{"id":613414,"date":"2024-03-19T19:18:26","date_gmt":"2024-03-19T16:18:26","guid":{"rendered":"https:\/\/en.buradabiliyorum.com\/building-fairness-into-ai-is-crucial-and-hard-to-get-right\/"},"modified":"2024-03-19T19:18:26","modified_gmt":"2024-03-19T16:18:26","slug":"building-fairness-into-ai-is-crucial-and-hard-to-get-right","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/building-fairness-into-ai-is-crucial-and-hard-to-get-right\/","title":{"rendered":"#Building fairness into AI is crucial, and hard to get right"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_85 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-6a502bab96e82\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #dd3333;color:#dd3333\" 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: #dd3333;color:#dd3333\" 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><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-6a502bab96e82\" checked aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/buradabiliyorum.com\/en\/building-fairness-into-ai-is-crucial-and-hard-to-get-right\/#Why_fairness_in_AI_matters\" >Why fairness in AI matters<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/buradabiliyorum.com\/en\/building-fairness-into-ai-is-crucial-and-hard-to-get-right\/#Why_fairness_in_AI_is_hard\" >Why fairness in AI is hard<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/buradabiliyorum.com\/en\/building-fairness-into-ai-is-crucial-and-hard-to-get-right\/#Unintended_effects_on_fairness\" >Unintended effects on fairness<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/buradabiliyorum.com\/en\/building-fairness-into-ai-is-crucial-and-hard-to-get-right\/#The_path_forward\" >The path forward<\/a><\/li><\/ul><\/nav><\/div>\n<div>\n<div class=\"article-gallery lightGallery\">\n<div data-thumb=\"https:\/\/scx1.b-cdn.net\/csz\/news\/tmb\/2024\/ai-and-scale.jpg\" data-src=\"https:\/\/scx2.b-cdn.net\/gfx\/news\/hires\/2024\/ai-and-scale.jpg\" data-sub-html=\"Credit: Pixabay\/CC0 Public Domain\">\n<figure class=\"article-img\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/scx1.b-cdn.net\/csz\/news\/800a\/2024\/ai-and-scale.jpg\" alt=\"ai and scale\" title=\"Credit: Pixabay\/CC0 Public Domain\" width=\"800\" height=\"400\"\/><figcaption class=\"text-darken text-low-up text-truncate-js text-truncate mt-3\">\n                Credit: Pixabay\/CC0 Public Domain<br \/>\n            <\/figcaption><\/figure>\n<\/div>\n<\/div>\n<p>Artificial intelligence&#8217;s capacity to process and analyze vast amounts of data has revolutionized decision-making processes, making operations in <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/doi.org\/10.7861%2Ffhj.2021-0095\">health care<\/a>, <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/doi.org\/10.1287\/mnsc.2016.2644\">finance<\/a>, <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/nij.ojp.gov\/topics\/articles\/using-artificial-intelligence-address-criminal-justice-needs\">criminal justice<\/a> and other sectors of society more efficient and, in many instances, more effective.<\/p>\n<p>With this transformative power, however, comes a significant responsibility: the need to ensure that these technologies are developed and deployed in a manner that is <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/doi.org\/10.48550\/arXiv.1610.02413\">equitable and just<\/a>. In short, AI needs to be fair.<\/p>\n<p>The pursuit of fairness in AI is not merely an ethical imperative but a requirement in order to foster trust, inclusivity and the <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.whitehouse.gov\/briefing-room\/presidential-actions\/2023\/10\/30\/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence\/\">responsible advancement of technology<\/a>. However, ensuring that AI is fair is a major challenge. And on top of that, my research as a computer scientist <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/scholar.google.com\/citations?hl=en&amp;user=ASf9Q04AAAAJ&amp;view_op=list_works&amp;sortby=pubdate\">who studies AI<\/a> shows that attempts to ensure fairness in AI can have unintended consequences.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Why_fairness_in_AI_matters\"><\/span>Why fairness in AI matters<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Fairness in AI has emerged as a <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.aies-conference.com\/2024\/\">critical area of focus<\/a> for researchers, developers and policymakers. It transcends technical achievement, touching on <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/www.whitehouse.gov\/briefing-room\/presidential-actions\/2023\/10\/30\/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence\/\">ethical, social and legal dimensions of the technology<\/a>.<\/p>\n<p>                                                                                                        <!-- TechX - News - In-article --><\/p>\n<p>                                                                                                                                            Ethically, fairness is a cornerstone of building trust and acceptance of AI systems. People need to trust that AI decisions that affect their lives\u2014for example, hiring algorithms\u2014are made equitably. <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/social-mediaa\/\" data-internallinksmanager029f6b8e52c=\"1\" title=\"Social Media\" target=\"_blank\" rel=\"noopener\">Social<\/a>ly, AI systems that embody fairness can help address and mitigate historical biases\u2014for example, those against women and minorities\u2014fostering inclusivity. Legally, embedding fairness in AI systems helps bring those systems into alignment with anti-discrimination laws and regulations around the world.<\/p>\n<p>Unfairness can stem from two primary sources: the input data and the algorithms. Research has shown that input data can <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.2139\/ssrn.2477899\">perpetuate bias<\/a> in various sectors of society. For example, in hiring, algorithms processing data that reflects societal prejudices or lacks diversity can <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/doi.org\/10.1145\/3351095.3372828\">perpetuate &#8220;like me&#8221; biases<\/a>. These biases favor candidates who are similar to the decision-makers or those already in an organization. When biased data is then used to train a machine learning algorithm to aid a decision-maker, the algorithm can <a rel=\"nofollow noopener\" target=\"_blank\" href=\"http:\/\/proceedings.mlr.press\/v81\/buolamwini18a.html?mod=article_inline&amp;ref=akusion-ci-shi-dai-bizinesumedeia\">propagate and even amplify these biases<\/a>.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Why_fairness_in_AI_is_hard\"><\/span>Why fairness in AI is hard<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Fairness is inherently subjective, influenced by cultural, social and personal perspectives. In the context of AI, researchers, developers and policymakers often translate fairness to the idea that algorithms <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/fairmlbook.org\/index.html\">should not perpetuate or exacerbate<\/a> existing biases or inequalities.<\/p>\n<p>However, measuring fairness and building it into AI systems is fraught with subjective decisions and technical difficulties. Researchers and policymakers have proposed <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/doi.org\/10.48550\/arXiv.1610.02413\">various definitions of fairness<\/a>, such as demographic parity, equality of opportunity and individual fairness.<\/p>\n<figure class=\"mb-4\" itemscope=\"\" itemtype=\"http:\/\/schema.org\/VideoObject\"><meta itemprop=\"name\" content=\"Building fairness into AI is crucial\u2014and hard to get right\"\/><meta itemprop=\"url\" content=\"https:\/\/www.youtube.com\/watch\/?v=hZG9tyOcyx0\"\/><meta itemprop=\"description\" content=\"Why the concept of algorithmic fairness is so challenging.\"\/><meta itemprop=\"uploadDate\" content=\"2024-03-19T09:47:19-04:00\"\/><meta itemprop=\"embedUrl\" content=\"https:\/\/www.youtube.com\/embed\/hZG9tyOcyx0\"\/><meta itemprop=\"thumbnailUrl\" content=\"https:\/\/img.youtube.com\/vi\/hZG9tyOcyx0\/maxresdefault.jpg\"\/><br \/>\n             <iframe loading=\"lazy\" title=\"How To Make Algorithms Fairer | Algorithmic Bias and Fairness\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/hZG9tyOcyx0?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><figcaption class=\"text-darken text-low-up mt-4\" itemprop=\"caption\">Why the concept of algorithmic fairness is so challenging.<\/figcaption><\/figure>\n<p>These definitions involve different mathematical formulations and underlying philosophies. They also often conflict, highlighting the <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/doi.org\/10.1145\/3433949\">difficulty of satisfying all fairness criteria<\/a> simultaneously in practice.<\/p>\n<p>In addition, fairness cannot be distilled into a single metric or guideline. It encompasses a spectrum of considerations including, but not limited to, <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/fairmlbook.org\/index.html\">equality of opportunity, treatment and impact<\/a>.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Unintended_effects_on_fairness\"><\/span>Unintended effects on fairness<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The multifaceted nature of fairness means that AI systems must be scrutinized at every level of their development cycle, from the initial design and data collection phases to their final deployment and ongoing evaluation. This scrutiny reveals another layer of complexity. AI systems are seldom deployed in isolation. They are used as part of often complex and important decision-making processes, such as making recommendations about hiring or allocating funds and resources, and are subject to many constraints, including <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/dx.doi.org\/10.2139\/ssrn.4589207\">security and privacy<\/a>.<\/p>\n<p>                                                                                                        <!-- TechX - News - In-article --><\/p>\n<p>                                                                                                                                            Research my colleagues and I conducted shows that constraints such as <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/doi.org\/10.48550\/arXiv.2312.03886\">computational resources, hardware types<\/a> and <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/doi.org\/10.24963\/ijcai.2021\/78\">privacy<\/a> can significantly influence the fairness of AI systems. For instance, the need for computational efficiency can lead to simplifications that inadvertently overlook or misrepresent marginalized groups.<\/p>\n<p>In our study on network pruning\u2014a method to make complex machine learning models smaller and faster\u2014we found that this process <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/doi.org\/10.48550\/arXiv.2205.13574\">can unfairly affect certain groups<\/a>. This h<a href=\"https:\/\/buradabiliyorum.com\/en\/category\/download-scripts-themes-apps\/\" data-internallinksmanager029f6b8e52c=\"9\" title=\"Download Scripts &amp; Themes &amp; Apps\" target=\"_blank\" rel=\"noopener\">app<\/a>ens because the pruning might not consider how different groups are represented in the data and by the model, leading to biased outcomes.<\/p>\n<p>Similarly, privacy-preserving techniques, while crucial, can obscure the data necessary to identify and mitigate biases or disproportionally affect the outcomes for minorities. For example, when statistical agencies add noise to data to protect privacy, this can <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/doi.org\/10.24963\/ijcai.2021\/78\">lead to unfair resource allocation<\/a> because the added noise affects some groups more than others. This disproportionality can also <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/doi.org\/10.24963\/ijcai.2022\/766\">skew decision-making processes<\/a> that rely on this data, such as resource allocation for public services.<\/p>\n<p>These constraints do not operate in isolation but intersect in ways that compound their impact on fairness. For instance, when privacy measures exacerbate biases in data, it can further amplify existing inequalities. This makes it important to have a comprehensive understanding and approach to both privacy and fairness for AI development.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_path_forward\"><\/span>The path forward<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Making AI fair is not straightforward, and there are no one-size-fits-all solutions. It requires a process of continuous learning, adaptation and collaboration. Given that bias is pervasive in society, I believe that people working in the AI field should recognize that it&#8217;s not possible to achieve perfect fairness and instead strive for continuous improvement.<\/p>\n<p>This challenge requires a commitment to rigorous research, thoughtful policymaking and ethical practice. To make it work, researchers, developers and users of AI will need to ensure that considerations of fairness are woven into all aspects of the AI pipeline, from its conception through data collection and algorithm design to deployment and beyond.<\/p>\n<div class=\"d-inline-block text-medium my-4\">\n                                                Provided by<br \/>\n                                                                                                    The Conversation<br \/>\n                                                                                                        <a rel=\"nofollow noopener\" target=\"_blank\" class=\"icon_open\" href=\"https:\/\/theconversation.com\"><br \/>\n                                                        <svg><use href=\"https:\/\/techx.b-cdn.net\/tmpl\/v2\/img\/svg\/sprite.svg#icon_open\" x=\"0\" y=\"0\"\/><\/svg><\/a><\/p><\/div>\n<p>                                                                                                                            This article is republished from <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/theconversation.com\">The Conversation<\/a> under a Creative Commons license. Read the <a rel=\"nofollow noopener\" target=\"_blank\" href=\"https:\/\/theconversation.com\/building-fairness-into-ai-is-crucial-and-hard-to-get-right-220271\">original article<\/a>.<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/counter.theconversation.com\/content\/220271\/count.gif?distributor=republish-lightbox-advanced\" alt=\"The Conversation\" width=\"1\" height=\"1\"\/><\/p>\n<p>                                        <!-- print only --><\/p>\n<div class=\"d-none d-print-block\">\n<p>                                                <strong>Citation<\/strong>:<br \/>\n                                                Building fairness into AI is crucial, and hard to get right (2024, March 19)<br \/>\n                                                retrieved 19 March 2024<br \/>\n                                                from https:\/\/techxplore.com\/<a href=\"https:\/\/buradabiliyorum.com\/en\/category\/news\/\" data-internallinksmanager029f6b8e52c=\"2\" title=\"News\" target=\"_blank\" rel=\"noopener\">news<\/a>\/2024-03-fairness-ai-crucial-hard.html<\/p>\n<p>                                            This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no<br \/>\n                                            part may be reproduced without the written permission. The content is provided for information purposes only.<\/p><\/div>\n<\/p><\/div>\n<p><script id=\"facebook-jssdk\" async=\"\" src=\"https:\/\/connect.facebook.net\/en_US\/sdk.js\"><\/script><\/p>\n<blockquote><p><strong><span style=\"color: #ff6600;\">If you liked the article, do not forget to share it with your friends. Follow us on\u00a0<span style=\"color: #ff0000;\"><a style=\"color: #ff0000;\" href=\"https:\/\/news.google.com\/publications\/CAAqBwgKMN63nwsw68G3Aw\" target=\"_blank\" rel=\"nofollow noopener noreferrer\">Google News<\/a><\/span>\u00a0too, click on the star and choose us from your favorites.<\/span><\/strong><\/p><\/blockquote>\n<blockquote>\n<p style=\"text-align: center;\"><strong>If you want to read more Like this articles, you can visit our <span style=\"color: #ff9900;\"><a style=\"color: #ff9900;\" href=\"https:\/\/en.buradabiliyorum.com\/science\/\" target=\"_blank\" rel=\"noopener\">Science category.<\/a><\/span><\/strong><\/p>\n<\/blockquote>\n<p><span style=\"color: black;\"><a style=\"color: #ff9900;\" href=\"https:\/\/techxplore.com\/news\/2024-03-fairness-ai-crucial-hard.html\" target=\"_blank\" rel=\"noopener\">Source<\/a><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Credit: Pixabay\/CC0 Public Domain Artificial intelligence&#8217;s capacity to process and analyze vast amounts of data has revolutionized decision-making processes, making operations in health care, finance, criminal justice and other sectors of society more efficient and, in many instances, more effective. With this transformative power, however, comes a significant responsibility: the need to ensure that these&#8230;<\/p>\n","protected":false},"author":1,"featured_media":613415,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"https:\/\/scx2.b-cdn.net\/gfx\/news\/hires\/2024\/ai-and-scale.jpg","fifu_image_alt":"","footnotes":""},"categories":[16],"tags":[],"class_list":["post-613414","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sciencee"],"_links":{"self":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/613414","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/comments?post=613414"}],"version-history":[{"count":0,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/613414\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media\/613415"}],"wp:attachment":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media?parent=613414"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/categories?post=613414"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/tags?post=613414"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}