{"id":439817,"date":"2022-04-30T13:00:53","date_gmt":"2022-04-30T10:00:53","guid":{"rendered":"https:\/\/en.buradabiliyorum.com\/why-companies-should-stop-trying-to-be-ai-first\/"},"modified":"2022-04-30T13:00:53","modified_gmt":"2022-04-30T10:00:53","slug":"why-companies-should-stop-trying-to-be-ai-first","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/why-companies-should-stop-trying-to-be-ai-first\/","title":{"rendered":"#Why companies should stop trying to be \u201cAI-first\u201d"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_84 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-6a2950f58fa8f\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #dd3333;color:#dd3333\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #dd3333;color:#dd3333\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-6a2950f58fa8f\" checked aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/buradabiliyorum.com\/en\/why-companies-should-stop-trying-to-be-ai-first\/#%E2%80%9CWhy_companies_should_stop_trying_to_be_%E2%80%9CAI-first%E2%80%9D%E2%80%9D\" >&#8220;Why companies should stop trying to be \u201cAI-first\u201d&#8221;<\/a><\/li><\/ul><\/nav><\/div>\n<h1><span class=\"ez-toc-section\" id=\"%E2%80%9CWhy_companies_should_stop_trying_to_be_%E2%80%9CAI-first%E2%80%9D%E2%80%9D\"><\/span>&#8220;Why companies should stop trying to be \u201cAI-first\u201d&#8221;<span class=\"ez-toc-section-end\"><\/span><\/h1>\n<p><img decoding=\"async\" src=\"https:\/\/img-cdn.tnwcdn.com\/image?fit=796%2C417&amp;url=https%3A%2F%2Fcdn0.tnwcdn.com%2Fwp-content%2Fblogs.dir%2F1%2Ffiles%2F2022%2F04%2FAI-first-def3.jpg&amp;signature=1753a22ee2e82b2803da6b3af927f580\" \/><\/p>\n<div>\n                            Artificial intelligence has become a buzzword in the tech industry. Companies are eager to present themselves as \u201cAI-first\u201d and use the terms \u201cAI,\u201d \u201cmachine learning,\u201d and \u201cdeep learning\u201d abundantly in their web and marketing copy.<\/p>\n<p>What are the effects of the current hype surrounding AI? Is it just misleading consumers and end-users or is it also affecting investors and regulators? How is it shaping the mindset for creating products and services? How is the merging of scientific research and commercial product development feeding into the hype?<\/p>\n<p>These are some of the questions that Richard Heimann, Chief AI Officer at Cybraics, answers in his new book\u00a0<em><a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.amazon.com\/Doing-AI-Business-Centric-Examination-Culture\/dp\/1953295738\">Doing AI<\/a>.<\/em>\u00a0Heimann\u2019s main message is that when AI itself becomes our goal, we lose sight of all the important problems we must solve. And by extension, we draw the wrong conclusions and make the wrong decisions.<\/p>\n<p>Machine learning, deep learning, and all other technologies that fit under the umbrella term \u201cAI\u201d should be considered only after you have well-defined goals and problems, Heimann argues. And this is why being AI-first means doing AI last.<\/p>\n<p>One of the <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/download-scripts-themes-apps\/\" data-internallinksmanager029f6b8e52c=\"9\" title=\"Download Scripts &amp; Themes &amp; Apps\" target=\"_blank\" rel=\"noopener\">theme<\/a>s that Heimann returns to in the book is having the wrong focus. When companies talk about being \u201cAI-first,\u201d their goal becomes to somehow integrate the latest and greatest advances in AI research into their products (or\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2018\/07\/23\/artificial-intelligence-wizard-of-oz\/\">at least pretend to do so<\/a>). When this happens, the company starts with the solution and then tries to find a problem to solve with it.<\/p>\n<p>Perhaps a stark example is the trend surrounding\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2021\/12\/20\/artificial-intelligence-large-language-understanding\/\">large language models<\/a>, which are making a lot of noise in mainstream <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/social-mediaa\/\" data-internallinksmanager029f6b8e52c=\"1\" title=\"Social Media\" target=\"_blank\" rel=\"noopener\">media<\/a> and are being presented as <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/general\/\" data-internallinksmanager029f6b8e52c=\"3\" title=\"General\" target=\"_blank\" rel=\"noopener\">general<\/a> problem-solvers in natural language processing. While these models are truly impressive, they are not a silver bullet. In fact, in many cases, when you have a well-defined problem,\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2020\/08\/19\/practical-nlp-review\/\">a simpler model<\/a>\u00a0or even a regular expression or rule-based program can be more reliable than GPT-3.<\/p>\n<p>\u201cWe interpret AI-first as though we ought to literally become solution-first without knowing why. What\u2019s more is that we conceptualize an abstract, idealized solution that we place before problems and customers without fully considering whether it is wise to do so, whether the hype is true, or how solution-centricity impacts\u00a0<em>our<\/em>\u00a0business,\u201d Heimann writes in\u00a0<em>Doing AI<\/em>.<\/p>\n<p>This is a pain point that I\u2019ve encountered time and again in how companies try to\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2021\/01\/06\/how-to-write-an-ai-pitch\/\">pitch their products<\/a>. I often read through a bunch of (sometimes self-contradicting) AI jargon, trying hard to find out what kind of a problem the company solves. Sometimes, I find nothing impressive.<\/p>\n<p>\u201cAnyone talking about AI without the support of a problem is probably not interested in creating a real business or has no idea what a business signifies,\u201d Heimann told\u00a0<em>TechTalks<\/em>. \u201cPerhaps these wannapreneurs are looking for a strategic acquisition. If your dream is to be acquired by Google, you don\u2019t always need a business. Google is one and doesn\u2019t need yours. However, the fact that Google is a business should not be overlooked.\u201d<\/p>\n<p>The AI hype has attracted interest and funding to the field, providing startups and research labs with plenty of money to chase their dreams. But it has also had adverse effects. For one thing, using the ambiguous, anthropomorphic, and vaguely defined term \u201cAI\u201d sets high expectations in clients and users and causes confusion. It can also drive companies into overlooking more affordable solutions and waste resources on unnecessary <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/technology\/\" data-internallinksmanager029f6b8e52c=\"4\" title=\"Technology\" target=\"_blank\" rel=\"noopener\">technology<\/a>.<\/p>\n<p>\u201cWhat is important to remember is that AI is not some monolith. It means different things to different people,\u201d Heimann said. \u201cIt cannot be said without confusing everyone. If you\u2019re a manager and say \u2018AI,\u2019 you have created external goals for problem-solvers. If you say \u2018AI\u2019 without a connection to a problem, you will create misalignments because staff will find problems suitable for some arbitrary solution.\u201d<\/p>\n<p>Academic AI research is focused on pushing the boundaries of <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/sciencee\/\" data-internallinksmanager029f6b8e52c=\"5\" title=\"Science\" target=\"_blank\" rel=\"noopener\">science<\/a>. Scientists study cognition, brain, and behavior in animals and humans to find hints about creating artificial intelligence. They use ImageNet, COCO, GLUE, Winograd, ARC, board <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/game\/\" data-internallinksmanager029f6b8e52c=\"7\" title=\"Game\" target=\"_blank\" rel=\"noopener\">game<\/a>s, video games, and other\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2021\/12\/06\/ai-benchmarks-limitations\/\">benchmarks<\/a>\u00a0to measure progress on AI. Although they know that their findings can serve humankind in the future, they are not worried about whether their technology will be commercialized or productized in the next few months or years.<\/p>\n<p><a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2021\/04\/19\/applied-machine-learning-challenges\/\">Applied AI<\/a>, on the other hand, aims to solve specific problems and ship products to the market. Developers of applied AI systems must meet memory and computational constraints imposed by the environment. They must conform to regulations and meet safety and robustness standards. They measure success in terms of audience, profits, and losses, customer satisfaction, growth, scalability, etc. In fact, in product development, machine learning and deep learning (and any other AI technology) become one of the many tools you use to solve customer problems.<\/p>\n<p>In recent years, especially as commercial entities and big tech companies have\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2019\/08\/26\/deepmind-mustafa-suleyman-commercial-ai\/\">taken the lead in AI research<\/a>, the lines between research and applications have blurred. Today, companies like Google, Facebook, Microsoft, and Amazon account for much of the money that goes into AI research. Consequently, their commercial goals affect the directions that AI research takes.<\/p>\n<p>\u201cThe aspiration to solve everything, instead of something, is the summit for insiders, and it\u2019s why they seek\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2022\/02\/04\/ai-brain-cognitive-plausibility\/\">cognitively plausible solutions<\/a>,\u201d Heimann writes in\u00a0<em>Doing AI<\/em>. \u201cBut that does not change the fact that solutions cannot be all things to all problems, and, whether we like it or not, neither can business. Virtually no business requires solutions that are universal, because business is not universal in nature and often cannot achieve goals \u2018in a wide range of environments.\u2019\u201d<\/p>\n<p>An example is DeepMind, the UK-based AI research lab that was acquired by Google in 2014. DeepMind\u2019s mission is to create safe artificial general intelligence. At the same time, it has a duty to\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2020\/12\/21\/deepminds-annual-report-why-its-hard-to-run-a-commercial-ai-lab\/\">turn in profits for its owner<\/a>.<\/p>\n<p>The same can be said of OpenAI, another research lab that chases the dream of AGI. But being mostly funded by Microsoft, OpenAI must find a balance between scientific research and developing technologies\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2021\/05\/31\/microsoft-gpt-3-and-the-future-of-openai\/\">that can be integrated into Microsoft\u2019s products<\/a>.<\/p>\n<p>\u201cThe boundaries [between academia and business] are increasingly difficult to recognize and are complicated by economic factors and motivations, disingenuous behavior, and conflicting goals,\u201d Heimann said. \u201cThis is where you see companies doing research and publishing papers and behaving similarly to traditional academic institutions to attract academically-minded professionals. You also find academics who maintain their positions while holding industry roles. Academics make inflated claims and create AI-only businesses that solve no problem to grab cash during AI summers. Companies make big claims with academic support. This supports human resource pipelines, generally company prestige, and impacts the \u2018multiplier effect.\u2019\u201d<\/p>\n<p>Time and again, scientists have discovered that solutions to many problems don\u2019t necessarily require human-level intelligence. Researchers have managed to create AI systems that can master\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2019\/01\/02\/humanizing-ai-deep-learning-alphazero\/\">chess, go<\/a>,\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2022\/02\/07\/deepmind-alphacode-competitive-programming\/\">programming contests<\/a>, and\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2019\/09\/09\/aristo-ai-science-exam\/\">science exams<\/a>\u00a0without reproducing the human reasoning process.<\/p>\n<p>These findings often create debates around whether AI should simulate the human brain or aim at producing acceptable results.<\/p>\n<p>\u201cThe question is relevant because AI doesn\u2019t solve problems in the same way as humans,\u201d Heimann said. \u201cWithout human cognition, these solutions will not solve any other problem.\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2020\/04\/09\/what-is-narrow-artificial-intelligence-ani\/\">What we call \u2018AI\u2019 is narrow<\/a>\u00a0and only solves problems they were intended to solve. That means business leaders still need to find problems that matter and either find the right solution or design the right solution to solve those problems.\u201d<\/p>\n<p>Heimann also warned that AI solutions that do not act like humans will fail in unique\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2020\/12\/16\/machine-learning-adversarial-attacks-against-machine-learning-time-bomb\/\">ways that are unlike humans<\/a>. This has important implications for safety, security, fairness, trustworthiness, and many other social issues.<\/p>\n<p>\u201cIt necessarily means we should use \u2018AI\u2019 with discretion and never on simple problems that humans could solve easily or when the cost of error is high, and accountability is required,\u201d Heimann said. \u201cAgain, this brings us back to the nature of the problem we want to solve.\u201d<\/p>\n<p>In another sense, the question of whether AI should simulate the human brain lacks relevance because most AI research cares very little about cognitive plausibility or biological plausibility, Heimann believes.<\/p>\n<p>\u201cI often hear business-minded people espouse nonsense about artificial neural networks being \u2018inspired by,\u2026\u2019 or \u2018roughly mimic\u2019 the brain,\u201d he said. \u201cThe neuronal aspect of artificial neural networks is just a window dressing for computational functionalism that ignores all differences between silicon and biology anyway. Aside from a few counterexamples, artificial neural network research still focuses on functionalism and does not care about improving neuronal plausibility. If insiders generally don\u2019t care about bridging the gap between biological and artificial neural networks, neither should you.\u201d<\/p>\n<p>In\u00a0<em>Doing AI<\/em>, Heimann stresses that to solve sufficiently complex problems, we may use advanced technology like machine learning, but what that technology is called means less than why we used it. A business\u2019s survival doesn\u2019t rely on the name of a solution, the philosophy of AI, or the definition of intelligence.<\/p>\n<p>He writes: \u201cRather than asking if AI is about simulating the brain, it would be better to ask, \u2018Are businesses required to use artificial neural networks?\u2019 If that is the question, then the answer is no. The presumption that you need to use some arbitrary solution before you identify a problem is solution guessing. Although artificial neural networks are very popular and almost perfect in the narrow sense that they can fit complex functions to data\u2014and thus compress data into useful representations\u2014they should never be the goal of business, because approximating a function to data is rarely enough to solve a problem and, absent of solving a problem, never the goal of business.\u201d<\/p>\n<p>When it comes to developing products and business plans, the problem comes first, and the technology follows. Sometimes, in the context of the problem, highlighting the technology makes sense. For example, a \u201cmobile-first\u201d application suggests that it addresses a problem that users mainly face when they\u2019re not sitting behind a computer. A \u201ccloud-first\u201d solution suggests that storage and processing are mainly done in the cloud to make the same information available across multiple devices or to avoid overloading the computational resources of end-user devices. (It is worth noting that those two terms also became meaningless buzzwords after being overused. They were meaningful in the years when companies were transitioning from on-premise installations to the cloud and from web to mobile. Today, every application is expected to be available on mobile and to have a strong cloud infrastructure.)<\/p>\n<p>But what does \u201cAI-first\u201d say about the problem and context of the application and the problem it solves?<\/p>\n<p>\u201cAI-first is an oxymoron and an ego <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/trip-and-travel\/\" data-internallinksmanager029f6b8e52c=\"10\" title=\"Trip &amp; Travel\" target=\"_blank\" rel=\"noopener\">trip<\/a>. You cannot do something before you understand the circumstances that make it necessary,\u201d Heimann said. \u201cAI strategies, such as AI-first, could mean anything. Business strategy is too broad when it includes everything or things it shouldn\u2019t, like intelligence. Business strategy is too narrow when it fails to include things that it should, like mentioning an actual problem or a real-world customer. Circular strategies are those in which a solution defines a goal, and the goal defines that solution.<\/p>\n<p>\u201cWhen you lack problem-, customer-, and market-specific information, teams will fill in the blanks and work on whatever they think of when they think of AI. Nevertheless, you are unlikely to find a customer inside an abstract solution like \u2018AI.\u2019 Therefore, artificial intelligence cannot be a business goal, and when it is, strategy is more complex verging on impossible.\u201d<\/p>\n<p><em>This article was originally written by Ben Dickson and published by Ben Dickson on<span>\u00a0<\/span><a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/\">TechTalks<\/a>, a publication that examines trends in technology, how they affect the way we live and do business, and the problems they solve. But we also discuss the evil side of technology, the darker implications of new tech, and what we need to look out for. You can read the original article<span>\u00a0<a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/bdtechtalks.com\/2022\/04\/25\/doing-ai\/\">here<\/a><\/span>.<\/em>\n                        <\/div>\n<blockquote><p><strong><span style=\"color: #ff6600;\">If you liked the article, do not forget to share it with your friends. Follow us on\u00a0<span style=\"color: #ff0000;\"><a style=\"color: #ff0000;\" href=\"https:\/\/news.google.com\/publications\/CAAqBwgKMLG0nwswvr63Aw\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Google News<\/a><\/span>\u00a0too, click on the star and choose us from your favorites.<\/span><\/strong><\/p><\/blockquote>\n<blockquote>\n<p style=\"text-align: center;\">For forums sites go to <span style=\"color: #ff9900;\"><a style=\"color: #ff9900;\" href=\"https:\/\/forum.buradabiliyorum.com\/\" target=\"_blank\" rel=\"noopener\">Forum.BuradaBiliyorum.Com<\/a><\/span><\/strong><\/p>\n<\/blockquote>\n<blockquote>\n<p style=\"text-align: center;\"><strong>If you want to read more like this article, you can visit our <span style=\"color: #ff9900;\"><a style=\"color: #ff9900;\" href=\"https:\/\/en.buradabiliyorum.com\/technology\/\" target=\"_blank\" rel=\"noopener\">Technology category.<\/a><\/span><\/strong><\/p>\n<\/blockquote>\n<p><span style=\"color: black;\"><a style=\"color: #ff9900;\" href=\"https:\/\/thenextweb.com\/news\/why-companies-should-stop-be-ai-first\" target=\"_blank\" rel=\"noopener\">Source<\/a><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>&#8220;Why companies should stop trying to be \u201cAI-first\u201d&#8221; Artificial intelligence has become a buzzword in the tech industry. Companies are eager to present themselves as \u201cAI-first\u201d and use the terms \u201cAI,\u201d \u201cmachine learning,\u201d and \u201cdeep learning\u201d abundantly in their web and marketing copy. What are the effects of the current hype surrounding AI? Is it&#8230;<\/p>\n","protected":false},"author":1,"featured_media":439818,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"https:\/\/img-cdn.tnwcdn.com\/image\/neural?filter_last=1&fit=1280,640&url=https:\/\/cdn0.tnwcdn.com\/wp-content\/blogs.dir\/1\/files\/2022\/04\/AI-first-def3.jpg&signature=be9017619396bbe48941e1ffd9fe74d5","fifu_image_alt":"","footnotes":""},"categories":[18],"tags":[],"class_list":["post-439817","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"_links":{"self":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/439817","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/comments?post=439817"}],"version-history":[{"count":0,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/439817\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media\/439818"}],"wp:attachment":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media?parent=439817"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/categories?post=439817"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/tags?post=439817"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}