{"id":5495,"date":"2024-02-26T20:18:22","date_gmt":"2024-02-26T20:18:22","guid":{"rendered":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/speakers\/gary-godding-copy\/"},"modified":"2024-03-12T12:24:52","modified_gmt":"2024-03-12T12:24:52","slug":"matt-bezdek","status":"publish","type":"page","link":"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/speakers\/matt-bezdek\/","title":{"rendered":"Matt Bezdek"},"content":{"rendered":"<!--themify_builder_content-->\n<div id=\"themify_builder_content-5495\" data-postid=\"5495\" class=\"themify_builder_content themify_builder_content-5495 themify_builder tf_clear\">\n                    <div  data-lazy=\"1\" class=\"module_row themify_builder_row dropPadding-bottom tb_6dug310 tb_first tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_2 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col4-1 tb_qv1i048 first\">\n                    <!-- module image -->\n<div  class=\"module module-image tb_3zrh000 image-top   tf_mw\" data-lazy=\"1\">\n        <div class=\"image-wrap tf_rel tf_mw\">\n            <img loading=\"lazy\" decoding=\"async\" width=\"300\" height=\"300\" src=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Matt_Bezdek.jpg\" class=\"wp-post-image wp-image-5452\" title=\"Matt Bezdek\" alt=\"Matt Bezdek headshot\" srcset=\"https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Matt_Bezdek.jpg 300w, https:\/\/meetings.informs.org\/wordpress\/analytics2024\/files\/2024\/02\/Matt_Bezdek-150x150.jpg 150w\" sizes=\"auto, (max-width: 300px) 100vw, 300px\" \/>    \n        <\/div>\n    <!-- \/image-wrap -->\n    \n        <div class=\"image-content\">\n                    <h3 class=\"image-title\">\n                                    Matt Bezdek                            <\/h3>\n                    <\/div>\n    <!-- \/image-content -->\n        <\/div>\n<!-- \/module image -->        <\/div>\n                    <div  data-lazy=\"1\" class=\"module_column tb-column col4-3 tb_1pw8999 last\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_g5z6009   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h1>Matt Bezdek<\/h1>\n<h5>Senior Data Scientist at Elder Research<\/h5>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module accordion -->\n<div  class=\"module module-accordion tb_ejav992 \" data-behavior=\"toggle\" data-lazy=\"1\">\n    \n    <ul class=\"ui module-accordion  glossy tb_default_color\">\n            <li>\n            <div class=\"accordion-title tf_rel\">\n                <a href=\"#acc-ejav992-0\" class=\"tb_title_accordion\" aria-controls=\"acc-ejav992-0-content\" aria-expanded=\"false\">\n                    <i class=\"accordion-icon\"><svg  class=\"tf_fa tf-ti-plus\" aria-hidden=\"true\"><use href=\"#tf-ti-plus\"><\/use><\/svg><\/i>                    <i class=\"accordion-active-icon tf_hide\"><svg  class=\"tf_fa tf-ti-minus\" aria-hidden=\"true\"><use href=\"#tf-ti-minus\"><\/use><\/svg><\/i>                    <span class=\"accordion-title-wrap\">Bio<\/span>                <\/a>\n            <\/div><!-- .accordion-title -->\n            <div id=\"acc-ejav992-0-content\" data-id=\"acc-ejav992-0\" aria-hidden=\"true\" class=\"accordion-content tf_hide tf_clearfix\">\n                                    <div class=\"tb_text_wrap\">\n                        <p>Matt Bezdek is a Senior Data Scientist at Elder Research. He has over 10 years of experience in performing advanced statistical analyses and leading research teams. At Elder Research he helps commercial and nonprofit clients with model validation, software development, interactive data visualization, data literacy education, and building data analytic strategies. He holds a PhD in Cognitive Psychology from Stony Brook University and has conducted research at the Georgia Institute of Technology and Washington University in St. Louis on how brains attend to engaging narratives, learn from educational messages, and process everyday life events. <\/p>                    <\/div>\n                            <\/div><!-- .accordion-content -->\n        <\/li>\n        <\/ul>\n\n<\/div><!-- \/module accordion -->        <\/div>\n                        <\/div>\n        <\/div>\n                        <div  data-css_id=\"i7eg519\" data-lazy=\"1\" class=\"module_row themify_builder_row fullwidth_row_container tb_i7eg519 tf_w\">\n                        <div class=\"row_inner col_align_top tb_col_count_1 tf_box tf_rel\">\n                        <div  data-lazy=\"1\" class=\"module_column tb-column col-full tb_gnbi310 first\">\n                    <!-- module text -->\n<div  class=\"module module-text tb_1zrc222 track  \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h6>Track: Decision Analytics<\/h6>    <\/div>\n<\/div>\n<!-- \/module text --><!-- module text -->\n<div  class=\"module module-text tb_o1ie993   \" data-lazy=\"1\">\n        <div  class=\"tb_text_wrap\">\n        <h2>Better Decision-Making with Explainable AI Models<\/h2>\n<p>So-called \u2018black box\u2019 models are popular, as in some cases they can provide boosts to accuracy over simpler and more transparent models. However, there is a cost to using a model that doesn\u2019t reveal the relationship between its predictions and its input features. Luckily, even when using a black box model, there are techniques that can generate useful explanations of model predictions. Better yet, these techniques are available in free Python packages and work on a wide variety of model types. I will discuss applications of how to use explanation techniques to understand the predictions of otherwise opaque predictive models. I will show how meaningful explanations build trust in model predictions and improve the decision-making process through the integration of stakeholders\u2019 subject matter expertise with the specific predictions of the model.<\/p>    <\/div>\n<\/div>\n<!-- \/module text -->        <\/div>\n                        <\/div>\n        <\/div>\n        <\/div>\n<!--\/themify_builder_content-->","protected":false},"excerpt":{"rendered":"<p>Matt Bezdek Senior Data Scientist at Elder Research<\/p>\n","protected":false},"author":1001094,"featured_media":0,"parent":712,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"class_list":["post-5495","page","type-page","status-publish","hentry","has-post-title","has-post-date","has-post-category","has-post-tag","has-post-comment","has-post-author",""],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v26.0 (Yoast SEO v26.0) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Matt Bezdek - 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He has over 10 years of experience in performing advanced statistical analyses and leading research teams. At Elder Research he helps commercial and nonprofit clients with model validation, software development, interactive data visualization, data literacy education, and building data analytic strategies. He holds a PhD in Cognitive Psychology from Stony Brook University and has conducted research at the Georgia Institute of Technology and Washington University in St. Louis on how brains attend to engaging narratives, learn from educational messages, and process everyday life events. <\/p><\/li><\/ul>\n<h6>Track: Decision Analytics<\/h6>\n<h2>Better Decision-Making with Explainable AI Models<\/h2> <p>So-called \u2018black box\u2019 models are popular, as in some cases they can provide boosts to accuracy over simpler and more transparent models. However, there is a cost to using a model that doesn\u2019t reveal the relationship between its predictions and its input features. 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