Beyond Intelligence Augmentation: The Next Phase of AI & Market Research - GRBN.ORG<\/title>\n<meta name=\"description\" content=\"Advances in artificial intelligence are set to dramatically impact market research in the short term. 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PG Slots Cassino{"id":8365,"date":"2017-10-16T08:20:33","date_gmt":"2017-10-16T06:20:33","guid":{"rendered":"http:\/\/grbnnews.com\/?p=8365"},"modified":"2017-10-14T04:15:43","modified_gmt":"2017-10-14T02:15:43","slug":"beyond-intelligence-augmentation-next-phase-ai-market-research","status":"publish","type":"post","link":"https:\/\/grbn.org\/beyond-intelligence-augmentation-next-phase-ai-market-research\/","title":{"rendered":"Beyond Intelligence Augmentation: The Next Phase of AI & Market Research"},"content":{"rendered":"Advances in artificial intelligence are set to dramatically impact market research in the short term. Specifically, narrow AI will enable the automation of individual research tasks. During this phase of Intelligence Augmentation AI will act to augment the capabilities of researches; enabling one person to achieve what previously would have taken an entire team.\r\n\r\nThe next phase of AI\u2019s impact will happen as AI becomes increasingly generalized; extending automation out to functions which typically are not in the scope of a market researcher – such as content creation. The application of reinforcement learning based approaches to simultaneously solve market research & design challenges will signal the transition into this phase\u2014 and potentially the end of market research as we know it.\r\n

What is reinforcement learning? And how might it impact market research?<\/strong><\/blockquote>\r\nReinforcement learning<\/a> (RL) involves an intelligent agent which takes actions and learns from the outcome of those actions in order to become increasingly better at achieving a goal.\r\n\r\nFormulating a problem into one which can be tackled by an RL Agent (RLA) requires defining three things:\r\n
\r\n \t
What is the RL\u2019s goal<\/strong>?<\/li>\r\n \t
What actions<\/strong> can the RL take?<\/li>\r\n \t
What does it observe<\/strong> in order to learn how its actions impact its goal?<\/li>\r\n<\/ol>\r\nAlready, AI researchers have developed RLAs capable of playing video games<\/a> which require complex strategy and planning at a superhuman level. In this case the RLA\u2019s goal<\/strong> is to achieve the highest score possible, the actions<\/strong> it can take are virtually \u2018pushing’ the game controller\u2019s buttons and it observes<\/strong> the video game screen in order to learn how its actions impact the state of the game and ultimately the score.\r\n\r\nTo see how this approach can map to something at the intersection of market research and design, lets consider how an ad is created, tested, & then launched. Specifically, lets consider a simple ad like the ones you see in Google search results, and define the purpose of the ad to drive a person to click it and then sign up for some service.\r\n\r\nIn this case, we can define the RLA\u2019s goal<\/strong> as maximizing the number of people who click the ad and sign up (given a set of constraints, like a budget). The actions<\/strong> it can take are to generate the content of the ad and make ad buys against various demographics. During this process it observes<\/strong> the click through rates & sign up rates of the various ads & targeting profiles.\r\n\r\nAt first, one can imagine it learning to generate ads that get a high rate of click through because it has learned that a certain set of words get people to click & that a person clicking is correlated with them signing up (which is the goal). With more time it may learn that while a certain set of ads generate strong click through rates, the rate of signups after clicking through varies greatly. As it then hones in on the ads that achieve both high click through & sign up rates, it may lean how those rates vary across demographics and optimize its targeting accordingly.\r\n\r\nWith this example we can see how an RLA could learn to produce ads that not only drive click throughs, but specifically those which are likely convert to a sign up, and then learn who to best target those ads at. From a financial perspective, the RLA would learn to continuously reduce the cost per sign up \u2014 a clearly quantifiable ROI .\r\n
ROI and Morality<\/strong><\/blockquote>\r\nWhile this seems ideal from an economic perspective, morally it does leave many open questions about how such an ROI optimizing RLA might impact society (more on that here<\/a>).\r\n\r\n $\"Andrew_Konya\"$ Andrew Konya\r\n\r\nCEO at Remesh.ai\r\n\r\nAndrew Konya is the founder and CEO of Remesh. \u00a0 A computational physicist by training, he\u00a0has\u00a0spent the past 8 years developing and applying artificial intelligence and machine\u00a0learning algorithms to problems in material science,\u00a0bio-sensing, traffic, image analysis and language.\u00a0 His most recent focus is on developing artificial intelligence to engage and understand large crowds of people with Remesh.<\/em>\r\n\r\nFind out more at Remesh at\u00a0remesh.ai<\/a>\r\n\r\n ","protected":false},"excerpt":{"rendered":"
Advances in artificial intelligence are set to dramatically impact market research in the short term. Specifically, narrow AI will enable the automation of individual research tasks. During this phase of Intelligence Augmentation AI will act to augment the capabilities of researches; enabling one person to achieve what previously would have taken an entire team. The […]<\/p>\n","protected":false},"author":1,"featured_media":8370,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[227,21,57,19],"tags":[81],"yoast_head":"\nBeyond Intelligence Augmentation: The Next Phase of AI & Market Research - GRBN.ORG<\/title>\n<meta name=\"description\" content=\"Advances in artificial intelligence are set to dramatically impact market research in the short term. AI will enable the automation of individual tasks\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/grbn.org\/beyond-intelligence-augmentation-next-phase-ai-market-research\/\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"GRBN_News\" \/>\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\":\"WebPage\",\"@id\":\"https:\/\/grbn.org\/beyond-intelligence-augmentation-next-phase-ai-market-research\/\",\"url\":\"https:\/\/grbn.org\/beyond-intelligence-augmentation-next-phase-ai-market-research\/\",\"name\":\"Beyond Intelligence Augmentation: The Next Phase of AI & Market Research - GRBN.ORG\",\"isPartOf\":{\"@id\":\"https:\/\/grbn.org\/#website\"},\"datePublished\":\"2017-10-16T06:20:33+00:00\",\"dateModified\":\"2017-10-14T02:15:43+00:00\",\"author\":{\"@id\":\"https:\/\/grbn.org\/#\/schema\/person\/e3e6f44d4cd62a5881eeb240fe5184a0\"},\"description\":\"Advances in artificial intelligence are set to dramatically impact market research in the short term. 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