{"id":6770,"date":"2016-03-02T14:19:20","date_gmt":"2016-03-02T21:19:20","guid":{"rendered":"https:\/\/www.roughtype.com\/?p=6770"},"modified":"2016-03-02T20:12:44","modified_gmt":"2016-03-03T03:12:44","slug":"will-we-compile","status":"publish","type":"post","link":"https:\/\/www.roughtype.com\/?p=6770","title":{"rendered":"Will we compile?"},"content":{"rendered":"<p><a href=\"https:\/\/i0.wp.com\/www.roughtype.com\/wp\/wp-content\/uploads\/2016\/03\/ordvac1.jpg?ssl=1\" rel=\"attachment wp-att-6774\"><img data-recalc-dims=\"1\" loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-6774\" src=\"https:\/\/i0.wp.com\/www.roughtype.com\/wp\/wp-content\/uploads\/2016\/03\/ordvac1.jpg?resize=625%2C275&#038;ssl=1\" alt=\"ordvac1\" width=\"625\" height=\"275\" srcset=\"https:\/\/i0.wp.com\/www.roughtype.com\/wp\/wp-content\/uploads\/2016\/03\/ordvac1.jpg?w=640&amp;ssl=1 640w, https:\/\/i0.wp.com\/www.roughtype.com\/wp\/wp-content\/uploads\/2016\/03\/ordvac1.jpg?resize=300%2C132&amp;ssl=1 300w, https:\/\/i0.wp.com\/www.roughtype.com\/wp\/wp-content\/uploads\/2016\/03\/ordvac1.jpg?resize=624%2C275&amp;ssl=1 624w\" sizes=\"auto, (max-width: 625px) 100vw, 625px\" \/><\/a><\/p>\n<p>Getting machines to understand, and speak, the language used by people \u2014 natural language processing \u2014 has long been a central goal of artificial intelligence research. In a provocative\u00a0new <a href=\"http:\/\/edge.org\/conversation\/stephen_wolfram-ai-the-future-of-civilization\">interview<\/a> at <em>Edge<\/em>, Stephen Wolfram turns that goal on its head. The real challenge, he suggests, is getting people to understand, and speak, the language used by machines. In a future world in which we rely on computers to fulfill our desires, we\u2019re going to need to be able to express those desires in a way that computers can understand.<\/p>\n<p>We\u2019re amazed that Siri can answer our questions. But, as Wolfram points out, Siri\u2019s ability to make sense of human language is profoundly constrained. You can\u2019t have a deep or subtle conversation with a computer using human language. \u201cIt works pretty well when you&#8217;re holding up your phone and asking one question,\u201d he says. \u201cIt&#8217;s a pretty successful way to communicate, to use natural language. When you want to say something longer and more complicated, it doesn&#8217;t work very well.\u201d The problem is not just a consequence of the limits of natural language processing. It\u2019s a consequence of the limits of natural language. We think of human\u00a0language as all-encompassing\u00a0(because\u00a0it encompasses the whole of our conscious thought), but the language we humans speak is particular to our history. It has, as Wolfram puts it, \u201cevolved to describe what we typically encounter in the world.\u201d It\u2019s absurd to assume that our language would do a good job of describing the way computers encounter the world.<\/p>\n<p>If we\u2019re going to depend on computers to fulfill our purposes, we\u2019re going to need a shared language. We\u2019re going to need to describe our purposes, our desires, in a code that can run successfully through a machine. Most of those\u00a0who advocate teaching programming skills to the masses argue that learning to code will expand our job prospects. Wolfram\u2019s view is more interesting. He argues that we need to learn to code in order to expand our ontological prospects.<\/p>\n<p>In adopting a new\u00a0language, a machine language, to describe our purposes, we will also, necessarily, change those\u00a0purposes. That is the price of computer automation. &#8220;What do the humans do&#8221; in a world where &#8220;things can get done automatically?\u201d Wolfram asks. The answer, of course, is that we compose\u00a0the instructions\u00a0for the machines to follow to fulfill our wishes.\u00a0<em>Will it compile?<\/em> is the iron law of programming. Either\u00a0the machine can\u00a0follow the instructions written for it, or it can&#8217;t.\u00a0<em>Will we compile?<\/em> would seem to be the great ontological question that lies ahead of us in our automated future. Have we formulated our purposes in such a way that machines can carry them out?<\/p>\n<p>Computers can\u2019t choose our goals for us, Wolfram correctly observes. \u201cGoals are a human construct.\u201d Determining our purposes will remain a human activity, beyond the reach of automation. But will it really matter? If we are required to formulate our goals in a language a machine can understand, is not the machine determining, or at least circumscribing, our purposes? Can you assume another\u2019s language without also assuming its system of meaning and its system of being?<\/p>\n<p>The question isn\u2019t a new one. \u201cI must create a system, or be enlaved by another man\u2019s,\u201d wrote William Blake two hundred years ago. Poets and other thoughtful persons have always struggled to express themselves, to formulate and fulfill their purposes, within and against the constraints of language. Up to now, the struggle has been with a language that evolved to express human purposes \u2014 to express <em>human being<\/em>. The ontological crisis changes, and deepens, when we are required to express ourselves in a language developed to suit the workings of a computer. Suddenly, we face a new\u00a0question: Is the\u00a0compilable life worth living?<\/p>\n<p><em>Image: <a href=\"http:\/\/ftp.arl.mil\/ftp\/historic-computers\/\">U.S. Army Photo<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Getting machines to understand, and speak, the language used by people \u2014 natural language processing \u2014 has long been a central goal of artificial intelligence research. In a provocative\u00a0new interview at Edge, Stephen Wolfram turns that goal on its head. The real challenge, he suggests, is getting people to understand, and speak, the language used [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[1],"tags":[],"class_list":["post-6770","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_publicize_connections":[],"jetpack_sharing_enabled":true,"jetpack_featured_media_url":"","_links":{"self":[{"href":"https:\/\/www.roughtype.com\/index.php?rest_route=\/wp\/v2\/posts\/6770","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.roughtype.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.roughtype.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.roughtype.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.roughtype.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=6770"}],"version-history":[{"count":10,"href":"https:\/\/www.roughtype.com\/index.php?rest_route=\/wp\/v2\/posts\/6770\/revisions"}],"predecessor-version":[{"id":6783,"href":"https:\/\/www.roughtype.com\/index.php?rest_route=\/wp\/v2\/posts\/6770\/revisions\/6783"}],"wp:attachment":[{"href":"https:\/\/www.roughtype.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=6770"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.roughtype.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=6770"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.roughtype.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=6770"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}