{"id":813,"date":"2025-12-23T10:34:31","date_gmt":"2025-12-23T10:34:31","guid":{"rendered":"https:\/\/alandix.com\/statistics\/?page_id=813"},"modified":"2025-12-23T10:42:23","modified_gmt":"2025-12-23T10:42:23","slug":"chapter-12","status":"publish","type":"page","link":"https:\/\/alandix.com\/statistics\/second-edition\/toc\/chapter-12\/","title":{"rendered":"Chapter 12: AI &#8212; intelligence but not as we know it"},"content":{"rendered":"<div class=\"embedurl\" data-url=\"https:\/\/alandix.com\/books\/hcistats\/content2e\/chaps\/chap-12.html\" ><!--  Chapter 12 AI \u2013 intelligence but not as we knowit  -->\n\n<script>\nvar chapnos = 12;\nvar json_url = \"https:\\\/\\\/alandix.com\\\/books\\\/hcistats\\\/content2e\\\/chaps\\\/chap-12.json\";\n<\/script>\n\n\n\n\n\n\n<h3> Contents <\/h3>\n<div class=\"toc\">\n<dl>\n<dt>12.1&nbsp;&nbsp;AI and statistics working together<\/dt><dd><dl>\n<dt>12.1.1&nbsp;&nbsp;AI as an alternative to statistics<\/dt>\n<dt>12.1.2&nbsp;&nbsp;Statistics under the bonnet of AI<\/dt>\n<\/dl><\/dd>\n<dt>12.2&nbsp;&nbsp;Explainable AI<\/dt><dd><dl>\n<dt>12.2.1&nbsp;&nbsp;Why we need explainability<\/dt>\n<dt>12.2.2&nbsp;&nbsp;Explainable statistics<\/dt>\n<dt>12.2.3&nbsp;&nbsp;Explainability in AI<\/dt>\n<\/dl><\/dd>\n<dt>12.3&nbsp;&nbsp;Evaluating AI<\/dt><dd><dl>\n<dt>12.3.1&nbsp;&nbsp;Holdout<\/dt>\n<dt>12.3.2&nbsp;&nbsp;Limits to validity<\/dt>\n<dt>12.3.3&nbsp;&nbsp;Comparing AI algorithms<\/dt>\n<\/dl><\/dd>\n<dt>12.4&nbsp;&nbsp;Case study: regret<\/dt>\n<dt>12.5&nbsp;&nbsp;User testing of AI systems<\/dt>\n<dt>12.6&nbsp;&nbsp;AI as statistics guru<\/dt>\n<\/dl><\/div>\n\n\n<h3> Glossary items referenced in this chapter <\/h3>\n<div class=\"toc\">\n<a href=\"https:\/\/alandix.com\/glossary\/hcistats\/accuracy%20measure\">accuracy measure<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/anova\">ANOVA (Analysis of Variance)<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/average\">average<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/bayes%20rule\">Bayes rule<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/bayesian%20network\">bayesian network<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/bias\">bias<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/big%20data\">big data<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/binomial%20distribution\">Binomial distribution<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/black%20box%20models\">black box models<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/chatgpt\">chatgpt<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/cloud%20infrastructure\">cloud infrastructure<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/cognitive%20model\">cognitive model<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/confidence%20in%20estimates\">confidence in estimates<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/confidence%20measure\">confidence measure<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/decision%20tree\">decision tree<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/deep%20neural%20network\">deep neural network<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/discrete%20classification\">discrete classification<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/diversity\">diversity<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/empirical%20testing\">empirical testing<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/estimation\">estimation<\/a>, <strong><a href=\"https:\/\/alandix.com\/glossary\/hcistats\/explainable%20ai\">explainable ai<\/a><\/strong>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/explainable%20statistics\">explainable statistics<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/factor%20analysis\">factor analysis<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/generalisation\">generalisation<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/global%20explanation\">global explanation<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/gpu\">gpu<\/a>, <strong><a href=\"https:\/\/alandix.com\/glossary\/hcistats\/hold%20out\">hold out<\/a><\/strong>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/hyperparameters\">hyperparameters<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/hyperplane\">hyperplane<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/interaction%20effect\">interaction effect<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/jackknifing\">jackknifing<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/knowledge%20base\">knowledge base<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/large%20language%20model\">large language model<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/legally%20compliant\">legally compliant<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/likert%20scale\">Likert scale<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/linear%20discriminant\">linear discriminant<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/linear%20regression\">linear regression<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/local%20explanation\">local explanation<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/machine%20learning\">machine learning<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/main%20effect\">main effect<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/neural%20network\">neural network<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/neural%20network%20weights\">neural network weights<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/overfitting\">overfitting<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/personal%20data%20sovereignty\">personal data sovereignty<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/perturbations\">perturbations<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/probability%20distribution\">probability distribution<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/recommender%20systems\">recommender systems<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/regret\">regret<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/reinforcement%20learning\">reinforcement learning<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/replications\">replications<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/reproducibility\">reproducibility<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/residual%20sum%20of%20squares\">residual sum of squares<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/safety\">safety<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/selection%20bias\">selection bias<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/sensitivity%20analysis\">sensitivity analysis<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/shap\">SHAP<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/standard%20deviation\">standard deviation (s.d., &amp;sigma;)<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/stochastic\">stochastic<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/summative%20evaluation\">summative evaluation<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/symbolic%20ai\">symbolic ai<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/test%20data\">test data<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/three%20cs\">three cs<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/training%20data\">training data<\/a>, <strong><a href=\"https:\/\/alandix.com\/glossary\/hcistats\/transparency\">transparency<\/a><\/strong>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/user%20experience%20design\">user experience design<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/user%20studies\">user studies<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/wizard%20of%20oz%20prototyping\">Wizard of Oz prototyping<\/a>, <a href=\"https:\/\/alandix.com\/glossary\/hcistats\/xai\">xai<\/a><\/div>\n\n\n<!-- ?php\n\tif ( @$page['prolog_examples'] ):\n?>\n<h3> Prolog examples (from 1st ed.) <\/h3>\n<!-- ?php\n\techo $page['prolog_examples'];\n?>\n<!-- ?php\n\tendif; \/\/ @$page['prolog_examples']\n? -->\n\n<\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":2,"featured_media":0,"parent":801,"menu_order":12,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_themeisle_gutenberg_block_has_review":false,"footnotes":""},"class_list":["post-813","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/alandix.com\/statistics\/wp-json\/wp\/v2\/pages\/813","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/alandix.com\/statistics\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/alandix.com\/statistics\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/alandix.com\/statistics\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/alandix.com\/statistics\/wp-json\/wp\/v2\/comments?post=813"}],"version-history":[{"count":2,"href":"https:\/\/alandix.com\/statistics\/wp-json\/wp\/v2\/pages\/813\/revisions"}],"predecessor-version":[{"id":845,"href":"https:\/\/alandix.com\/statistics\/wp-json\/wp\/v2\/pages\/813\/revisions\/845"}],"up":[{"embeddable":true,"href":"https:\/\/alandix.com\/statistics\/wp-json\/wp\/v2\/pages\/801"}],"wp:attachment":[{"href":"https:\/\/alandix.com\/statistics\/wp-json\/wp\/v2\/media?parent=813"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}