{"id":15851,"date":"2023-07-26T00:00:00","date_gmt":"2023-07-25T23:00:00","guid":{"rendered":"https:\/\/members.dataiq.global\/report\/how-well-do-you-need-to-know-your-models\/"},"modified":"2024-05-30T16:23:28","modified_gmt":"2024-05-30T15:23:28","slug":"how-well-do-you-need-to-know-your-models","status":"publish","type":"report","link":"https:\/\/www.dataiq.global\/devstage\/report\/how-well-do-you-need-to-know-your-models\/","title":{"rendered":"How well do you (need to) know your models?"},"content":{"rendered":"<p>DataIQ member Robert Bates, head of decision sciences, Currys, delves into the ways in which ML and AI models are being utilised and what more needs to be done to ensure quality, compliance and efficient use with these new tools and technologies.<\/p>\n<p><em>\u201cI don\u2019t know what concerned me more \u2013 the blind faith in processes without any real understanding of how the business I work in operated, or the matter-of- fact way it was presented.\u201d<\/em> \u2013 Robert Bates<\/p>\n<p>Download this report for the finer details on AI and ML modelling presented by DataIQ member Robert Bates and discover how it can be implemented within your own organisation.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Over the past five years there has been a massive growth within retailers looking to use Machine Learning (ML) and Artificial Intelligence (AI) to improve performance, simplify the customer journey and increase innovation. But should we always trust the algorithms, and are they even required?<\/p>\n","protected":false},"author":3,"featured_media":15852,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_theme","format":"standard","meta":{"_acf_changed":false,"content-type":"","_searchwp_excluded":"","footnotes":""},"categories":[129,133],"tags":[752],"pillar":[],"class_list":["post-15851","report","type-report","status-publish","format-standard","has-post-thumbnail","hentry","category-editorial","category-reports","tag-market-insight"],"acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-21 07:59:31","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/report\/15851","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/report"}],"about":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/types\/report"}],"author":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/comments?post=15851"}],"version-history":[{"count":0,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/report\/15851\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media\/15852"}],"wp:attachment":[{"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/media?parent=15851"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/categories?post=15851"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/tags?post=15851"},{"taxonomy":"pillar","embeddable":true,"href":"https:\/\/www.dataiq.global\/devstage\/wp-json\/wp\/v2\/pillar?post=15851"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}