{"id":3941,"date":"2016-10-10T20:56:39","date_gmt":"2016-10-10T20:56:39","guid":{"rendered":"http:\/\/www.listenandlearn.org\/blog\/?p=3941"},"modified":"2017-08-23T15:47:20","modified_gmt":"2017-08-23T15:47:20","slug":"how-does-a-i-compare-to-human-intelligence","status":"publish","type":"post","link":"https:\/\/www.listenandlearn.org\/blog\/how-does-a-i-compare-to-human-intelligence\/","title":{"rendered":"How Does A.I. Compare to Human Intelligence?"},"content":{"rendered":"<div id=\"attachment_3947\" style=\"width: 510px\" class=\"wp-caption aligncenter\"><a href=\"http:\/\/www.listenandlearn.org\/blog\/wp-content\/uploads\/2016\/10\/Gif_1-21.gif\"><img decoding=\"async\" aria-describedby=\"caption-attachment-3947\" class=\"wp-image-3947 size-full\" src=\"http:\/\/www.listenandlearn.org\/blog\/wp-content\/uploads\/2016\/10\/Gif_1-21.gif\" alt=\"\" width=\"500\" height=\"267\" \/><\/a><p id=\"caption-attachment-3947\" class=\"wp-caption-text\">GIF via <a href=\"https:\/\/giphy.com\/gifs\/terminator-gif-arnold-schwarzenegger-JDKxRN0Bvmm2c\" target=\"_blank\">Giphy<\/a><\/p><\/div>\n<p>For the Sci-Fi fans among us, we have this famous <em>Terminator<\/em> quote<span style=\"color: #222222;\">\u2014<\/span>and gesture<span style=\"color: #222222;\">\u2014<\/span>down pat. Some of us grew up using it, some of the geekier ones might argue that \u201cI need your clothes, your boots and your motorcycle\u201d is a much more memorable quote from the franchise, but this one is the one that really sticks with us. Maybe playing into our nightmares about the day the machines take over (April 19th, 2011, amirite?).<\/p>\n<p>But before we begin to really worry that the giants Apple and Google are our Cyberdynes and things like deep learning will ultimately lead to a neural net-based conscious group mind and artificial general intelligence that will take over our internet akin to Skynet, what if we can bite the bullet of machines vs humans by making our machines <i>behave<\/i> human? Is that even a realistic possibility? And, given how flawed humanity is at times, would we really <i>want<\/i> our machines to behave like us?<\/p>\n<p>Let us explain our reasoning before we begin to incite panic\u2026<\/p>\n<p><b>Deep learning<\/b><\/p>\n<p>Deep learning is, essentially, machines learning for themselves and by themselves, through a series of intricate and complex mathematical calculations that roughly simulate what is happening in our brains when our interconnected layers of neurons fire off messages to one another. In essence, deep learning simulates the way that humans think without the \u2018benefit\u2019 our alleged common sense.<\/p>\n<p>Deep learning, then, is an artificial neural network (...say it with us\u2026 <i>Skynet\u2026<\/i>) that developers intend to use to second guess our wants and intentions, in an effort to make our progress more.... progress-able. Perhaps one day deep learning will be applied during surgery, working alongside the medically fittest to help with snap decisions that could mean the difference between life and death. Currently, however, if you want to <i>witness<\/i> deep learning in action, look no further than Facebook. Facebook has been using <a href=\"http:\/\/www.infoworld.com\/article\/3115466\/artificial-intelligence\/facebook-taps-deep-learning-for-customized-feeds.html\" target=\"_blank\">deep learning techniques<\/a> to customise our feeds for a little while now, which poses two questions: 1, why does Facebook\u2019s deep learning keep <i>suggesting<\/i> we watch videos of baby sloths, and, 2, is Mark Zuckerberg our very own Miles Bennett Dyson?<\/p>\n<p><b>Language processing<\/b><\/p>\n<p>Linguists may be pleased or thoroughly incensed by the idea of deep learning processes assisting with the natural order of things in language learning, but there is in fact a field of computer science dedicated to artificial intelligence, and computational linguistics focussing entirely on the interactions between computers and humans (<i>Natural Language Processing<\/i>, or <i>NLP<\/i>).<\/p>\n<p>Google has recently added NLP to its <a href=\"http:\/\/www.zdnet.com\/article\/google-adds-natural-langauge-processing-to-drive-search\/\" target=\"_blank\">Drive search<\/a>, which essentially means searching for your files in Google Drive will become more like using the normal Google search engine. Don\u2019t see the difference? Well, if you haven\u2019t already noticed, gone are the days when if you wanted to search for something you had to use a series of keywords to find what you were looking for. Now you can just type what you are thinking: <i>show me documents shared with &gt;&gt;&gt;<\/i>, for example, will now bring up exactly what you are after. Clearly this isn\u2019t exactly innovative: many of us \u2018speak\u2019 to Siri daily to help us with our daily lives, with our devices adapting to our languages rather than all of us learning to speak in SQL or Javascript in the hope of being able to converse with <i>them<\/i>.<\/p>\n<p style=\"text-align: center;\"><b>Learning a new language? Check out our\u00a0<\/b><b><a href=\"https:\/\/www.listenandlearn.org\/level-tests.php\">free placement test<\/a>\u00a0<\/b><b>to see how your level measures up!<\/b><\/p>\n<p>There is, of course, a discourse here, because the internet does tend to become a bit of a <a href=\"http:\/\/www.listenandlearn.org\/blog\/internet-language-a-language-blackhole\/\" target=\"_blank\">language blackhole<\/a>. English is well-represented, as are many other languages using the Latin alphabet. But that NLP becomes trickier when there are less sources for AI to work with: the lack of representation in <a href=\"https:\/\/www.inverse.com\/article\/21318-why-a-i-can-struggle-to-understand-arabic\" target=\"_blank\">Arabic<\/a>, for example, means that there is less opportunity for our favourite technologies to recognise the language and effectively <i>learn<\/i> it, leading to a great language and therefore NLP disparity.<\/p>\n<p><b>Teaching our machines<\/b><\/p>\n<div id=\"attachment_3946\" style=\"width: 660px\" class=\"wp-caption aligncenter\"><a href=\"http:\/\/www.listenandlearn.org\/blog\/wp-content\/uploads\/2016\/10\/Photo_1-1.jpg\"><img decoding=\"async\" aria-describedby=\"caption-attachment-3946\" class=\"wp-image-3946 size-full\" src=\"http:\/\/www.listenandlearn.org\/blog\/wp-content\/uploads\/2016\/10\/Photo_1-1.jpg\" alt=\"\" width=\"650\" height=\"365\" srcset=\"https:\/\/www.listenandlearn.org\/blog\/wp-content\/uploads\/2016\/10\/Photo_1-1.jpg 650w, https:\/\/www.listenandlearn.org\/blog\/wp-content\/uploads\/2016\/10\/Photo_1-1-300x168.jpg 300w\" sizes=\"(max-width: 650px) 100vw, 650px\" \/><\/a><p id=\"caption-attachment-3946\" class=\"wp-caption-text\">Photo via <a href=\"https:\/\/en.wikipedia.org\/wiki\/Computer_keyboard\" target=\"_blank\">Wikipedia<\/a><\/p><\/div>\n<p>Which leads us to the point we were considering earlier. When we <i>teach<\/i> computers, and by <i>teach<\/i>, we mean provide with masses of information and let the computers do their processing thing, the data we choose to give them can, theoretically, influence those machines and pass on our biases and prejudices.<\/p>\n<p>Think about the way we learn as children. We learn to smile when we see a cute furry animal but draw back in fear when we see a gnarly-looking insect. We learn our positives and negatives from those around us, and in effect, when computers are <i>learning<\/i> human languages they become those children: learning what is deemed <i>good<\/i> and <i>bad<\/i> by what <i>we <\/i>teach them.<\/p>\n<p>Don\u2019t believe us? A <a href=\"http:\/\/qz.com\/768567\/when-computers-learn-human-languages-they-also-learn-human-prejudices\/\" target=\"_blank\">recent study<\/a> out of the <a href=\"http:\/\/randomwalker.info\/publications\/language-bias.pdf\" target=\"_blank\">University of Princeton<\/a> demonstrated that machine-learning algorithms showed strong gender bias related to profession based on the extraction of around a trillion words taken from English language texts from the internet. No actual biases were implied, just a sample of the English in use out there on the web, and this is what the algorithm came back with. <i>Management<\/i> means <i>man<\/i>, <i>family<\/i> means <i>woman<\/i>.<\/p>\n<p>With that in mind, where would the line be drawn? If we can teach fear and intolerance to each other with carefully worded phrases and both subliminal and in-your-face propaganda, does it not follow that we can do the same disservice to our machines as well? Are we leading ourselves to a dystopian future of Skynet-esque <i>1984<\/i>, with controlled language and the control of others we just don\u2019t <i>like<\/i> or think are somehow beneath us?<\/p>\n<p>A sobering thought, perhaps.<\/p>\n<p>Next up on our look into AI and its impact on language, or perhaps language\u2019s impact on AI, we will introduce you to <a href=\"https:\/\/www.theguardian.com\/technology\/2014\/jun\/09\/eugene-person-human-computer-robot-chat-turing-test\" target=\"_blank\">Eugene<\/a> and talk about the outcome and significance of the Turing Test, see if our future really is destined to be crushed beneath the foot of a cybernetic organism. Until then<span style=\"color: #222222;\">\u2014<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>For the Sci-Fi fans among us, we have this famous Terminator quote\u2014and gesture\u2014down pat. Some of us grew up using it, some of the geekier ones might argue that \u201cI need your clothes, your boots and your motorcycle\u201d is a much more memorable quote from the franchise, but this one is the one that really(\u2026)<\/p>\n<div class=\"row\">\n<div class=\"col-md-12 text-right\">\n\t \t\t\t\t<a class=\"btn btn-primary btn-xs\" href=\"https:\/\/www.listenandlearn.org\/blog\/how-does-a-i-compare-to-human-intelligence\/\">CONTINUE READING &raquo;<\/a>\n\t\t\t<\/div>\n<\/p><\/div>\n","protected":false},"author":37,"featured_media":3946,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[236,17,9],"tags":[568,441,567,66,470,304,160],"class_list":["post-3941","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-must-know","category-news-politics-religion-history-law","category-technology","tag-computer-learning","tag-computer-science","tag-deep-learning","tag-language","tag-learn-languages","tag-learning","tag-technology-2"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.8 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How Does A.I. 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As a writer, I get to cover a range of topics by working for a variety of clients in a number of industries. My focus when writing for Listen and Learn is on language and travel, but away from that, I like to write a lot about animals and the environment. Travelling while writing gives me a fresh perspective for all the things I write and allows me to consider everything from opposing points of view thanks to the people I meet along the way. Europe is an amazing place to travel. The countries vary so much, as do the languages, cuisines and ways of life. Though underneath all of that, travelling has really taught me that people are just people, and that we have more similarities than we do differences. We talk a lot at Listen and Learn about languages teaching us so much more than purely vocabulary and grammar, and it is true; there is nothing as exciting as getting to talk to someone you might not normally get to, just because you have made the effort to learn some of their language. Teaching English has given me further insight into the importance of understanding other languages and cultures. I've taught lessons on beaches about the climate crisis and the impact of oil spills on marine animals, and helped students in train stations to practise booking train tickets and make travel plans. I've worked with laboratory technicians in large conglomerates and newly qualified architects starting their own companies; people with completely different lives to mine. And it has been a privilege getting to know them all! Though the most rewarding thing about teaching is seeing students achieve their goals. 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