{"id":4456,"date":"2019-11-21T11:16:12","date_gmt":"2019-11-21T15:16:12","guid":{"rendered":"https:\/\/www.shortform.com\/blog\/?p=4456"},"modified":"2022-03-11T16:14:05","modified_gmt":"2022-03-11T20:14:05","slug":"deterministic-chaos","status":"publish","type":"post","link":"https:\/\/www.shortform.com\/blog\/deterministic-chaos\/","title":{"rendered":"Deterministic Chaos: Why Prediction is Often Impossible"},"content":{"rendered":"\n<p>What is deterministic chaos? How is it different than &#8220;true randomness&#8221;? Can we make predictions in situations of deterministic chaos?<\/p>\n\n\n\n<p>Deterministic chaos is a system whose operation <em>could <\/em>be predicted, but whose complexity makes prediction so difficult that it\u2019s effectively impossible. That is, if we had the right information, we would be able to make sense of \u201cchaos.\u201d<\/p>\n\n\n\n<p>We&#8217;ll cover situations of deterministic chaos and if it affects our <a href=\"https:\/\/www.shortform.com\/blog\/methods-of-decision-making-crucial-conversations\/\">decision-making<\/a>.<\/p>\n\n\n\n<!--more-->\n\n\n\n<h2 class=\"wp-block-heading\">Deterministic Chaos: <strong>Our Information Is Always Incomplete<\/strong><\/h2>\n\n\n\n<p>Mathematicians and philosophers draw a distinction between \u201ctrue randomness\u201d and \u201cdeterministic chaos.\u201d A \u201crandom\u201d system is one whose operation is always and forever impossible to predict. A system of deterministic chaos is one whose operation <em>could <\/em>be predicted, but whose complexity makes prediction so difficult that it\u2019s effectively impossible. That is, if we had the right information, we would be able to make sense of \u201cdeterministic chaos.\u201d<br><\/p>\n\n\n\n<p><a href=\"https:\/\/www.shortform.com\/blog\/nassim-nicholas-taleb\/\">Taleb<\/a> notes that, for normal people trying to make predictions about their stock portfolio, for example, or the appreciation of the value of their house, there\u2019s no difference between \u201ctrue randomness\u201d and \u201cdeterministic chaos.\u201d <strong>That\u2019s because when we\u2019re faced with a <a href=\"https:\/\/www.shortform.com\/blog\/what-is-a-dynamic-system\/\">dynamical system<\/a>, we <\/strong><strong><em>always <\/em><\/strong><strong>lack the necessary information to decide whether it\u2019s truly random or simply chaotic.<\/strong><br><\/p>\n\n\n\n<p>Such is the case with history as well: Perhaps each major historical event conforms to some incredibly complex plan\u2014that is, perhaps history is just chaotic, not random\u2014<strong>but we\u2019ll <em>never have enough information<\/em> to discern that plan<\/strong>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Predicting the Past<\/strong><\/h2>\n\n\n\n<p>Whether or not we live in a system of deterministic chaos, we&#8217;ll never have enough information to make predictions, even when we know the outcome. Through the limitations of inductive reasoning as illustrated by the turkey anecdote, as well as the distortions of the <a href=\"https:\/\/www.shortform.com\/blog\/narrative-fallacy-2\/\">narrative fallacy<\/a> and <a href=\"https:\/\/www.shortform.com\/blog\/silent-evidence\/\">silent evidence<\/a>, we\u2019ve seen how problematic the past is vis-\u00e0-vis prediction. <strong>But because of these phenomena and others, the past <em>itself <\/em>is as unknowable as the future<\/strong>.<br><\/p>\n\n\n\n<p>One of the major obstacles that prevents us from knowing the past with certainty is the impossibility of reverse engineering causes for events. That is, there\u2019s no way to determine the precise cause of an event when we work backward in time from the event itself.<br><\/p>\n\n\n\n<p>An example should help illustrate.&nbsp;<br><\/p>\n\n\n\n<p>Think of an ice cube sitting on a table. Imagine the shape of the puddle that ice cube will make as it melts.<br><\/p>\n\n\n\n<p>Now think of a puddle on the table and try to imagine how that puddle got there.<br><\/p>\n\n\n\n<p>The second <a href=\"https:\/\/www.shortform.com\/blog\/philosophical-thought-experiments\/\">thought experiment<\/a> is much harder than the first. With the right physics know-how and ample time, one could model exactly what kind of puddle will result from the melting ice cube (based on the cube\u2019s shape, the environmental conditions, etc.). In contrast, it\u2019s nearly impossible to <a href=\"https:\/\/www.shortform.com\/blog\/how-to-reverse-engineer\/\">reverse engineer<\/a> a cause from a random puddle (because the puddle could have been caused by any number of things).<br><\/p>\n\n\n\n<p>When historians propose causes for certain historical events, they\u2019re looking at puddles and imagining ice cubes (or a spilled glass of water, or some other cause). The problem is that the sheer number of possible causes for a puddle\u2014or a historical event\u2014render any ascription of cause suspect. We don&#8217;t have the information to fully understand the system of deterministic chaos.<br><\/p>\n\n\n\n<p>Poincar\u00e9\u2019s nonlinearities too help illustrate this problem. Again, with the right tools and time, one might be able to observe how the flutter of a butterfly\u2019s wings in India causes a hurricane in Florida, <strong>but it would be impossible to work backwards from the hurricane to that cause\u2014there are just too many <em>other <\/em>tiny events that may have played a part<\/strong>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>What is deterministic chaos? How is it different than &#8220;true randomness&#8221;? Can we make predictions in situations of deterministic chaos? Deterministic chaos is a system whose operation could be predicted, but whose complexity makes prediction so difficult that it\u2019s effectively impossible. That is, if we had the right information, we would be able to make sense of \u201cchaos.\u201d We&#8217;ll cover situations of deterministic chaos and if it affects our decision-making.<\/p>\n","protected":false},"author":4,"featured_media":4472,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[21],"tags":[60],"class_list":["post-4456","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-philosophy","tag-black-swan","","tg-column-two"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v24.3 (Yoast SEO v24.3) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Deterministic Chaos: Why Prediction is Often Impossible - Shortform Books<\/title>\n<meta name=\"description\" content=\"Deterministic chaos is a system whose operation could be predicted, but whose complexity makes prediction so difficult that it\u2019s effectively impossible.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.shortform.com\/blog\/deterministic-chaos\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Deterministic Chaos: Why Prediction is Often Impossible\" \/>\n<meta property=\"og:description\" content=\"Deterministic chaos is a system whose operation could be predicted, but whose complexity makes prediction so difficult that it\u2019s effectively impossible.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.shortform.com\/blog\/deterministic-chaos\/\" \/>\n<meta property=\"og:site_name\" content=\"Shortform Books\" \/>\n<meta property=\"article:published_time\" content=\"2019-11-21T15:16:12+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2022-03-11T20:14:05+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.shortform.com\/blog\/wp-content\/uploads\/2019\/11\/swan-deterministic-chaos.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"774\" \/>\n\t<meta property=\"og:image:height\" content=\"514\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Amanda Penn\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Amanda Penn\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.shortform.com\/blog\/deterministic-chaos\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.shortform.com\/blog\/deterministic-chaos\/\"},\"author\":{\"name\":\"Amanda Penn\",\"@id\":\"https:\/\/www.shortform.com\/blog\/#\/schema\/person\/01b0e4c9ddb993e51d03808839d538b0\"},\"headline\":\"Deterministic Chaos: Why Prediction is Often Impossible\",\"datePublished\":\"2019-11-21T15:16:12+00:00\",\"dateModified\":\"2022-03-11T20:14:05+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.shortform.com\/blog\/deterministic-chaos\/\"},\"wordCount\":626,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/www.shortform.com\/blog\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.shortform.com\/blog\/deterministic-chaos\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.shortform.com\/blog\/wp-content\/uploads\/2019\/11\/swan-deterministic-chaos.jpg\",\"keywords\":[\"The Black Swan\"],\"articleSection\":[\"Philosophy\"],\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/www.shortform.com\/blog\/deterministic-chaos\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.shortform.com\/blog\/deterministic-chaos\/\",\"url\":\"https:\/\/www.shortform.com\/blog\/deterministic-chaos\/\",\"name\":\"Deterministic Chaos: Why Prediction is Often Impossible - 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