{"id":66,"date":"2018-02-25T22:10:53","date_gmt":"2018-02-26T06:10:53","guid":{"rendered":"http:\/\/linguamonium.com\/?p=66"},"modified":"2021-04-25T20:19:29","modified_gmt":"2021-04-25T20:19:29","slug":"on-machine-translation-the-media-and-meaning-a-response","status":"publish","type":"post","link":"https:\/\/linguamonium.com\/?p=66","title":{"rendered":"On machine translation, the media, and meaning (a response)"},"content":{"rendered":"<p>I\u2019m a Douglas Hofstadter fan. I read his book <em>I Am a Strange Loop<\/em> years ago, and it remains one of my three favorite non-fiction books, period. I highly recommend it to anyone who is at all interested in the nature of consciousness. The cognitive scientist\u2019s Pulitzer Prize-winning <em>G\u00f6del, Escher, Bach: An Eternal Golden Braid<\/em> has also been on my to-read list for a long time. So I was excited to see <a href=\"https:\/\/www.theatlantic.com\/technology\/archive\/2018\/01\/the-shallowness-of-google-translate\/551570\/?lipi=urn%3Ali%3Apage%3Ad_flagship3_feed%3B%2BOwfwH4sSEyuYJRkUfqhFA%3D%3D\" target=\"_blank\" rel=\"noopener\">this article<\/a> by him in <em>The Atlantic<\/em>, on another area that interests me: machine translation and machine \u201cintelligence\u201d.<\/p>\n<p>Early on in the piece, Hofstadter says he has a \u201clongstanding belief that it\u2019s important to combat exaggerated claims about artificial intelligence\u201d. Having worked in the machine learning\/AI field for a little under a year now (but what an intense year it has been!), and having read countless popular media articles touting the astonishing advances in natural language processing\/understanding, ML, and AI, I heartily agree with his sentiment. Such reporting is as misleading as it is annoying.<\/p>\n<p>I came across a statement of this type the other day, in <a href=\"https:\/\/venturebeat.com\/2017\/08\/08\/stanford-ai-researchers-make-socially-inclusive-nlp-using-urban-dictionary-and-twitter\/\" target=\"_blank\" rel=\"noopener\">Stanford AI researchers make \u2018socially inclusive\u2019 NLP<\/a>:<\/p>\n<p>\u201cThe average person working with NLP today may consider language identification a solved problem.&#8221;<\/p>\n<p>I have trouble believing that any researcher working in NLP\/NLU\/ML\/AI thinks anything is a <em>solved problem<\/em>. Despite much progress, the field is still in its infancy. Doesn\u2019t anyone remember Einstein\u2019s quote (adapted from a similar idea expressed by Socrates) \u2013 \u201cThe more I learn, the more I realize how much I don\u2019t know\u201d? Where I work, every possible solution to a given problem brings up more questions, and even the \u201csimplest\u201d \u201cfacts\u201d cannot always be taken for granted. (Remember when you were taught parts of speech like verb, noun, and preposition in grade school? Working at the level of detail we do, even these fundamental rules are often inadequate, requiring further specification. Turns out it\u2019s hard to throw messy, real language into clean, fixed bins.) So I think the media does the field, its researchers, and the reading public a great disservice by sensationalizing and oversimplifying the challenges.<\/p>\n<p>Hofstadter\u2019s argument about <em>understanding<\/em> is even more poignant:<\/p>\n<p>\u201cThe practical utility of Google Translate and similar technologies is undeniable, and probably it\u2019s a good thing overall, but there is still something deeply lacking in the approach, which is conveyed by a single word: understanding. Machine translation has never focused on understanding language. Instead, the field has always tried to \u2018decode\u2019\u2014 to get away without worrying about what understanding and meaning are.\u201d<\/p>\n<p>We call the study of meaning and understanding <strong>semantics <\/strong>and <strong>pragmatics<\/strong>. People\u2019s <strong>real world knowledge <\/strong>plays a key role here as well. To my mind, meaning (only complete when tied to real world knowledge) is the last frontier for AI and language. Today\u2019s mobile\/home voice assistants have definitely not yet mastered meaning. Technologies have made serious headway in resolving structural patterns (<strong>syntax<\/strong>), proper nouns (<strong>Named Entity Recognition<\/strong>) and some other aspects of language. But meaning, that great magical beast, eludes its pursuers. It is really, <em>really <\/em>challenging to computationally model the depth and complexity of human understanding. Because, although language itself is quite complicated, it\u2019s still an impoverished medium for conveying the millions of subtle things we want and are able to convey \u2013 it relies heavily on <strong>context<\/strong>, <strong>implicature<\/strong>, <strong>presupposition<\/strong>,\u00a0<strong>entailment<\/strong>, <strong>prosody<\/strong>, <strong>speaker-listener relationship<\/strong>, etc. I agree again with the author when he says that human-like machines are \u201cnot around the corner.\u201d<\/p>\n<p>I do think that Hofstadter seems to be simultaneously recognizing how hard the task of modeling meaning is, while not giving enough credit for things accomplished. Google Translate is <em>way <\/em>better now than it was at its inception over ten years ago. I also think he glosses over the tool\u2019s main usage \u2013 which is more functional than artistic or poetic. Am I wrong to assume people use Translate much more for a quick word or phrase, when traveling or speaking on the fly, than for translating longer passages of literature? If they\u2019re doing the latter\u2026 per the author\u2019s experimental results, they clearly shouldn\u2019t be.<\/p>\n<p>&nbsp;<\/p>\n<p>What do you think \u2013 about media reportage of technology, machine \u201cintelligence\u201d, Hofstadter\u2019s article? Feel free to comment!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>I\u2019m a Douglas Hofstadter fan. I read his book I Am a Strange Loop years ago, and it remains one of my three favorite non-fiction books, period. I highly recommend it to anyone who is at all interested in the nature of consciousness. The cognitive scientist\u2019s Pulitzer Prize-winning G\u00f6del, Escher, Bach: An Eternal Golden Braid&#8230;<\/p>\n","protected":false},"author":1,"featured_media":67,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_newsletter_tier_id":0,"footnotes":"","jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[20,22,28,31],"tags":[38,116,118,119,121,130,131,162,165],"class_list":["post-66","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-nlu-nlp-ml-ai","category-polemical-topics","category-semantics","category-translation","tag-ai","tag-machine-translation","tag-meaning","tag-media","tag-ml","tag-nlp","tag-nlu","tag-technology-reporting","tag-understanding"],"jetpack_publicize_connections":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>On machine translation, the media, and meaning (a response) - Linguamonium<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/linguamonium.com\/?p=66\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"On machine translation, the media, and meaning (a response) - Linguamonium\" \/>\n<meta property=\"og:description\" content=\"I\u2019m a Douglas Hofstadter fan. 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