{"id":709,"date":"2021-05-13T20:14:17","date_gmt":"2021-05-13T20:14:17","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/?post_type=pattern&#038;p=709"},"modified":"2023-10-25T07:51:34","modified_gmt":"2023-10-25T14:51:34","slug":"g11-g-what-if-explanations","status":"publish","type":"pattern","link":"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/pattern\/g11-g-what-if-explanations\/","title":{"rendered":"Pattern 11G: \u201cWhat if?\u201d explanations"},"content":{"rendered":"\n\n<div class=\"toolkit-heading-with-image-block\">\n\t\n\n<h2 class=\"wp-block-heading\">Pattern 11G: \u201cWhat if?\u201d explanations<\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/uploads\/prod\/2023\/05\/yellow-header-bar-1536x14-5-23.png\" alt=\"\" \/><\/figure>\n\n<\/div>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"problem\">Problem<\/h4>\n\n\n\n<p>The user needs to understand how to change their input in order to achieve a specific system output (see&nbsp;<a href=\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/pattern\/g11-a-local-explanations\/\">G11-A: Local explanations<\/a>\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b).<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"solution\">Solution<\/h4>\n\n\n\n<p>Enable users to simulate and experiment with alternative input values that might change the system\u2019s decision.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"use-when\">Use when<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The user wants decision-making support.<\/li>\n\n\n\n<li>The user wants to see \u201cwhat if\u201d kinds of answers.<\/li>\n\n\n\n<li>The user wants to predict system decisions.<\/li>\n\n\n\n<li>The user wants to understand the system\u2019s logic.<\/li>\n\n\n\n<li>The system has the capability to calculate specific relationships among variables.<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"how\">How<\/h4>\n\n\n\n<p>Provide users the ability to simulate different system decisions by changing:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The initial or default input by increasing or decreasing it.<\/li>\n\n\n\n<li>Influencing conditions to make them better or worse.<\/li>\n<\/ul>\n\n\n\n<p>When enabling users to engage in simulations, support changing the following:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Control \u2013 Enable users to change aspects they can realistically control.<\/li>\n\n\n\n<li>Actions \u2013 Enable users to modify actions rather than failures to act.<\/li>\n\n\n\n<li>Recency \u2013 Enable users to modify the most recent event.<\/li>\n<\/ul>\n\n\n\n<p>It is possible to make this type of explanation actionable by providing the user additional support through recommendations for specific input values that can achieve a fixed desired output.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"user-benefits\">User benefits<\/h4>\n\n\n\n<p>Supports decision making by enabling users to understand the consequences of alternative inputs, states, or conditions.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"common-pitfalls\">Common pitfalls<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The cause and effect relationships in the simulation are not clear to the user.<\/li>\n\n\n\n<li>It is hard for the user to make a decision based on the simulation.<\/li>\n\n\n\n<li>In the case the simulation fails (e.g., the outcome change is unpredictable or inconsistent, or repeated input alterations don\u2019t result in an output change), collaborate with an AI\/ML practitioner to mitigate such failures. For example, establish a mechanism for detecting and mitigating repeated identical failures, and\/or enable the user to provide feedback (see&nbsp;<a href=\"https:\/\/www.microsoft.com\/en-us\/haxtoolkit\/guideline\/encourage-granular-feedback\/\">Guideline 15,&nbsp;<em>Encourage granular feedback<\/em><\/a>).<\/li>\n\n\n\n<li>It is not clear to the user what can be altered.<\/li>\n\n\n\n<li>It is not clear to the user how to alter a specific state.<\/li>\n<\/ul>\n\n\n\n<h4 class=\"wp-block-heading\" id=\"references\">References<\/h4>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Byrne, R. M. (2019, August).&nbsp;<a href=\"https:\/\/www.ijcai.org\/Proceedings\/2019\/876\" target=\"_blank\" rel=\"noreferrer noopener\">Counterfactuals in explainable artificial intelligence (XAI): evidence from human reasoning<\/a>. In&nbsp;<em>Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19<\/em>&nbsp;(pp. 6276-6282).<\/li>\n\n\n\n<li>Ustun, Berk, Alexander Spangher, and Yang Liu. &#8220;<a href=\"https:\/\/ui.adsabs.harvard.edu\/abs\/2018arXiv180906514U\/abstract\" target=\"_blank\" rel=\"noreferrer noopener\">Actionable recourse in linear classification<\/a>.&#8221; Proceedings of the Conference on Fairness, Accountability, and Transparency. 2019.<\/li>\n<\/ul>\n","protected":false},"menu_order":117,"template":"","meta":{"toolkit_pattern_number":"11G","ep_exclude_from_search":false},"application-type":[68,61,57,96,60,99,56,55,69,29,58,30,59],"goal":[114,126,123],"guideline-term":[13],"product-category":[71,70,23,64,62,26,66,28,65,31,32,63],"class_list":["post-709","pattern","type-pattern","status-publish","hentry","application-type-classification","application-type-facial-recognition","application-type-filtering-and-ranking","application-type-gen-ai","application-type-image-recognition","application-type-llm","application-type-natural-language-processing-text","application-type-natural-language-processing-voice","application-type-prediction","application-type-recommendation","application-type-route-planning","application-type-search","application-type-text-generation","goal-appropriate-reliance","goal-reliability","goal-transparency","guideline-term-make-clear-why-the-system-did-what-it-did","product-category-advertising","product-category-chatbot","product-category-e-commerce","product-category-email","product-category-health-and-wellness","product-category-navigation","product-category-media-entertainment","product-category-productivity","product-category-search-engine","product-category-social-networks","product-category-voice-assistants","product-category-writing-and-editing"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Pattern 11G: \u201cWhat if?\u201d explanations - Microsoft HAX Toolkit<\/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:\/\/www.microsoft.com\/en-us\/haxtoolkit\/pattern\/g11-g-what-if-explanations\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Pattern 11G: \u201cWhat if?\u201d explanations - Microsoft HAX Toolkit\" \/>\n<meta property=\"og:description\" content=\"Problem The user needs to understand how to change their input in order to achieve a specific system output (see&nbsp;G11-A: Local explanations\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b\u200b). Solution Enable users to simulate and experiment with alternative input values that might change the system\u2019s decision. 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