165","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.macloo.com\/ai\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.macloo.com\/ai\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.macloo.com\/ai\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.macloo.com\/ai\/wp-json\/wp\/v2\/comments?post=165"}],"version-history":[{"count":10,"href":"https:\/\/www.macloo.com\/ai\/wp-json\/wp\/v2\/posts\/165\/revisions"}],"predecessor-version":[{"id":186,"href":"https:\/\/www.macloo.com\/ai\/wp-json\/wp\/v2\/posts\/165\/revisions\/186"}],"wp:attachment":[{"href":"https:\/\/www.macloo.com\/ai\/wp-json\/wp\/v2\/media?parent=165"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.macloo.com\/ai\/wp-json\/wp\/v2\/categories?post=165"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.macloo.com\/ai\/wp-json\/wp\/v2\/tags?post=165"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}