{"id":176405,"date":"2024-01-16T13:02:53","date_gmt":"2024-01-16T12:02:53","guid":{"rendered":"https:\/\/datascientest.com\/en\/?p=176405"},"modified":"2024-01-16T13:25:14","modified_gmt":"2024-01-16T12:25:14","slug":"xai-or-explainable-artificial-intelligence-what-is-it-about","status":"publish","type":"post","link":"https:\/\/datascientest.com\/en\/xai-or-explainable-artificial-intelligence-what-is-it-about","title":{"rendered":"XAI or eXplainable Artificial Intelligence: What is it about?"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"176405\" class=\"elementor elementor-176405\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t\t<div class=\"elementor-element elementor-element-bede84b e-flex e-con-boxed e-con\" data-id=\"bede84b\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-c0bec63 elementor-widget elementor-widget-heading\" data-id=\"c0bec63\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-heading-title{padding:0;margin:0;line-height:1}.elementor-widget-heading .elementor-heading-title[class*=elementor-size-]>a{color:inherit;font-size:inherit;line-height:inherit}.elementor-widget-heading .elementor-heading-title.elementor-size-small{font-size:15px}.elementor-widget-heading .elementor-heading-title.elementor-size-medium{font-size:19px}.elementor-widget-heading .elementor-heading-title.elementor-size-large{font-size:29px}.elementor-widget-heading .elementor-heading-title.elementor-size-xl{font-size:39px}.elementor-widget-heading .elementor-heading-title.elementor-size-xxl{font-size:59px}<\/style><h2 class=\"elementor-heading-title elementor-size-default\"><p>One of the great challenges of Machine Learning is to produce systems capable of explaining their decisions and actions to human users.<\/p>\n<p>Thus, the explicability of Artificial Intelligences (XAI) has become one of the challenges of Machine Learning and is now an integral part of the job of Data Scientists, who are called upon to convince users of the acceptability of their models' reasoning.<\/p>\n<\/h2>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-0a34b01 e-flex e-con-boxed e-con\" data-id=\"0a34b01\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-d261997 elementor-widget elementor-widget-heading\" data-id=\"d261997\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">What is the explicability of a model? (XAI)<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d262a80 elementor-widget elementor-widget-text-editor\" data-id=\"d262a80\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-text-editor.elementor-drop-cap-view-stacked .elementor-drop-cap{background-color:#69727d;color:#fff}.elementor-widget-text-editor.elementor-drop-cap-view-framed .elementor-drop-cap{color:#69727d;border:3px solid;background-color:transparent}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap{margin-top:8px}.elementor-widget-text-editor:not(.elementor-drop-cap-view-default) .elementor-drop-cap-letter{width:1em;height:1em}.elementor-widget-text-editor .elementor-drop-cap{float:left;text-align:center;line-height:1;font-size:50px}.elementor-widget-text-editor .elementor-drop-cap-letter{display:inline-block}<\/style>\t\t\t\t<p>XAI, or &#8220;<strong>eXplainable Artificial Intelligence<\/strong>&#8220;, refers to a set of processes and methods used to explain every result calculated by an <a href=\"https:\/\/datascientest.com\/en\/artificial-intelligence-definition\">Artificial Intelligence<\/a> in a simple, understandable way. It&#8217;s a field of <a href=\"https:\/\/datascientest.com\/en\/boosting-business-with-3-essential-machine-learning-algorithms\">Machine Learning<\/a> that aims to justify as precisely as possible a result given by a model.<\/p><p>In effect, this AI helps anyone who is not a technical specialist or Data Scientist to understand why an algorithm has given such results.<\/p><p>For example, if you&#8217;ve <a href=\"https:\/\/datascientest.com\/en\/mlops-devops-applied-to-machine-learning-projects\">trained a Machine Learning (ML) model with financial data<\/a> to guide an investor in choosing an investment sector. With <strong>explainable AI<\/strong> you are then able to explain why one option was selected over another, and why the recommended investment <strong>options are best suited to his situation.<\/strong><\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-d6fd4e1 e-flex e-con-boxed e-con\" data-id=\"d6fd4e1\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-e1b7c08 elementor-widget elementor-widget-heading\" data-id=\"e1b7c08\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">XAI, Why explainability?<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d8f48c8 elementor-widget elementor-widget-text-editor\" data-id=\"d8f48c8\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>Explainable AI<\/strong> is essential, both for developers and <a href=\"https:\/\/datascientest.com\/en\/essential-data-scientist-tools-for-your-daily-workflow\">data scientists<\/a>, and for users, for several good reasons:<\/p><ul><li><a href=\"https:\/\/datascientest.com\/en\/unpacking-the-power-of-integrated-development-environments-ides\">Enabling developers<\/a> to update and improve models, as well as measure their effectiveness.<\/li><li>Since the <a href=\"https:\/\/datascientest.com\/en\/understanding-gdpr-definition-and-its-crucial-impact-on-businesses\">implementation of the GDPR<\/a> it has been mandatory to be able to explain all results (scores, segmentation, etc.) that relate to individuals. This is now possible thanks to XAI.<\/li><li>Bring more concrete results by providing valuable information on a company&#8217;s key indicators.<\/li><li>Understanding the &#8220;why&#8221; will enable you to make better use of the results to prepare and adapt your presentation.<\/li><li>For example, in the case of a telephone operator, an advisor will need to address a customer who is likely to cancel his contract because he is looking for a cheaper offer, differently from a customer who is about to move house.<\/li><li>Understanding the <a href=\"https:\/\/datascientest.com\/en\/classification-algorithms-definition-and-main-models\">reasoning behind algorithms<\/a> will enable end-users to realize that they are based on logical principles.<\/li><\/ul>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-af7abb2 elementor-widget elementor-widget-image\" data-id=\"af7abb2\" data-element_type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<style>\/*! elementor - v3.15.0 - 02-08-2023 *\/\n.elementor-widget-image{text-align:center}.elementor-widget-image a{display:inline-block}.elementor-widget-image a img[src$=\".svg\"]{width:48px}.elementor-widget-image img{vertical-align:middle;display:inline-block}<\/style>\t\t\t\t\t\t\t\t\t<figure class=\"wp-caption\">\n\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/datascientest.com\/wp-content\/uploads\/2023\/04\/XAI.png\" title=\"\" alt=\"\" loading=\"lazy\" \/>\t\t\t\t\t\t\t\t\t\t\t<figcaption class=\"widget-image-caption wp-caption-text\"><\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-750be60 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"750be60\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/en\/machine-learning-engineer-course\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Mastering AI explainability<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-f9a364a e-flex e-con-boxed e-con\" data-id=\"f9a364a\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a4bf629 elementor-widget elementor-widget-heading\" data-id=\"a4bf629\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Methods for implementing XAI<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d1dc9a1 elementor-widget elementor-widget-text-editor\" data-id=\"d1dc9a1\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>There are a number of ways to bring transparency and understanding to <a href=\"https:\/\/datascientest.com\/en\/exploring-the-boundaries-of-artificial-intelligence\">Artificial Intelligence<\/a>. The main approaches are as follows.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e6ed6b2 elementor-widget elementor-widget-heading\" data-id=\"e6ed6b2\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Layer-wise Relevance Propagation (LRP) :<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7b2f609 elementor-widget elementor-widget-text-editor\" data-id=\"7b2f609\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>This is a technology that enables the specific features of input vectors to be defined.<\/p><p>It is applicable to <a href=\"https:\/\/datascientest.com\/en\/convolutional-neural-network-everything-you-need-to-know\">neural network models<\/a>, where inputs can be images, videos or text.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bd3f5a4 elementor-widget elementor-widget-heading\" data-id=\"bd3f5a4\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Counterfactual Method :<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cd01581 elementor-widget elementor-widget-text-editor\" data-id=\"cd01581\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>A counterfactual explanation describes a causal situation in the form: &#8220;<strong>If X had not happened, Y would not have happened<\/strong>&#8220;.<\/p><p>This technology refers to the way in which data inputs are modified once a result has been obtained. The extent to which the result has been modified is then observed.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c8eed17 elementor-widget elementor-widget-heading\" data-id=\"c8eed17\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Local Interpretable Model-Agnostic Explanations (LIME) :<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-fd2c13f elementor-widget elementor-widget-text-editor\" data-id=\"fd2c13f\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p><strong>LIME<\/strong> is a method based on a globalist approach that aims to explain any mechanical classifier and the resulting prognoses. It is one of the so-called local methods, in the sense that it gives explanations of model choice on a value-by-value basis, rather than globally <a href=\"https:\/\/datascientest.com\/en\/datasets-top-5-places-to-find-quality-datasets\">over an entire dataset.<\/a> With such a method, even non-specialists can access the data and the methods.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-490cfef elementor-widget elementor-widget-heading\" data-id=\"490cfef\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h4 class=\"elementor-heading-title elementor-size-default\">Rationalisation :<\/h4>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e4f3d4a elementor-widget elementor-widget-text-editor\" data-id=\"e4f3d4a\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>This is a method used especially for AI-based robots such as <a href=\"https:\/\/datascientest.com\/en\/chatgpt-how-does-this-nlp-algorithm-work\">ChatGPT.<\/a> Here, the machine is given autonomy to explain its actions.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7fb318a e-flex e-con-boxed e-con\" data-id=\"7fb318a\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-a7b8a13 elementor-widget elementor-widget-heading\" data-id=\"a7b8a13\" data-element_type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Conclusion about XAI<\/h3>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c0cbf84 elementor-widget elementor-widget-text-editor\" data-id=\"c0cbf84\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<p>The transparent nature of <strong>explainable AI offers<\/strong> numerous advantages for decision-making. XAI helps interpret the complex results produced by Machine Learning models. It also enables developers to update and improve models. It also offers the added advantage of good data traceability.<\/p>\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-eb71e91 elementor-align-center button-principale elementor-widget elementor-widget-button\" data-id=\"eb71e91\" data-element_type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm elementor-animation-grow\" href=\"https:\/\/datascientest.com\/en\/machine-learning-engineer-course\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-text\">Start a Machine Learning Engineer course<\/span>\n\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-45288a6 e-flex e-con-boxed e-con\" data-id=\"45288a6\" data-element_type=\"container\" data-settings=\"{&quot;content_width&quot;:&quot;boxed&quot;}\">\n\t\t\t\t\t<div class=\"e-con-inner\">\n\t\t\t\t<div class=\"elementor-element elementor-element-2561a7b elementor-widget elementor-widget-html\" data-id=\"2561a7b\" data-element_type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [{\n    \"@type\": \"Question\",\n    \"name\": \"What is model explainability?\",\n    \"acceptedAnswer\": {\n      \"@type\": \"Answer\",\n      \"text\": \"XAI, or \"eXplainable Artificial Intelligence\", refers to a set of processes and methods for explaining every result computed by an Artificial Intelligence in a simple and understandable way. 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Bringing more concrete results by offering valuable information on a company's key indicators.\"\n    }\n  }]\n}\n<\/script>\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>One of the great challenges of Machine Learning is to produce systems capable of explaining their decisions and actions to human users. Thus, the explicability of Artificial Intelligences (XAI) has become one of the challenges of Machine Learning and is now an integral part of the job of Data Scientists, who are called upon to [&hellip;]<\/p>\n","protected":false},"author":67,"featured_media":176410,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"content-type":"","inline_featured_image":false},"categories":[2420],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v21.7 (Yoast SEO v21.7) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>XAI or eXplainable Artificial Intelligence: What is it about?<\/title>\n<meta name=\"description\" content=\"Explainable AI or XAI is crucial as AI technologies become more integrated into various aspects of our lives. 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