{"id":248160,"date":"2024-05-24T11:15:39","date_gmt":"2024-05-24T11:15:39","guid":{"rendered":"https:\/\/www.techopedia.com\/?p=248160"},"modified":"2024-05-24T11:15:39","modified_gmt":"2024-05-24T11:15:39","slug":"your-ceo-may-be-ready-for-ai-but-your-data-isnt","status":"publish","type":"post","link":"https:\/\/www.techopedia.com\/poor-data-quality-is-killing-your-ai-project","title":{"rendered":"Your CEO May Be Ready for AI, but Your Data Isn\u2019t"},"content":{"rendered":"<p>Worries about dodgy <a href=\"https:\/\/www.techopedia.com\/definition\/807\/data\">data<\/a> have been with us since <a href=\"https:\/\/www.researchgate.net\/publication\/1775771_Information_and_Data_Quality_in_Spreadsheets\" target=\"_blank\">the dawn of spreadsheets<\/a>. Now that <a href=\"https:\/\/www.techopedia.com\/definition\/34633\/generative-ai\">GenAI<\/a> has exploded onto the scene, questionable inputs are being blamed for the <a href=\"https:\/\/www.techopedia.com\/definition\/ai-hallucination\">hallucinations<\/a> and other odd behaviors that routinely plague <a href=\"https:\/\/www.techopedia.com\/definition\/34948\/large-language-model-llm\">LLMs<\/a>.<\/p>\n<p><a href=\"https:\/\/www.techopedia.com\/definition\/14653\/data-quality\">Data quality<\/a> determines the reliability of AI outputs. If you don\u2019t have full confidence in the strings, floats, bools, chars, enums, and arrays you\u2019re feeding into a <a href=\"https:\/\/www.techopedia.com\/best-machine-learning-algorithms\">machine learning model<\/a>, you can\u2019t be 100% sure of the answers it spits out or the inferences it makes.<\/p>\n<p>To trust <a href=\"https:\/\/www.techopedia.com\/definition\/190\/artificial-intelligence-ai\">AI<\/a>, you need trusted data. How can <a href=\"https:\/\/www.techopedia.com\/definition\/34461\/machine-learning-operations-mlops\">MLOps<\/a> teams ensure their training sets are always fit for purpose?<\/p>\n<div class=\"su-note\"  style=\"border-color:#e5e54c;border-radius:\u201c3\u201dpx;-moz-border-radius:\u201c3\u201dpx;-webkit-border-radius:\u201c3\u201dpx;\"><div class=\"su-note-inner su-u-clearfix su-u-trim\" style=\"background-color:#FFFF66;border-color:#ffffff;color:#333333;border-radius:\u201c3\u201dpx;-moz-border-radius:\u201c3\u201dpx;-webkit-border-radius:\u201c3\u201dpx;\">\n<h2><span id=\"key_takeaways\">Key Takeaways<\/span><\/h2>\n<ul>\n<li>Data sets with incomplete, out-of-date, or unreadable information are being blamed for high-profile AI malfunctions: hallucinations, made-up facts, or doubling down when falsehoods are challenged.<\/li>\n<li>With the arrival of Big Data analytics, you might think we\u2019d have solved the data quality issue by now. But problems persist.<\/li>\n<li>Just this week, the teenage founder of Scale AI closed an Nvidia-backed $1 billion funding round for his data-cleansing startup.<\/li>\n<li>Better technology to manage data might help, but tools can only do so much. Chief Data Officers and Data Science teams need to work together and create a company-wide culture of data quality assurance.<\/li>\n<\/ul>\n<\/div><\/div>\n<div>\n    <section class=\"toc-sticky w-100 bg-white \">\n        <div class=\"toc-sticky__container container\">\n            <div class=\"toc-sticky__open d-flex align-items-end\" data-bs-toggle=\"collapse\"\n                 aria-controls=\"multiCollapse1\"\n                 data-bs-target=\"#multiCollapse1\">\n                <button\n                        class=\"btn btn-primary collapse-action-btn p-1 rounded-circle\"\n                        type=\"button\"\n                >\n                    <i class=\"icon-chevron-up\"><\/i>\n                <\/button>\n                <span id=\"toc-current-title\" class=\"d-flex align-items-center\">\n                    Table of Contents\n                <\/span>\n                <span class=\"toc-main-title-permanent\">Table of Contents<\/span>\n            <\/div>\n            <div\n                    class=\"collapse my-3\"\n                    id=\"multiCollapse1\"\n            >\n                <ol class=\"StepProgress\">\n                                                                        <li class=\"StepProgress-item current\">\n                                                <div class=\"StepProgress-item__group\">\n                            <a data-id=\"key_takeaways\"\n                               onclick=handleScrollToTitle(\"key_takeaways\")\n                               class=\"StepProgress-item__link\" data-level=\"2\">Key Takeaways<\/a>\n                                                    <\/div>\n                                                <\/li>\n                                                                        <li class=\"StepProgress-item\">\n                                                <div class=\"StepProgress-item__group\">\n                            <a data-id=\"garbage_in_garbage_out\"\n                               onclick=handleScrollToTitle(\"garbage_in_garbage_out\")\n                               class=\"StepProgress-item__link\" data-level=\"2\">Garbage In. Garbage Out.<\/a>\n                                                    <\/div>\n                                                <\/li>\n                                                                        <li class=\"StepProgress-item\">\n                                                <div class=\"StepProgress-item__group\">\n                            <a data-id=\"why_dodgy_data_is_behind_those_ai_hallucinations\"\n                               onclick=handleScrollToTitle(\"why_dodgy_data_is_behind_those_ai_hallucinations\")\n                               class=\"StepProgress-item__link\" data-level=\"2\">Why Dodgy Data Is Behind Those AI Hallucinations<\/a>\n                                                    <\/div>\n                                                <\/li>\n                                                                        <li class=\"StepProgress-item\">\n                                                <div class=\"StepProgress-item__group\">\n                            <a data-id=\"an_innovation_killer\"\n                               onclick=handleScrollToTitle(\"an_innovation_killer\")\n                               class=\"StepProgress-item__link\" data-level=\"2\">An Innovation Killer<\/a>\n                                                    <\/div>\n                                                <\/li>\n                                                                        <li class=\"StepProgress-item\">\n                                                <div class=\"StepProgress-item__group\">\n                            <a data-id=\"maintaining_data_quality_is_hard\"\n                               onclick=handleScrollToTitle(\"maintaining_data_quality_is_hard\")\n                               class=\"StepProgress-item__link\" data-level=\"2\">Maintaining Data Quality Is Hard<\/a>\n                                                    <\/div>\n                                                <\/li>\n                                                                        <li class=\"StepProgress-item\">\n                                                <div class=\"StepProgress-item__group\">\n                            <a data-id=\"ai_needs_data_does_data_need_ai\"\n                               onclick=handleScrollToTitle(\"ai_needs_data_does_data_need_ai\")\n                               class=\"StepProgress-item__link\" data-level=\"2\">AI Needs Data. Does Data Need AI?<\/a>\n                                                    <\/div>\n                                                <\/li>\n                                                                        <li class=\"StepProgress-item\">\n                                                <div class=\"StepProgress-item__group\">\n                            <a data-id=\"the_bottom_line\"\n                               onclick=handleScrollToTitle(\"the_bottom_line\")\n                               class=\"StepProgress-item__link\" data-level=\"2\">The Bottom Line<\/a>\n                                                    <\/div>\n                                                <\/li>\n                                                                        <li class=\"StepProgress-item\">\n                                                <div class=\"StepProgress-item__group\">\n                            <a data-id=\"faqs\"\n                               onclick=handleScrollToTitle(\"faqs\")\n                               class=\"StepProgress-item__link\" data-level=\"2\">FAQs<\/a>\n                                                    <\/div>\n                                                <\/li>\n                                                                        <li class=\"StepProgress-item\">\n                                                <div class=\"StepProgress-item__group\">\n                            <a data-id=\"references\"\n                               onclick=handleScrollToTitle(\"references\")\n                               class=\"StepProgress-item__link\" data-level=\"2\">References<\/a>\n                                                    <\/div>\n                                                <\/li>\n                                    <\/ol>\n                <div class=\"toc-sticky__container__disperse\"><\/div>\n                <div class=\"toc-sticky__btn-top justify-content-center\">\n                    <button class=\"btn btn-link d-flex align-items-center\" onclick={btnTop()}><p>Show Full Guide<\/p><img decoding=\"async\"\n                                src=\"\/wp-content\/plugins\/table-of-contents\/assets\/images\/arrow-up-circle.svg\"\n                                alt=\"arrow-up-circle\">\n                    <\/button>\n                <\/div>\n            <\/div>\n        <\/div>\n    <\/section>\n    <div class=\"toc-sticky-list\">\n        <div class=\"toc-sticky__container container\">\n            <div class=\"toc-sticky__open d-flex align-items-end\" data-bs-toggle=\"collapse\" aria-controls=\"multiCollapse2\" data-bs-target=\"#multiCollapse2\">\n                <button class=\"btn btn-primary collapse-action-btn p-1 rounded-circle\"\n                        type=\"button\">\n                    <i class=\"icon-chevron-up up\"><\/i>\n                <\/button>\n                <span id=\"toc-current-title\" class=\"d-flex align-items-center\">\n                    Table of Contents\n                <\/span>\n            <\/div>\n            <div  class=\"collapse my-3\" id=\"multiCollapse2\">\n                <ol class=\"StepProgress\">\n                    \t\t\t\t\t \t\t\t\t\t                                                     <li class=\"StepProgress-item current \">\n                                                    <div class=\"StepProgress-item__group\">\n                                <a data-id=\"key_takeaways\"\n                                   onclick=handleScrollToTitle(\"key_takeaways\")\n                                   class=\"StepProgress-item__link\"\n                                   data-level=\"2\">Key Takeaways<\/a>\n                                                            <\/div>\n                                                    <\/li>\n                    \t\t\t\t\t \t\t\t\t\t                                                     <li class=\"StepProgress-item \">\n                                                    <div class=\"StepProgress-item__group\">\n                                <a data-id=\"garbage_in_garbage_out\"\n                                   onclick=handleScrollToTitle(\"garbage_in_garbage_out\")\n                                   class=\"StepProgress-item__link\"\n                                   data-level=\"2\">Garbage In. Garbage Out.<\/a>\n                                                            <\/div>\n                                                    <\/li>\n                    \t\t\t\t\t \t\t\t\t\t                                                     <li class=\"StepProgress-item \">\n                                                    <div class=\"StepProgress-item__group\">\n                                <a data-id=\"why_dodgy_data_is_behind_those_ai_hallucinations\"\n                                   onclick=handleScrollToTitle(\"why_dodgy_data_is_behind_those_ai_hallucinations\")\n                                   class=\"StepProgress-item__link\"\n                                   data-level=\"2\">Why Dodgy Data Is Behind Those AI Hallucinations<\/a>\n                                                            <\/div>\n                                                    <\/li>\n                    \t\t\t\t\t \t\t\t\t\t\n\t\t\t\t\t\t <span class=\"show_moretoc\">Show Full Guide<\/span>\n\t\t\t\t\t\t \t\t\t\t\t \t\t\t\t\t\t  \t\t\t\t\t                                                      <li class=\"StepProgress-item ms_hidetoc\">\n                                                    <div class=\"StepProgress-item__group\">\n                                <a data-id=\"an_innovation_killer\"\n                                   onclick=handleScrollToTitle(\"an_innovation_killer\")\n                                   class=\"StepProgress-item__link\"\n                                   data-level=\"2\">An Innovation Killer<\/a>\n                                                            <\/div>\n                                                    <\/li>\n                    \t\t\t\t\t \t\t\t\t\t \t\t\t\t\t\t  \t\t\t\t\t                                                      <li class=\"StepProgress-item ms_hidetoc\">\n                                                    <div class=\"StepProgress-item__group\">\n                                <a data-id=\"maintaining_data_quality_is_hard\"\n                                   onclick=handleScrollToTitle(\"maintaining_data_quality_is_hard\")\n                                   class=\"StepProgress-item__link\"\n                                   data-level=\"2\">Maintaining Data Quality Is Hard<\/a>\n                                                            <\/div>\n                                                    <\/li>\n                    \t\t\t\t\t \t\t\t\t\t \t\t\t\t\t\t  \t\t\t\t\t                                                      <li class=\"StepProgress-item ms_hidetoc\">\n                                                    <div class=\"StepProgress-item__group\">\n                                <a data-id=\"ai_needs_data_does_data_need_ai\"\n                                   onclick=handleScrollToTitle(\"ai_needs_data_does_data_need_ai\")\n                                   class=\"StepProgress-item__link\"\n                                   data-level=\"2\">AI Needs Data. Does Data Need AI?<\/a>\n                                                            <\/div>\n                                                    <\/li>\n                    \t\t\t\t\t \t\t\t\t\t \t\t\t\t\t\t  \t\t\t\t\t                                                      <li class=\"StepProgress-item ms_hidetoc\">\n                                                    <div class=\"StepProgress-item__group\">\n                                <a data-id=\"the_bottom_line\"\n                                   onclick=handleScrollToTitle(\"the_bottom_line\")\n                                   class=\"StepProgress-item__link\"\n                                   data-level=\"2\">The Bottom Line<\/a>\n                                                            <\/div>\n                                                    <\/li>\n                    \t\t\t\t\t \t\t\t\t\t \t\t\t\t\t\t  \t\t\t\t\t                                                      <li class=\"StepProgress-item ms_hidetoc\">\n                                                    <div class=\"StepProgress-item__group\">\n                                <a data-id=\"faqs\"\n                                   onclick=handleScrollToTitle(\"faqs\")\n                                   class=\"StepProgress-item__link\"\n                                   data-level=\"2\">FAQs<\/a>\n                                                            <\/div>\n                                                    <\/li>\n                    \t\t\t\t\t \t\t\t\t\t \t\t\t\t\t\t  \t\t\t\t\t                                                      <li class=\"StepProgress-item ms_hidetoc\">\n                                                    <div class=\"StepProgress-item__group\">\n                                <a data-id=\"references\"\n                                   onclick=handleScrollToTitle(\"references\")\n                                   class=\"StepProgress-item__link\"\n                                   data-level=\"2\">References<\/a>\n                                                            <\/div>\n                                                    <\/li>\n                                    <\/ol>\n            <\/div>\n            <div class=\"toc-sticky__container__disperse\"><\/div>\n        <\/div>\n    <\/div>\n<\/div>\n\n<script id=\"toc-js\">\n    window.addEventListener(\"DOMContentLoaded\", () => {\n        const header = document.querySelector(\".header_wrapper\");\n\n        const pageLegend = document.querySelector('#multiCollapse1');\n        const pageLegendList = document.querySelector('#multiCollapse2');\n        const pageLegendCollapse = new bootstrap.Collapse(pageLegend, {toggle: document.querySelector(\".toc-sticky\").classList.contains('sticky')});\n\n        \/**\n         * Changing current title\n         *\/\n        (function (pageLegend) {\n            const titleNodes = pageLegend.querySelectorAll('.StepProgress-item__link');\n\n            if (!titleNodes.length) return;\n\n            const titles = [...titleNodes].map((itm, i) => ({\n                id: itm.getAttribute('data-id'),\n                text: itm.textContent,\n                level: itm.getAttribute('data-level'),\n                linkNode: itm,\n                titleNode: document.getElementById(itm.getAttribute('data-id')),\n                index: i,\n            }));\n\n            \/**\n             * Source: https:\/\/www.sitepoint.com\/throttle-scroll-events\/\n             * @param {Function} fn\n             * @param {number} wait\n             * @returns {(function(): void)|*}\n             *\/\n            const throttle = (fn, wait) => {\n                let time = Date.now();\n                return function () {\n                    if ((time + wait - Date.now()) < 0) {\n                        fn();\n                        time = Date.now();\n                    }\n                }\n            }\n\n            const changeCurrentTitle = () => {\n                const documentScrollTop = window.pageYOffset || document.documentElement.scrollTop || document.body.scrollTop || 0;\n                let current = 0;\n\n                \/\/ Title\n                titles.forEach((itm, i) => {\n\t\t\t\t\/\/console.log(itm)\n                    const itmOffsetTop = itm.titleNode ? 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-30 : -15;\n        window.scrollTo({\n            top: el.offsetTop - 60 - headerHeightDifference - 10,\n        });\n    }\n<\/script>\n\n<h2><span id=\"garbage_in_garbage_out\">Garbage In. Garbage Out.<\/span><\/h2>\n<p>GenAI\u2019s plausibility problem is getting harder to ignore.<\/p>\n<p>A November 2023 <a href=\"https:\/\/vectara.com\/blog\/cut-the-bull-detecting-hallucinations-in-large-language-models\/\" target=\"_blank\">study by Vectara<\/a>, an AI startup founded by ex-Google employees, found the frequency of GenAI hallucinations ranging from three percent for <a href=\"https:\/\/www.techopedia.com\/definition\/34933\/chatgpt\">ChatGPT<\/a> to 5% for <a href=\"https:\/\/www.techopedia.com\/meta-ai-ecosystem-a-snapshot-of-llama-3\">Meta\u2019s AI systems<\/a> and 8% for <a href=\"https:\/\/www.techopedia.com\/anthropic-unveils-claude-2-1-its-most-advanced-ai-assistant-yet\">Anthropic\u2019s Claude 2<\/a>. Google\u2019s PaLM came in highest at an eye-watering 27%.<\/p>\n<div class=\"infogram-embed\" data-id=\"b4cb9cfa-91e6-4226-ab10-2a666417d434\" data-type=\"interactive\" data-title=\"Untitled infographic\"><\/div>\n<p><script>!function(e,n,i,s){var d=\"InfogramEmbeds\";var o=e.getElementsByTagName(n)[0];if(window[d]&&window[d].initialized)window[d].process&&window[d].process();else if(!e.getElementById(i)){var r=e.createElement(n);r.async=1,r.id=i,r.src=s,o.parentNode.insertBefore(r,o)}}(document,\"script\",\"infogram-async\",\"https:\/\/e.infogram.com\/js\/dist\/embed-loader-min.js\");<\/script><\/p>\n<p>Figures from machine learning platform Aporia suggest that may be the <a href=\"https:\/\/www.aporia.com\/survey-2024\/\" target=\"_blank\">tip of the iceberg<\/a>.<\/p>\n<p>Nearly 90% of MLOps professionals working on AI projects told researchers that their models display signs of hallucination. Aporia\u2019s survey also found that 93% of engineers experience issues on a daily or weekly basis.<\/p>\n<div class=\"infogram-embed\" data-id=\"af387c6c-27db-4994-9ace-9c49a1f94a53\" data-type=\"interactive\" data-title=\"test\"><\/div>\n<p><script>!function(e,n,i,s){var d=\"InfogramEmbeds\";var o=e.getElementsByTagName(n)[0];if(window[d]&&window[d].initialized)window[d].process&&window[d].process();else if(!e.getElementById(i)){var r=e.createElement(n);r.async=1,r.id=i,r.src=s,o.parentNode.insertBefore(r,o)}}(document,\"script\",\"infogram-async\",\"https:\/\/e.infogram.com\/js\/dist\/embed-loader-min.js\");<\/script><\/p>\n<p>That\u2019s a lot of unreliable inferencing. While part of the blame rests with the models themselves, experts say poor training data is often the fail point.<\/p>\n<p><a href=\"https:\/\/www2.deloitte.com\/uk\/en\/profiles\/lobarnes.html\" target=\"_blank\"><strong>Lorraine Barnes<\/strong><\/a><strong>, UK Generative AI lead at Deloitte<\/strong>, told Techopedia that GenAI tools read patterns and \u201csometimes these patterns lead to unexpected or inaccurate outputs, even if the training data itself is high quality.\u201d<\/p>\n<p>But she adds that the importance of fit-for-purpose data \u201ccannot be overstated \u2014 especially in AI applications. Unlike traditional applications, AI often makes decisions or generates content that can directly impact business outcomes.<\/p>\n<blockquote><p>\u201cIf the data fed into the AI model is flawed, biased, or incomplete, the resulting decisions or outputs will be flawed as well.\u201d<\/p><\/blockquote>\n<h2><span id=\"why_dodgy_data_is_behind_those_ai_hallucinations\">Why Dodgy Data Is Behind Those AI Hallucinations<\/span><\/h2>\n<p>\u201cThere\u2019s a common assumption that the data (companies) have accumulated over the years is AI-ready, but that\u2019s not the case,\u201d <a href=\"https:\/\/centricconsulting.com\/blog\/no-ones-data-is-ready-for-ai-yet\/\" target=\"_blank\">writes<\/a> <strong>Joseph Ours, a Partner at Centric Consulting<\/strong>. \u201cThe reality is that no one has truly AI-ready data, at least not yet.\u201d<\/p>\n<p>He says firms have typically collected data primarily for immediate operational needs or to power analytics tools driven by humans. \u201cThis often leads to limited and gap-filled datasets. They might be rich in specific operational aspects but missing other potential dimensions.\u201d<\/p>\n<p>In layman\u2019s terms, that means corporate data sets can be riddled with duplicates, out-of-date information, or stored in hard-to-read formats. They can also be incomplete, of uncertain lineage, or collected in ways that skirt <a href=\"https:\/\/www.techopedia.com\/definition\/10380\/information-privacy\">data privacy<\/a> regulations.<\/p>\n<p>Bad data is both an AI and a business risk.<\/p>\n<h2><span id=\"an_innovation_killer\">An Innovation Killer<\/span><\/h2>\n<div class=\"infogram-embed\" data-id=\"6c6ab1d3-f12b-4a24-aaae-71220a36a0df\" data-type=\"interactive\" data-title=\"Untitled infographic\"><\/div>\n<p><script>!function(e,n,i,s){var d=\"InfogramEmbeds\";var o=e.getElementsByTagName(n)[0];if(window[d]&&window[d].initialized)window[d].process&&window[d].process();else if(!e.getElementById(i)){var r=e.createElement(n);r.async=1,r.id=i,r.src=s,o.parentNode.insertBefore(r,o)}}(document,\"script\",\"infogram-async\",\"https:\/\/e.infogram.com\/js\/dist\/embed-loader-min.js\");<\/script><\/p>\n<p>If an LLM contains data that\u2019s inaccurate, incomprehensible, or missing key details, it&#8217;s easy to see how it could make errors. Complicating matters further is the tendency to <strong>\u2018overfit<\/strong>,<strong>\u2019<\/strong> meaning the AI model memorizes the inputs and outputs it made using a sub-optimal data set. Its ability to generalize new data is compromised, creating the basis for hallucinations.<\/p>\n<p><a href=\"https:\/\/uk.linkedin.com\/in\/sue-daley-b13398b6\" target=\"_blank\"><strong>Sue Daley<\/strong><\/a><strong>, Director for Tech and Innovation at techUK<\/strong>, told Techopedia that Generative AI\u2019s effectiveness \u201chinges on the quality of data it\u2019s trained on.<\/p>\n<blockquote><p>\u201cIncomplete or inaccurate data may result in lower model accuracy, higher likelihood of bias, and in incorrect or factually inaccurate outputs.\u201d<\/p><\/blockquote>\n<p>That would make bad data an innovation killer. As far back as 2018, Gartner <a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2018-02-13-gartner-says-nearly-half-of-cios-are-planning-to-deploy-artificial-intelligence\" target=\"_blank\">famously predicted<\/a> that 85% of AI projects would fail due to bias in data or algorithms. Last year, the Harvard Business Review said plainly that \u2018<a href=\"https:\/\/hbr.org\/2023\/11\/keep-your-ai-projects-on-track\" target=\"_blank\">most AI projects fail<\/a>,\u2019 with \u2018availability, quantity, freshness, and overall quality of data\u2019 being a key barrier.<\/p>\n<p>While the AI juggernaut continues to dominate tech headlines at the corporate level, a lack of trust could still hinder investments in R&amp;D.<\/p>\n<h2><span id=\"maintaining_data_quality_is_hard\">Maintaining Data Quality Is Hard<\/span><\/h2>\n<p>With all the emphasis on business intelligence and analytics over the last two decades, why is data quality still a concern?<\/p>\n<p><a href=\"https:\/\/uk.linkedin.com\/in\/georgejohnston1\" target=\"_blank\"><strong>George Johnston<\/strong><\/a><strong>, data, privacy and analytics lead at Deloitte<\/strong>, told Techopedia there are several challenges in getting data quality right, but four stand out:<\/p>\n<div class=\"su-note\"  style=\"border-color:#e5e54c;border-radius:3px;-moz-border-radius:3px;-webkit-border-radius:3px;\"><div class=\"su-note-inner su-u-clearfix su-u-trim\" style=\"background-color:#FFFF66;border-color:#ffffff;color:#333333;border-radius:3px;-moz-border-radius:3px;-webkit-border-radius:3px;\">\n<ul>\n<li><strong>There\u2019s So Much of It:<\/strong> \u201cThe sheer volume and variety of data formats available today make it difficult to manage, clean, and maintain.\u201d<\/li>\n<li><strong>Siloes Make Unifying Data More Difficult:<\/strong> \u201cIntegrating data from diverse sources and systems often involves resolving inconsistencies, dealing with missing values, and data compatibility.\u201d<\/li>\n<li><strong>Legacy Systems Can&#8217;t Keep Up:<\/strong> \u201cMany organizations rely on outdated systems that were not designed to maintain data quality at the scale and complexity observed in today\u2019s system landscape.\u201d<\/li>\n<li><strong>Budgets, Tools, and Skill Sets May Be Lacking:<\/strong> \u201cGetting data quality right, requires resources, expertise, and tools. Many organizations struggle to secure the necessary funding for their data initiatives. This is often due to competing priorities, with other investments promising more immediate returns.\u201d<\/li>\n<\/ul>\n<\/div><\/div>\n<h2><span id=\"ai_needs_data_does_data_need_ai\">AI Needs Data. Does Data Need AI?<\/span><\/h2>\n<p>So what\u2019s the solution? Some say the symbiotic relationship between data and AI points to a solution.<\/p>\n<p><a href=\"https:\/\/www.techopedia.com\/definition\/5422\/data-management\">Data management<\/a> and <a href=\"https:\/\/www.techopedia.com\/definition\/16904\/data-governance-dg\">governance<\/a> vendors have begun adding \u2018AI-powered\u2019 to their descriptors. These platforms automate time- and labor-intensive tasks around data quality like <a href=\"https:\/\/www.techopedia.com\/definition\/1174\/data-cleansing\">cleaning<\/a>, <a href=\"https:\/\/www.techopedia.com\/definition\/25328\/data-extraction\">extracting<\/a>, <a href=\"https:\/\/www.techopedia.com\/definition\/28290\/data-integration\">integrating<\/a>, <a href=\"https:\/\/www.techopedia.com\/definition\/32034\/data-catalog\">cataloging<\/a>, <a href=\"https:\/\/www.techopedia.com\/definition\/33695\/labeled-data\">labeling<\/a>, and <a href=\"https:\/\/www.techopedia.com\/definition\/26464\/data-security\">securing<\/a> it. Adding an AI engine <a href=\"https:\/\/sloanreview.mit.edu\/article\/how-ai-is-improving-data-management\/\" target=\"_blank\">scales their capabilities<\/a> to meet the intense data and computational demands of LLMs.<\/p>\n<p>Investors have also woken up to the issue. Earlier this week, <a href=\"https:\/\/scale.com\/\" target=\"_blank\">Scale AI<\/a>, a startup specializing in data quality for AI applications, announced a <a href=\"https:\/\/www.reuters.com\/technology\/ai-startup-scale-ai-raises-1-billion-fresh-funding-2024-05-21\/\" target=\"_blank\">$1 billion funding round<\/a> backed by <a href=\"https:\/\/www.techopedia.com\/investing\/nvidia-stock-forecast\">Nvidia<\/a> (NVDA) and <a href=\"https:\/\/www.techopedia.com\/investing\/amazon-stock-forecast\">Amazon<\/a> (AMZN).<\/p>\n<p>New and better solutions for data management are part of the answer, but people and processes factor in too.<\/p>\n<p>TechUK\u2019s Daley says it demands a holistic approach:<\/p>\n<blockquote><p>\u201cIt involves significant investment in better infrastructure and tools, but also changes in organizational culture, data governance practices, and regulatory guidance. Given the systemic nature of these issues, addressing them will require data governance and management to be put at the top of each organization&#8217;s agenda, and should be supported by the next government\u2019s policy agenda.\u201d<\/p><\/blockquote>\n<p>Deloitte\u2019s Johnston points to more focused coordination between <a href=\"https:\/\/www.techopedia.com\/definition\/32046\/chief-data-officer-cdo\">Chief Data Officers<\/a> (CDOs) and Machine Learning Operations (MLOps) teams as a way to embed data quality into corporate culture. He says:<\/p>\n<p>\u201cA key point of intersection between the CDO and MLOps team lies in the iterative process of identifying and prioritizing data quality where it truly matters for specific AI projects. Rather than embarking on an exhaustive enterprise-wide data quality remediation programme, a more effective approach is to focus on improving the quality of data directly relevant to specific use cases.\u201d<\/p>\n<h2><span id=\"the_bottom_line\">The Bottom Line<\/span><\/h2>\n<p>Deloitte\u2019s Lorraine Barnes says it&#8217;s essential to ensure machine learning models are effective and reliable in real-world applications.<\/p>\n<blockquote><p>\u201cJust as a chef carefully selects the freshest, highest-quality ingredients to create a culinary masterpiece, AI developers must curate and pre-process data to ensure its accuracy, relevance, and representativeness.\u201d<\/p><\/blockquote>\n<p>One way or another, tech vendors, CDOs and <a href=\"https:\/\/www.techopedia.com\/definition\/30202\/data-science\">data science<\/a> teams need to deal with GenAI\u2019s data dilemma. Those <a href=\"https:\/\/www.reddit.com\/r\/ChatGPT\/comments\/12spg7d\/im_sorry_dave\/\" target=\"_blank\">HAL 9000 memes<\/a> aren&#8217;t going to go away on their own.<\/p>\n<h2><span id=\"faqs\">FAQs<\/span><\/h2>\n<div class=\"man_faq_sec\" itemscope itemtype=\"https:\/\/schema.org\/FAQPage\"><\/time><section class=\"ms_faq ms_card \" ><div itemscope itemprop=\"mainEntity\" itemtype=\"https:\/\/schema.org\/Question\"><div class=\"accordionButton\"><h3 itemprop=\"name\">Why is data quality important in generative AI?<\/h3> <\/div>\n<div class=\"accordionContent\" itemscope itemprop=\"acceptedAnswer\" itemtype=\"https:\/\/schema.org\/Answer\" style=\"display:none;\"><p itemprop=\"text\">Generative AI tools analyze huge data sets to identify patterns and predict outcomes. If the information being analyzed is inaccurate or incomplete, the patterns identified may be wrong \u2014 even if they follow logically from the flawed data.<\/p>\r\n                <\/div><\/div><\/section>\n<section class=\"ms_faq ms_card \" ><div itemscope itemprop=\"mainEntity\" itemtype=\"https:\/\/schema.org\/Question\"><div class=\"accordionButton\"><h3 itemprop=\"name\">Where can I get training data for machine learning?<\/h3> <\/div>\n<div class=\"accordionContent\" itemscope itemprop=\"acceptedAnswer\" itemtype=\"https:\/\/schema.org\/Answer\" style=\"display:none;\"><p itemprop=\"text\">Data sets are often built up over time by organizations, including customer, transactional, operational, and other kinds of information. Training data sets for AI can also be purchased from data vendors.<\/p>\r\n                <\/div><\/div><\/section>\n<section class=\"ms_faq ms_card \" ><div itemscope itemprop=\"mainEntity\" itemtype=\"https:\/\/schema.org\/Question\"><div class=\"accordionButton\"><h3 itemprop=\"name\">What type of data is used to train generative AI models?<\/h3> <\/div>\n<div class=\"accordionContent\" itemscope itemprop=\"acceptedAnswer\" itemtype=\"https:\/\/schema.org\/Answer\" style=\"display:none;\"><p itemprop=\"text\">The type of data used to train GenAI models depends on the application the AI will be primarily used for. Data scientists typically look for domain-specific data related to specialized fields, including banking, healthcare, and law.<\/p>\r\n                <\/div><\/div><\/section>\n<div class=\"reference-content\">\n<div class=\"reference-heading reference-content-collapsible-heading\">\n<h2><span id=\"references\">References<\/span><\/h2>\n<\/div>\n<div class=\"reference-content-body\">\n<ol>\n<li><a href=\"https:\/\/www.researchgate.net\/publication\/1775771_Information_and_Data_Quality_in_Spreadsheets\" target=\"_blank\">(PDF) Information and Data Quality in Spreadsheets<\/a>\u00a0(Researchgate)<\/li>\n<li><a href=\"https:\/\/vectara.com\/blog\/cut-the-bull-detecting-hallucinations-in-large-language-models\/\" target=\"_blank\">Cut the Bull\u2026. Detecting Hallucinations in Large Language Models<\/a>\u00a0(Vectara)<\/li>\n<li><a href=\"https:\/\/www.aporia.com\/survey-2024\/\" target=\"_blank\">2024 AI &amp; ML Report\u2028Evolution of Models &amp; Solutions &#8211; Aporia<\/a>\u00a0(Aporia)<\/li>\n<li><a href=\"https:\/\/www2.deloitte.com\/uk\/en\/profiles\/lobarnes.html\" target=\"_blank\">Lorraine Barnes | Deloitte UK<\/a>\u00a0(Www2.deloitte)<\/li>\n<li><a href=\"https:\/\/centricconsulting.com\/blog\/no-ones-data-is-ready-for-ai-yet\/\" target=\"_blank\">No One\u2019s Data is Ready for AI \u2013 Yet<\/a>\u00a0(Centricconsulting)<\/li>\n<li><a href=\"https:\/\/uk.linkedin.com\/in\/sue-daley-b13398b6\" target=\"_blank\">Sue Daley &#8211; techUK | LinkedIn<\/a>\u00a0(Uk.linkedin)<\/li>\n<li><a href=\"https:\/\/www.gartner.com\/en\/newsroom\/press-releases\/2018-02-13-gartner-says-nearly-half-of-cios-are-planning-to-deploy-artificial-intelligence\" target=\"_blank\">Gartner Says Nearly Half of CIOs Are Planning to Deploy Artificial Intelligence<\/a>\u00a0(Gartner)<\/li>\n<li><a href=\"https:\/\/hbr.org\/2023\/11\/keep-your-ai-projects-on-track\" target=\"_blank\">Keep Your AI Projects on Track<\/a>\u00a0(Hbr)<\/li>\n<li><a href=\"https:\/\/uk.linkedin.com\/in\/georgejohnston1\" target=\"_blank\">George Johnston<\/a>\u00a0(Uk.linkedin)<\/li>\n<li><a href=\"https:\/\/sloanreview.mit.edu\/article\/how-ai-is-improving-data-management\/\" target=\"_blank\">How AI Is Improving Data Management<\/a>\u00a0(Sloanreview.mit)<\/li>\n<li><a href=\"https:\/\/scale.com\/\" target=\"_blank\">Accelerate the Development of AI Applications | Scale AI<\/a>\u00a0(Scale)<\/li>\n<li><a href=\"https:\/\/www.reuters.com\/technology\/ai-startup-scale-ai-raises-1-billion-fresh-funding-2024-05-21\/\" target=\"_blank\">Scale AI valued at $14 bln in Nvidia, Amazon-backed funding round<\/a>\u00a0(Reuters)<\/li>\n<li><a href=\"https:\/\/www.reddit.com\/r\/ChatGPT\/comments\/12spg7d\/im_sorry_dave\/\" target=\"_blank\">I&#8217;m sorry Dave<\/a>\u00a0(Reddit)<\/li>\n<\/ol>\n<\/div>\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Worries about dodgy data have been with us since the dawn of spreadsheets. Now that GenAI has exploded onto the scene, questionable inputs are being blamed for the hallucinations and other odd behaviors that routinely plague LLMs. Data quality determines the reliability of AI outputs. If you don\u2019t have full confidence in the strings, floats, [&hellip;]<\/p>\n","protected":false},"author":286786,"featured_media":248268,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_lmt_disableupdate":"","_lmt_disable":"","om_disable_all_campaigns":false,"footnotes":""},"categories":[573,557],"tags":[],"category_partsoff":[],"class_list":["post-248160","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence","category-data-management"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v24.2 (Yoast SEO v24.5) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Poor Data Quality Is Killing Your AI Project, Experts Warn Techopedia<\/title>\n<meta name=\"description\" content=\"Good data or bad? The question MLOps teams need to ask about their AI training data. Poor data creates flawed outputs. 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The question MLOps teams need to ask about their AI training data. Poor data creates flawed outputs. 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