{"id":10181,"date":"2026-11-12T09:41:26","date_gmt":"2026-11-12T09:41:26","guid":{"rendered":"https:\/\/www.aom.org\/today\/?p=10181"},"modified":"2026-11-12T14:42:47","modified_gmt":"2026-11-12T14:42:47","slug":"when-ai-screwed-up-and-real-people-suffered","status":"publish","type":"post","link":"https:\/\/www.aom.org\/today\/when-ai-screwed-up-and-real-people-suffered\/","title":{"rendered":"When AI Screwed Up and Real People Suffered"},"content":{"rendered":"

By Daniel Butcher<\/a><\/p>\n

The stakes riding on whether or not AI gets it right are often high. In fact, when AI is trained on bad data or makes an error, sometimes people suffer.<\/p>\n

Academy of Management Scholar Christine Moser<\/a> of the Vrije Universiteit Amsterdam cited the example of the Dutch childcare benefits scandal known as \u201ctoeslagenaffaire,<\/em>\u201d which involved the Netherlands\u2019s tax authority wrongly accusing about 26,000 parents of fraud between 2005 and 2019, using discriminatory algorithms and ethnic profiling. The agency forced innocent families to repay large sums of money, causing severe financial hardship and the separation of more than 1,000 children from their families.<\/p>\n

\u201cThere\u2019s a more philosophical question here that goes back to the example that the tax authority in the Netherlands incorrectly identified thousands of individuals saying that they were fraudulently using childcare benefits, even though they were actually eligible,\u201d Moser said. \u201cAnd so it had a really negative impact on a lot of families who experienced severe financial consequences due to this fact that the error made by this AI algorithm wasn\u2019t double-checked and was just trusted by the tax authority that it was correct.<\/p>\n

\u201cIt went beyond financial consequences\u2014people had to sell their houses; the worst cases are suicides, but also children placed in foster care. And once they\u2019re in this foster-care system, it\u2019s super hard to get them out, because the family has been tainted by that which they haven\u2019t even caused themselves,\u201d she said. \u201cThat\u2019s another example of an algorithm that was designed to make life for the tax authorities more efficient and fairer as well, because they said, \u2018Oh, let\u2019s just figure out those who commit fraud to protect the bigger group of people who do not commit fraud,\u2019 but then, in the way that the algorithm was designed, and also in the way that the data were selected and then curated for the algorithm to work on this issue, the algorithm spit out that output because that\u2019s what it\u2019s designed to do.<\/p>\n

\u201cIt will give you output if you ask it to.\u201d<\/p>\n

It was alarming that no one at the organization bothered to check the accuracy of the AI outputs.<\/p>\n

\u201cIndeed, there was no human oversight, no judgment to actually look into what\u2019s going on here\u2014\u2018Is this actually correct?\u2019\u201d Moser said. \u201cThen it went into this bureaucratic machine preventing people from correcting these errors until it was way too late.<\/p>\n

\u201cThe Dutch government actually fell from power due to this scandal, which doesn\u2019t say much, because now we have another government that fell due to something else,\u201d she said.<\/p>\n

Moser noted similar cases in other countries, including a cautionary tale in Australia. The Australian Robodebt scheme used a faulty algorithm to automatically accuse more than 400,000 welfare recipients of debt between 2016 and 2019, causing immense distress and three known suicides.<\/p>\n

\u201cThis was a similar scheme where the government was supposed to give social benefits to people but used another algorithm to detect fraud, and this also went wrong,\u201d Moser said.<\/p>\n

In an incident called the Horizon IT scandal<\/a>, the British Post Office pursued thousands of innocent sub-postmasters for financial shortfalls that were actually caused by faults in a Fujitsu accounting software system.<\/p>\n

\u201cAnother one people might be familiar with is the UK Post Office scandal, where franchise-holders of post office subsidiaries were wrongly accused of fraud, of defrauding the system, leading to court cases there as well,\u201d Moser said. \u201cIt took years for the authorities to, first of all, see their mistake, and now they\u2019re still working to correct it.<\/p>\n

\u201cHere in the Netherlands, the mistakes of childcare benefits scandal still have not been corrected,\u201d she said. \u201cIt\u2019s been more than a decade now that these families have been suffering, and it\u2019s tens of thousands of people who have been affected here.<\/p>\n

\u201cIt\u2019s pretty insane.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"

By Daniel Butcher The stakes riding on whether or not AI gets it right are often high. In fact, when AI is trained on bad data or makes an error, sometimes people suffer. Academy of Management Scholar Christine Moser of the Vrije Universiteit Amsterdam cited the example of the Dutch childcare benefits scandal known as […]<\/p>\n","protected":false},"author":4,"featured_media":10110,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_ppma_block_editor_authors":""},"categories":[343,72,21,342],"tags":[],"sp_smart_badges":[],"ppma_author":[70],"class_list":["post-10181","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-ethics","category-innovation","category-technology"],"acf":[],"yoast_head":"\nWhen AI Screwed Up and Real People Suffered - Academy of Management Today<\/title>\n<meta name=\"description\" content=\"The stakes riding on whether or not AI gets it right are often high. 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You can reach him at dbutcher@aom.org or via LinkedIn.","sameAs":["https:\/\/aomtodayprod.wpenginepowered.com","https:\/\/www.linkedin.com\/in\/danielbutcher"],"url":"https:\/\/www.aom.org\/today\/author\/daniel-butcher\/"}]}},"authors":[{"term_id":70,"user_id":4,"is_guest":0,"slug":"daniel-butcher","display_name":"Daniel Butcher","avatar_url":{"url":"https:\/\/www.aom.org\/today\/wp-content\/uploads\/2025\/01\/DanButcher_Academy-of-Management.webp","url2x":"https:\/\/www.aom.org\/today\/wp-content\/uploads\/2025\/01\/DanButcher_Academy-of-Management.webp"},"avatar_alt":"","avatar_decorative":"","author_category":"1","first_name":"Daniel","last_name":"Butcher","user_url":"https:\/\/aomtodayprod.wpenginepowered.com","job_title":"Managing Editor, AOM Today, Academy of Management","description":"Daniel Butcher is a writer and the Managing Editor of AOM Today at the Academy of Management (AOM). Previously, he was a writer and the Finance Editor for <i>Strategic Finance<\/i> magazine and <i>Management Accounting Quarterly<\/i>, a scholarly journal, at the Institute of Management Accountants (IMA). Prior to that, he worked as a writer\/editor at <i>The Financial Times,<\/i> including daily FT sister publications <i>Ignites<\/i> and <i>FundFire<\/i>, as well as Crain Communications\u2019s <i>InvestmentNews<\/i> and <i>Crain\u2019s Wealth<\/i>, eFinancialCareers, and Arizent\u2019s <i>Financial Planning, Re:Invent|Wealth, On Wall Street, Bank Investment Consultant<\/i>, and <i>Money Management Executive<\/i>. He earned his bachelor\u2019s degree, Cum Laude, from the University of Colorado Boulder and his master\u2019s degree from New York University. You can reach him at <a href=\"mailto:dbutcher@aom.org\" target=\"_blank\" rel=\"noopener\">dbutcher@aom.org<\/a> or via <a href=\"https:\/\/www.linkedin.com\/in\/danielbutcher\" target=\"_blank\" rel=\"noopener\">LinkedIn<\/a>."}],"rttpg_featured_image_url":{"full":["https:\/\/www.aom.org\/today\/wp-content\/uploads\/2026\/10\/AI-interface-prompt-error-warning-system-alert.-AI-prompt-failure-leads-to-incorrect-output-or-hallucination.-safe-AI-deployment_cropped-scaled.jpg",2560,1707,false],"landscape":["https:\/\/www.aom.org\/today\/wp-content\/uploads\/2026\/10\/AI-interface-prompt-error-warning-system-alert.-AI-prompt-failure-leads-to-incorrect-output-or-hallucination.-safe-AI-deployment_cropped-scaled.jpg",2560,1707,false],"portraits":["https:\/\/www.aom.org\/today\/wp-content\/uploads\/2026\/10\/AI-interface-prompt-error-warning-system-alert.-AI-prompt-failure-leads-to-incorrect-output-or-hallucination.-safe-AI-deployment_cropped-scaled.jpg",2560,1707,false],"thumbnail":["https:\/\/www.aom.org\/today\/wp-content\/uploads\/2026\/10\/AI-interface-prompt-error-warning-system-alert.-AI-prompt-failure-leads-to-incorrect-output-or-hallucination.-safe-AI-deployment_cropped-150x150.jpg",150,150,true],"medium":["https:\/\/www.aom.org\/today\/wp-content\/uploads\/2026\/10\/AI-interface-prompt-error-warning-system-alert.-AI-prompt-failure-leads-to-incorrect-output-or-hallucination.-safe-AI-deployment_cropped-300x200.jpg",300,200,true],"large":["https:\/\/www.aom.org\/today\/wp-content\/uploads\/2026\/10\/AI-interface-prompt-error-warning-system-alert.-AI-prompt-failure-leads-to-incorrect-output-or-hallucination.-safe-AI-deployment_cropped-1024x683.jpg",800,534,true],"1536x1536":["https:\/\/www.aom.org\/today\/wp-content\/uploads\/2026\/10\/AI-interface-prompt-error-warning-system-alert.-AI-prompt-failure-leads-to-incorrect-output-or-hallucination.-safe-AI-deployment_cropped-1536x1024.jpg",1536,1024,true],"2048x2048":["https:\/\/www.aom.org\/today\/wp-content\/uploads\/2026\/10\/AI-interface-prompt-error-warning-system-alert.-AI-prompt-failure-leads-to-incorrect-output-or-hallucination.-safe-AI-deployment_cropped-2048x1365.jpg",2048,1365,true],"owl_elementor_thumbnail":["https:\/\/www.aom.org\/today\/wp-content\/uploads\/2026\/10\/AI-interface-prompt-error-warning-system-alert.-AI-prompt-failure-leads-to-incorrect-output-or-hallucination.-safe-AI-deployment_cropped-600x400.jpg",600,400,true],"owl_elementor_team":["https:\/\/www.aom.org\/today\/wp-content\/uploads\/2026\/10\/AI-interface-prompt-error-warning-system-alert.-AI-prompt-failure-leads-to-incorrect-output-or-hallucination.-safe-AI-deployment_cropped-350x450.jpg",350,450,true],"owl_elementor_testimonial":["https:\/\/www.aom.org\/today\/wp-content\/uploads\/2026\/10\/AI-interface-prompt-error-warning-system-alert.-AI-prompt-failure-leads-to-incorrect-output-or-hallucination.-safe-AI-deployment_cropped-100x100.jpg",100,100,true]},"rttpg_author":{"display_name":"Daniel Butcher","author_link":"https:\/\/www.aom.org\/today\/author\/daniel-butcher\/"},"rttpg_comment":0,"rttpg_category":"<a href=\"https:\/\/www.aom.org\/today\/category\/ai\/\" rel=\"category tag\">AI<\/a> <a href=\"https:\/\/www.aom.org\/today\/category\/ethics\/\" rel=\"category tag\">ETHICS<\/a> <a href=\"https:\/\/www.aom.org\/today\/category\/innovation\/\" rel=\"category tag\">INNOVATION<\/a> <a href=\"https:\/\/www.aom.org\/today\/category\/technology\/\" rel=\"category tag\">TECHNOLOGY<\/a>","rttpg_excerpt":"By Daniel Butcher The stakes riding on whether or not AI gets it right are often high. In fact, when AI is trained on bad data or makes an error, sometimes people suffer. Academy of Management Scholar Christine Moser of the Vrije Universiteit Amsterdam cited the example of the Dutch childcare benefits scandal known as…","_links":{"self":[{"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/posts\/10181","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/comments?post=10181"}],"version-history":[{"count":3,"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/posts\/10181\/revisions"}],"predecessor-version":[{"id":10184,"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/posts\/10181\/revisions\/10184"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/media\/10110"}],"wp:attachment":[{"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/media?parent=10181"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/categories?post=10181"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/tags?post=10181"},{"taxonomy":"sp_smart_badges","embeddable":true,"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/sp_smart_badges?post=10181"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.aom.org\/today\/wp-json\/wp\/v2\/ppma_author?post=10181"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}