{"id":4820,"date":"2022-12-07T19:29:23","date_gmt":"2022-12-08T00:29:23","guid":{"rendered":"http:\/\/skimai.com\/?p=4820"},"modified":"2024-04-29T17:27:40","modified_gmt":"2024-04-29T22:27:40","slug":"%e3%83%96%e3%83%ad%e3%82%b0-%e8%aa%ac%e6%98%8e%e5%8f%af%e8%83%bd%e3%81%aaai%e3%81%a8%e3%81%af","status":"publish","type":"post","link":"https:\/\/skimai.com\/ja\/blog-what-is-explainable-ai\/","title":{"rendered":"\u8aac\u660e\u53ef\u80fd\u306aAI\u3068\u306f\u4f55\u304b\uff1f"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_1 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">\u76ee\u6b21<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"\u30c8\u30b0\u30eb\u76ee\u6b21\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">\u30c8\u30b0\u30eb<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" 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: #999;color:#999\" 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><\/span><\/a><\/span><\/div>\n<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:\/\/skimai.com\/ja\/blog-what-is-explainable-ai\/#What_is_Explainable_AI\" >\u8aac\u660e\u53ef\u80fd\u306aAI\u3068\u306f\u4f55\u304b\uff1f<\/a><ul class='ez-toc-list-level-2' ><li class='ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/skimai.com\/ja\/blog-what-is-explainable-ai\/#Use_Cases_of_Explainable_AI\" >\u8aac\u660e\u53ef\u80fd\u306aAI\u306e\u4f7f\u7528\u4f8b<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/skimai.com\/ja\/blog-what-is-explainable-ai\/#Explainable_AI_%E2%80%93_Tools_and_Frameworks\" >\u8aac\u660e\u53ef\u80fd\u306aAI - \u30c4\u30fc\u30eb\u3068\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/skimai.com\/ja\/blog-what-is-explainable-ai\/#Conclusion\" >\u7d50\u8ad6<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h1><span class=\"ez-toc-section\" id=\"What_is_Explainable_AI\"><\/span>\u8aac\u660e\u53ef\u80fd\u306aAI\u3068\u306f\u4f55\u304b\uff1f<span class=\"ez-toc-section-end\"><\/span><\/h1>\n<p>\u4eba\u5de5\u77e5\u80fd\uff08AI\uff09\u3084\u6a5f\u68b0\u5b66\u7fd2\uff08ML\uff09\u306e\u3088\u3046\u306a\u6df1\u5c64\u5b66\u7fd2\u6280\u8853\u304c\u9032\u6b69\u3059\u308b\u306b\u3064\u308c\u3066\u3001\u6211\u3005\u306f\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u30fc\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u304c\u751f\u307f\u51fa\u3059\u30a2\u30a6\u30c8\u30d7\u30c3\u30c8\u3092\u7406\u89e3\u3059\u308b\u3053\u3068\u306b\u6311\u6226\u3057\u3066\u3044\u308b\u3002\u4f8b\u3048\u3070\u3001ML\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306f\u3069\u306e\u3088\u3046\u306b\u3057\u3066\u7279\u5b9a\u306e\u7d50\u679c\u3092\u751f\u307f\u51fa\u3057\u305f\u306e\u304b\uff1f<br \/>\n\u8aac\u660e\u53ef\u80fd\u306aAI\uff08\u307e\u305f\u306fXAI\uff09\u306f\u3001\u4eba\u9593\u306e\u30e6\u30fc\u30b6\u30fc\u304cML\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306b\u3088\u3063\u3066\u751f\u6210\u3055\u308c\u305f\u51fa\u529b\u3092\u7406\u89e3\u3067\u304d\u308b\u3088\u3046\u306b\u3059\u308b\u30d7\u30ed\u30bb\u30b9\u3068\u30c4\u30fc\u30eb\u3092\u30ab\u30d0\u30fc\u3059\u308b\u3002\u7d44\u7e54\u306f\u3001AI\u30e2\u30c7\u30eb\u3092\u672c\u756a\u7a3c\u52d5\u3055\u305b\u308b\u969b\u306b\u3001AI\u30e2\u30c7\u30eb\u306b\u5bfe\u3059\u308b\u4fe1\u983c\u3092\u7bc9\u304b\u306a\u3051\u308c\u3070\u306a\u3089\u306a\u3044\u3002<br \/>\nXAI\u30d7\u30ed\u30bb\u30b9\u5168\u4f53\u306f\u3001\u751f\u6210\u3055\u308c\u305f\u30c7\u30fc\u30bf\u304b\u3089\u76f4\u63a5\u4f5c\u6210\u3055\u308c\u308b\u300c\u30d6\u30e9\u30c3\u30af\u30dc\u30c3\u30af\u30b9\u300d\u30e2\u30c7\u30eb\u3068\u3082\u547c\u3070\u308c\u308b\u3002\u6b21\u306b\u3001\u8aac\u660e\u53ef\u80fd\u306aAI\u306e\u4f7f\u7528\u4f8b\u3092\u898b\u3066\u307f\u3088\u3046\u3002<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Use_Cases_of_Explainable_AI\"><\/span>\u8aac\u660e\u53ef\u80fd\u306aAI\u306e\u4f7f\u7528\u4f8b<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u8aac\u660e\u53ef\u80fd\u306aAI\u306e\u5b9f\u969b\u306e\u4f7f\u7528\u4f8b\u3092\u3044\u304f\u3064\u304b\u7d39\u4ecb\u3057\u3088\u3046\uff1a<\/p>\n<p><strong>\u81ea\u7136\u8a00\u8a9e\u30c6\u30ad\u30b9\u30c8\u306e\u5834\u5408\uff1a<\/strong><br \/>\nXAI for Text\u306f\u3001\u30c6\u30ad\u30b9\u30c8\u95a2\u9023\u30bf\u30b9\u30af\u306e\u305f\u3081\u306e\u30d6\u30e9\u30c3\u30af\u30dc\u30c3\u30af\u30b9\u30e2\u30c7\u30eb\u306e\u958b\u767a\u306b\u7126\u70b9\u3092\u5f53\u3066\u3066\u3044\u308b\u3002\u4f8b\u3048\u3070\u3001\u6cd5\u5f8b\u6587\u66f8\u306e\u8981\u7d04\u306a\u3069\u3067\u3042\u308b\u3002\u3053\u306e\u30e6\u30fc\u30b9\u30b1\u30fc\u30b9\u306b\u304a\u3044\u3066\u3001\u30e6\u30fc\u30b6\u30fc\u306f\u4ee5\u4e0b\u306e\u8003\u5bdf\u306b\u57fa\u3065\u3044\u3066XAI for Text\u3092\u63a2\u7d22\u3057\u3001\u7406\u89e3\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\uff1a<br \/>\n\u30c6\u30ad\u30b9\u30c8\u306b\u7126\u70b9\u3092\u5f53\u3066\u305f\u30bf\u30b9\u30af\u306e\u7a2e\u985e<br \/>\n\u30bf\u30b9\u30af\u306b\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b\u8aac\u660e\u30c6\u30af\u30cb\u30c3\u30af<br \/>\n\u7279\u5b9a\u306eXAI\u6280\u8853\u306e\u30bf\u30fc\u30b2\u30c3\u30c8\u30e6\u30fc\u30b6\u30fc<br \/>\n\u540c\u69d8\u306b\u3001XAI\u30d9\u30fc\u30b9\u306e\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u30e2\u30c7\u30eb\u306f\u3001\u30ec\u30d3\u30e5\u30fc\u3084\u30c8\u30e9\u30f3\u30b9\u30af\u30ea\u30d7\u30c8\u306e\u5f62\u3067\u30c6\u30ad\u30b9\u30c8\u30c7\u30fc\u30bf\u3092\u5206\u985e\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u8aac\u660e\u53ef\u80fd\u306aAI\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\u30c6\u30ad\u30b9\u30c8\u306b\u542b\u307e\u308c\u308b\u7279\u5b9a\u306e\u30ad\u30fc\u30ef\u30fc\u30c9\u3084\u30d5\u30ec\u30fc\u30ba\u306b\u57fa\u3065\u3044\u3066\u3001\u30e2\u30c7\u30eb\u304c\u4e88\u6e2c\u3059\u308b\u7406\u7531\u3092\u5224\u65ad\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<p>\u307e\u305f\u3001XAI for Text\u3092\u4f7f\u7528\u3057\u3066\u30c7\u30a3\u30fc\u30d7\u30e9\u30fc\u30cb\u30f3\u30b0\u30e2\u30c7\u30eb\u3092\u5b66\u7fd2\u3055\u305b\u3001\u30bd\u30fc\u30b9\u30c6\u30ad\u30b9\u30c8\u306b\u57fa\u3065\u3044\u3066\u8a18\u4e8b\u306e\u8981\u7d04\u3092\u751f\u6210\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002\u4f8b\u3048\u3070\u3001\u30bd\u30fc\u30b9\u30c6\u30ad\u30b9\u30c8\u5185\u306e\u9078\u629e\u3057\u305f\u30c8\u30fc\u30af\u30f3\u306b\u5bfe\u3059\u308b\u6ce8\u76ee\u30b9\u30b3\u30a2\u306e\u5206\u5e03\u3092\u5f97\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u6ce8\u76ee\u30b9\u30b3\u30a2\u304c 0 \uff5e 1 \u306e\u5358\u8a9e\uff09\u306f\u3001\u30bd\u30fc\u30b9\u30fb\u30c6\u30ad\u30b9\u30c8\u5185\u3067\u5f37\u8abf\u8868\u793a\u3055\u308c\u3001\u30a8\u30f3\u30c9\u30fb\u30e6\u30fc\u30b6\u30fc\u306b\u8868\u793a\u3055\u308c\u307e\u3059\u3002\u30a2\u30c6\u30f3\u30b7\u30e7\u30f3\u30fb\u30b9\u30b3\u30a2\u304c\u9ad8\u3044\u307b\u3069\u3001\u30c6\u30ad\u30b9\u30c8\u306e\u30cf\u30a4\u30e9\u30a4\u30c8\u306f\u6fc3\u304f\u306a\u308a\u3001\u8a18\u4e8b\u8981\u7d04\u306b\u304a\u3051\u308b\u5358\u8a9e\u306e\u91cd\u8981\u5ea6\u304c\u9ad8\u304f\u306a\u308a\u307e\u3059\u3002<\/p>\n<p><strong>\u8996\u899a\u7684\u306a\u30a4\u30e1\u30fc\u30b8\u306e\u305f\u3081\u306b\uff1a<\/strong><br \/>\n\u8aac\u660e\u53ef\u80fd\u306aAI\u306f\u3001\u9ad8\u89e3\u50cf\u5ea6\u306e\u8996\u899a\u753b\u50cf\u306b\u57fa\u3065\u304f\u610f\u601d\u6c7a\u5b9a\u306e\u81ea\u52d5\u5316\u306b\u3082\u4f7f\u308f\u308c\u3066\u3044\u308b\u3002\u9ad8\u89e3\u50cf\u5ea6\u753b\u50cf\u306e\u4f8b\u3068\u3057\u3066\u306f\u3001\u885b\u661f\u753b\u50cf\u3084\u533b\u7642\u30c7\u30fc\u30bf\u306a\u3069\u304c\u3042\u308b\u3002\u885b\u661f\u30c7\u30fc\u30bf\u306f\u5927\u5bb9\u91cf\u3067\u3042\u308b\u3053\u3068\u306b\u52a0\u3048\u3001\u64ae\u5f71\u3055\u308c\u305f\u30c7\u30fc\u30bf\u306f\u9ad8\u89e3\u50cf\u5ea6\u3067\u3042\u308a\u3001\u8907\u6570\u306e\u30b9\u30da\u30af\u30c8\u30eb\u30d0\u30f3\u30c9\u3092\u542b\u3093\u3067\u3044\u308b\u3002\u4f8b\u3048\u3070\u3001\u53ef\u8996\u5149\u3084\u8d64\u5916\u7dda\u306a\u3069\u3067\u3059\u3002XAI\u3067\u5b66\u7fd2\u3057\u305f\u30e2\u30c7\u30eb\u3092\u5c0e\u5165\u3059\u308b\u3053\u3068\u3067\u3001\u9ad8\u89e3\u50cf\u5ea6\u753b\u50cf\u3092\u3088\u308a\u5c0f\u3055\u306a\u30d1\u30c3\u30c1\u306b\u300c\u5206\u5272\u300d\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<p>\u533b\u7642\u753b\u50cf\u306e\u9818\u57df\u3067\u306f\u3001XAI\u30e2\u30c7\u30eb\u304cX\u7dda\u5199\u771f\u304b\u3089\u80f8\u90e8\u80ba\u708e\u3092\u691c\u51fa\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b\u3002\u540c\u69d8\u306b\u3001\u753b\u50cf\u8a8d\u8b58\u3082\u8996\u899a\u753b\u50cf\u306e\u9818\u57df\u306b\u304a\u3051\u308b\u8aac\u660e\u53ef\u80fd\u306aAI\u306e\u4f7f\u7528\u4f8b\u3067\u3042\u308b\u3002\u8996\u899aAI\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\uff08\u30ad\u30e3\u30d7\u30c1\u30e3\u3057\u305f\u753b\u50cf\u306b\u542b\u307e\u308c\u308b\uff09\u753b\u50cf\u3084\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u8a8d\u8b58\u3059\u308b\u305f\u3081\u306e\u30ab\u30b9\u30bf\u30e0AI\u30e2\u30c7\u30eb\u3092\u8a13\u7df4\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n<p><strong>\u7d71\u8a08\u306e\u305f\u3081\uff1a<\/strong><br \/>\nXAI\u306e\u30e2\u30c7\u30eb\u3084\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u306f\u3001\u305d\u306e\u7cbe\u5ea6\u3084\u89e3\u91c8\u306e\u5ea6\u5408\u3044\u306b\u57fa\u3065\u3044\u3066\u52b9\u679c\u7684\u3067\u3042\u308b\u3002\u7dda\u5f62\u56de\u5e30\u3001\u6c7a\u5b9a\u6728\u3001K-nearest neighborhoods\u306e\u3088\u3046\u306a\u7d71\u8a08\u7684\u95a2\u4fc2\u30e2\u30c7\u30eb\u306f\u89e3\u91c8\u3057\u3084\u3059\u3044\u304c\u3001\u7cbe\u5ea6\u306f\u4f4e\u3044\u3002\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u30e2\u30c7\u30eb\u304c\u89e3\u91c8\u53ef\u80fd\u3067\u6b63\u78ba\u3067\u3042\u308b\u305f\u3081\u306b\u306f\u3001\u9ad8\u54c1\u8cea\u306e\u30c7\u30fc\u30bf\u304cAI\u30e2\u30c7\u30eb\u306b\u4f9b\u7d66\u3055\u308c\u306a\u3051\u308c\u3070\u306a\u3089\u306a\u3044\u3002<\/p>\n<p>XAI\u306f\u30c7\u30fc\u30bf\u30b5\u30a4\u30a8\u30f3\u30b9\u306e\u9818\u57df\u3067\u5927\u304d\u306a\u53ef\u80fd\u6027\u3092\u79d8\u3081\u3066\u3044\u308b\u3002\u4f8b\u3048\u3070\u3001Explainable AI\u306f\u3001\u7d71\u8a08\u751f\u7523\u30b7\u30b9\u30c6\u30e0\u3067\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b\u3002 <a href=\"https:\/\/arxiv.org\/abs\/2107.08045\">\u6b27\u5dde\u4e2d\u592e\u9280\u884c<\/a> (ECB\uff09\u3002\u30e6\u30fc\u30b6\u30fc\u4e2d\u5fc3\u306e\u8981\u671b\u3092 \"\u5178\u578b\u7684\u306a \"\u30e6\u30fc\u30b6\u30fc\u306e\u5f79\u5272\u306b\u30ea\u30f3\u30af\u3055\u305b\u308b\u3053\u3068\u3067\u3001XAI\u306f\u5404\u30e6\u30fc\u30b6\u30fc\u306e\u30cb\u30fc\u30ba\u306b\u5bfe\u5fdc\u3059\u308b\u305f\u3081\u306e\u624b\u6cd5\u3084\u30c6\u30af\u30cb\u30c3\u30af\u3092\u6982\u8aac\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002<\/p>\n<p>\u6b21\u306b\u3001\u8aac\u660e\u53ef\u80fd\u306aAI\u3067\u4f7f\u308f\u308c\u308b\u4e00\u822c\u7684\u306a\u30c4\u30fc\u30eb\u3084\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u3088\u3046\u3002<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Explainable_AI_%E2%80%93_Tools_and_Frameworks\"><\/span>\u8aac\u660e\u53ef\u80fd\u306aAI - \u30c4\u30fc\u30eb\u3068\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u8fd1\u5e74\u3001AI\u7814\u7a76\u8005\u305f\u3061\u306f\u3001\u8aac\u660e\u53ef\u80fd\u306aAI\u3092\u63a8\u9032\u3059\u308b\u305f\u3081\u306e\u8907\u6570\u306e\u30c4\u30fc\u30eb\u3084\u30d5\u30ec\u30fc\u30e0\u30ef\u30fc\u30af\u306b\u53d6\u308a\u7d44\u3093\u3067\u304d\u305f\u3002\u3053\u3053\u3067\u306f\u3001\u4eba\u6c17\u306e\u3042\u308b\u3082\u306e\u3092\u3044\u304f\u3064\u304b\u7d39\u4ecb\u3057\u3088\u3046\uff1a<\/p>\n<p><strong>\u3082\u3057\u305d\u3046\u306a\u3089<\/strong> TensorFlow\u30c1\u30fc\u30e0\u306b\u3088\u3063\u3066\u958b\u767a\u3055\u308c\u305fWhat-If\u306f\u3001TensorFlow AI\u30e2\u30c7\u30eb\u306e\u51fa\u529b\u3092\u7406\u89e3\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u308b\u8996\u899a\u7684\u306b\u30a4\u30f3\u30bf\u30e9\u30af\u30c6\u30a3\u30d6\u306a\u30c4\u30fc\u30eb\u3067\u3059\u3002\u3053\u306e\u30c4\u30fc\u30eb\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001\u30c7\u30d7\u30ed\u30a4\u3055\u308c\u305fAI\u30e2\u30c7\u30eb\u306e\u30d1\u30d5\u30a9\u30fc\u30de\u30f3\u30b9\u3068\u3068\u3082\u306b\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u7c21\u5358\u306b\u8996\u899a\u5316\u3067\u304d\u307e\u3059\u3002<\/p>\n<p><strong>\u30e9\u30a4\u30e0<\/strong> Local Interpretable Model-agnostic Explanation\u306e\u7565\u3067\u3001LIME\u30c4\u30fc\u30eb\u306f\u30ef\u30b7\u30f3\u30c8\u30f3\u5927\u5b66\u306e\u7814\u7a76\u30c1\u30fc\u30e0\u306b\u3088\u3063\u3066\u958b\u767a\u3055\u308c\u305f\u3002LIME\u306f\u3001\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u5185\u3067 \"\u4f55\u304c\u8d77\u304d\u3066\u3044\u308b\u306e\u304b \"\u3092\u3088\u308a\u826f\u304f\u53ef\u8996\u5316\u3059\u308b\u3002\u3055\u3089\u306bLIME\u306f\u3001\u3042\u3089\u3086\u308b\u30e2\u30c7\u30eb\u306e\u4e88\u6e2c\u3092\u8aac\u660e\u3059\u308b\u305f\u3081\u306e\u30e2\u30b8\u30e5\u30e9\u30fc\u3067\u62e1\u5f35\u53ef\u80fd\u306a\u65b9\u6cd5\u3092\u63d0\u4f9b\u3059\u308b\u3002<\/p>\n<p><strong>AIX360\uff1a<\/strong> IBM\u306b\u3088\u3063\u3066\u958b\u767a\u3055\u308c\u305fAI Explainability 360\uff08AIX 360\uff09\u306f\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3084\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u8aac\u660e\u3068\u89e3\u91c8\u306b\u4f7f\u7528\u3055\u308c\u308b\u30aa\u30fc\u30d7\u30f3\u30bd\u30fc\u30b9\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u3067\u3042\u308b\u3002Python\u30d1\u30c3\u30b1\u30fc\u30b8\u3068\u3057\u3066\u30ea\u30ea\u30fc\u30b9\u3055\u308c\u305fAIX360\u306b\u306f\u3001\u30e1\u30c8\u30ea\u30af\u30b9\u3068\u3068\u3082\u306b\u69d8\u3005\u306a\u8aac\u660e\u3092\u30ab\u30d0\u30fc\u3059\u308b\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u4e00\u5f0f\u304c\u542b\u307e\u308c\u3066\u3044\u308b\u3002<\/p>\n<p><strong>SHAP\uff1a<\/strong> Shapley Additive Explanations\u306e\u7565\u3067\u3001SHAP\u306f\u3042\u3089\u3086\u308b\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb\u306e\u51fa\u529b\u3092\u8aac\u660e\u3059\u308b\u305f\u3081\u306e\u30b2\u30fc\u30e0\u30d9\u30fc\u30b9\u306e\u7406\u8ad6\u7684\u30a2\u30d7\u30ed\u30fc\u30c1\u3067\u3042\u308b\u3002\u30b2\u30fc\u30e0\u7406\u8ad6\u306e\u30b7\u30e3\u30d7\u30ec\u30fc\u5024\u3092\u4f7f\u3046\u3053\u3068\u3067\u3001SHAP\u306f\u6700\u9069\u306a\u30af\u30ec\u30b8\u30c3\u30c8\u5272\u308a\u5f53\u3066\u3068\u5c40\u6240\u7684\u306a\u8aac\u660e\u3092\u7d50\u3073\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u3002SHAP\u306fPyPI\u3084Conda Forge\u3092\u4f7f\u3063\u3066\u7c21\u5358\u306b\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3067\u304d\u308b\u3002<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span>\u7d50\u8ad6<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u7d44\u7e54\u306fAI\u30e2\u30cb\u30bf\u30ea\u30f3\u30b0\u3092\u901a\u3058\u3066\u3001AI\u3092\u6d3b\u7528\u3057\u305f\u610f\u601d\u6c7a\u5b9a\u30d7\u30ed\u30bb\u30b9\u3092\u5b8c\u5168\u306b\u7406\u89e3\u3059\u308b\u5fc5\u8981\u304c\u3042\u308b\u3002\u8aac\u660e\u53ef\u80fd\u306aAI\u306f\u3001\u4f01\u696d\u304c\u5c0e\u5165\u3057\u305fML\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3084\u30c7\u30a3\u30fc\u30d7\u30fb\u30cb\u30e5\u30fc\u30e9\u30eb\u30fb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u7c21\u5358\u306b\u8aac\u660e\u3059\u308b\u3053\u3068\u3092\u53ef\u80fd\u306b\u3059\u308b\u3002\u52b9\u679c\u7684\u306b\u3001AI\u3068ML\u6280\u8853\u306e\u751f\u7523\u7684\u306a\u5229\u7528\u3068\u3068\u3082\u306b\u3001\u30d3\u30b8\u30cd\u30b9\u4e0a\u306e\u4fe1\u983c\u3092\u69cb\u7bc9\u3059\u308b\u306e\u306b\u5f79\u7acb\u3064\u3002<\/p>","protected":false},"excerpt":{"rendered":"<p>What is Explainable AI? As deep learning technologies like Artificial Intelligence (AI) and Machine learning (ML) advance, we are being challenged to understand the outputs produced by computer algorithms. For example, how did ML algorithms produce a particular result? Explainable AI (or XAI) covers the processes and tools that enable human users to comprehend the outputs generated by ML algorithms. Organizations must build their trust in AI models when putting them into production. The entire XAI process is also referred to as a \u201cblack box\u201d model that is created directly from the generated data. Next, let\u2019s look at some of the use cases of Explainable AI. Use Cases of Explainable [&hellip;]<\/p>\n","protected":false},"author":1003,"featured_media":4821,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"single-custom-post-template.php","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","footnotes":""},"categories":[125],"tags":[],"class_list":["post-4820","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-enterprise-ai-blog"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>What is Explainable AI? - Skim AI<\/title>\n<meta name=\"description\" content=\"Explainable AI (or XAI) covers the processes and tools that enable human users to comprehend the outputs generated by ML algorithms.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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