{"id":35089,"date":"2026-07-29T07:00:56","date_gmt":"2026-07-29T11:00:56","guid":{"rendered":"https:\/\/www.wellable.co\/blog\/?p=35089"},"modified":"2026-07-29T07:01:00","modified_gmt":"2026-07-29T11:01:00","slug":"meta-workday-ai-lawsuit-employment-bias-work-situationship","status":"publish","type":"post","link":"https:\/\/www.wellable.co\/blog\/meta-workday-ai-lawsuit-employment-bias-work-situationship\/","title":{"rendered":"AI Lawsuits Capturing HR&#8217;s Attention"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">In this week&#8217;s episode, Nick and Geoff dig into two landmark AI employment lawsuits every HR leader should be following, and a new workforce sentiment story. Meta employees are&nbsp;<a href=\"https:\/\/www.hrdive.com\/news\/metas-ai-based-layoffs-allegedly-targeted-workers-who-had-taken-protected\/825325\/\" target=\"_blank\" rel=\"noreferrer noopener\">suing over an AI-driven layoff process<\/a>&nbsp;they claim targeted workers on protected leave. The&nbsp;<a href=\"https:\/\/www.hr-brew.com\/stories\/workdays-ai-lawsuit-keeps-spotlight-on-ai-powered-recruiting-as-case-works-through-courts\" target=\"_blank\" rel=\"noreferrer noopener\">Workday class action<\/a>&nbsp;advances on the question of whether AI vendors or their employer clients bear liability for hiring bias. Lastly, a&nbsp;<a href=\"https:\/\/www.hrdive.com\/news\/work-situationship-future-2026\/825632\/\" target=\"_blank\" rel=\"noreferrer noopener\">survey<\/a>&nbsp;shows younger workers increasingly describe their relationship with their employer as a &#8220;situationship&#8221; with no long-term commitment on either side.<\/p>\n\n\n\n<div class=\"video-embed\" style=\"position:relative;padding-bottom:56.25%;height:0;\">\n<iframe src=\"https:\/\/www.youtube.com\/embed\/F-1dfJ48PkY?si=vyHczY7ITDNoaPiY\" title=\"\nAI Lawsuits Capturing HR's Attention\" style=\"position:absolute;width:100%;height:100%;top:0;left:0;\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen=\"\">\n  <\/iframe>\n<\/div>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<div class=\"row justify-content-between\">\n<div class=\"cs-btn-light text-center mb-4 col-12 col-md-6 pr-md-4\">\n  <a class=\"cs-button d-flex align-items-center justify-content-center w-100\" href=\"https:\/\/podcasts.apple.com\/us\/podcast\/ai-lawsuits-capturing-hrs-attention\/id1869414001?i=1000778844784\" target=\"_blank\" style=\"gap: 8px\">\n\n<img decoding=\"async\" src=\"https:\/\/www.wellable.co\/blog\/wp-content\/uploads\/2026\/03\/Apple-Podcasts-logo.png\" alt=\"Apple podcast\" loading=\"lazy\" class=\"h-auto\" style=\"width: 24px\">\n\n<span style=\"font-size: 20px\">Listen on Apple Podcasts<\/span>\n<\/a>\n<\/div>\n\n<div class=\"cs-btn-light text-center mb-4 col-12 col-md-6 pl-md-4\">\n  <a class=\"cs-button d-flex align-items-center justify-content-center gap-3 w-100\" href=\"https:\/\/open.spotify.com\/episode\/7pcZe2AKe3HiMj7bOhIRDa?si=ZuDX2sg_RtWzQgWmj4EuDQ\" target=\"_blank\" style=\"gap: 8px\">\n\n<img decoding=\"async\" src=\"https:\/\/www.wellable.co\/blog\/wp-content\/uploads\/2026\/03\/Spotify_White_Logo.png\" alt=\"Apple podcast\" loading=\"lazy\" class=\"h-auto pr\" style=\"width: 24px\">\n<span style=\"font-size: 20px\">Listen on Spotify<\/span>\n\n<\/a>\n<\/div>\n<\/div>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n<div style=\"border: 1px solid rgb(0 0 0 \/ 0.1); padding: 25px 25px 10px; border-radius: 8px; box-shadow: 0 4px 6px -1px rgb(0 0 0 \/ 0.1), 0 2px 4px -2px rgb(0 0 0 \/ 0.1);\">\n<h3 id=\"h-pressed-for-time-here-s-a-quick-summary\" class=\"wp-block-heading nitoc\">Pressed for time? Here\u2019s a quick summary\u2026<\/h3>\n<ul>\n<li><span class=\"TextRun SCXW263571510 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW263571510 BCX0\">Twenty-six current and former Meta employees allege the company used AI to score, rank, and select employees for termination without neutralizing protected leave as an input<\/span><\/span><\/li>\n<li><span class=\"TextRun SCXW222904884 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW222904884 BCX0\">Meta&#8217;s spokesperson categorically denies AI made those decisions, creating a stark factual divide at the center of the case<\/span><\/span><\/li>\n<li><span class=\"TextRun SCXW121845233 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW121845233 BCX0\">Mobley v. Workday is advancing through the courts on the argument that AI hiring tools that replace functions normally performed by employers carry\u00a0<\/span><span class=\"NormalTextRun SCXW121845233 BCX0\">commensurate<\/span><span class=\"NormalTextRun SCXW121845233 BCX0\"> liability<\/span><\/span><\/li>\n<li><span class=\"TextRun SCXW237572081 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW237572081 BCX0\">Workday&#8217;s defense\u2014that its tools only screen candidates and final decisions rest with employers\u2014may be valid but puts its own customers on notice that they bear the liability for how AI outputs are used<\/span><\/span><\/li>\n<li><span class=\"TextRun SCXW173236725 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW173236725 BCX0\">HR and IT leaders should be asking vendors directly how their tools handle protected class attributes, what bias testing has been conducted, and where liability sits before using AI in any consequential hiring or termination process<\/span><\/span><\/li>\n<li><span class=\"TextRun SCXW28772110 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW28772110 BCX0\">59% of workers report no clear long-term path at their current employer, and the resulting &#8220;situationship&#8221; is partly a job market story<\/span><\/span><\/li>\n<li><span class=\"TextRun SCXW115802293 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW115802293 BCX0\">Employees cannot afford to leave but see no investment in their development either, a dynamic compounded by the hollowing out of middle management and the redirection of organizational energy toward AI over people<\/span><\/span><\/li>\n<\/ul>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"episode-summary\">Episode Summary<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"the-meta-lawsuit-did-ai-decide-who-got-fired\">The Meta Lawsuit: Did AI Decide Who Got Fired?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Meta has conducted some of the largest workforce reductions of the past two years, letting go of tens of thousands of employees across multiple rounds of cuts. A lawsuit filed by 26 current and former employees now alleges that those decisions were not made by managers with knowledge of their teams, but by a constellation of\u00a0<a href=\"https:\/\/www.wellable.co\/resources\/ai-for-hr\/\" target=\"_blank\" rel=\"noreferrer noopener\">internal AI systems<\/a>\u00a0that scored, ranked, and selected employees for termination, and that those systems disproportionately targeted workers who had taken protected leave in the preceding two years.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The legal concept at the center of the claim is what the lawsuit describes as Meta&#8217;s failure to &#8220;neutralize the inputs.&#8221; In plain terms: if an AI system is evaluating employee performance and productivity, and an employee spent part of that period on medical leave, parental leave, or other protected leave, the system should account for that gap before drawing conclusions about that person&#8217;s output. The allegation is that Meta&#8217;s system did not.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Meta&#8217;s response is categorical: a company spokesperson\u00a0stated\u00a0that workforce management and organizational decisions were made by people, not AI. That framing creates\u00a0a very clean\u00a0factual divide. This is not a case where both sides are arguing about whether the right precautions were taken. One side is claiming AI drove the decisions.\u00a0The other side is denying AI was used in a decision-making capacity.\u00a0The court will\u00a0ultimately have\u00a0to\u00a0determine\u00a0which account is\u00a0accurate, but the gap between the two positions is unusually wide.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Given Meta&#8217;s very public and ongoing commitment to AI across every aspect of the business, the claim that a major workforce restructuring was conducted entirely through human judgment, without any AI tooling in the process, will require convincing evidence to hold up.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"the-workday-lawsuit-when-the-vendor-becomes-the-defendant\">The Workday Lawsuit: When the Vendor Becomes the Defendant<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The Workday case, formally Mobley v. Workday, has been working through the courts and received renewed attention through reporting in Reuters and HR Brew. Where the Meta case is about how an internal AI system was used, the Workday case asks a different question: when an employer uses a third-party\u00a0<a href=\"https:\/\/www.wellable.co\/blog\/ai-hiring-bias-algorithmic-monoculture-uber-hr-layoffs\/\" target=\"_blank\" rel=\"noreferrer noopener\">AI platform that produces biased outcomes<\/a>\u00a0in hiring, who bears the legal liability?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Workday&#8217;s defense&nbsp;is similar to Meta&#8217;s:&nbsp;its tools screen&nbsp;candidates,&nbsp;they do not make hiring decisions. Final decisions&nbsp;remain&nbsp;with the employer. Therefore, Workday&nbsp;argues,&nbsp;any downstream legal violation sits with the company that used the tool, not the company that built it.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The court has refused to dismiss the case, and the reasoning matters. The judge&#8217;s position, as Nick describes it, is that an AI platform that effectively replaces functions a company would otherwise perform internally carries some of the responsibility that would have attached to those functions. The vendor cannot fully insulate itself behind the argument that the tool only&nbsp;assists&nbsp;rather than decides, if the practical effect of that&nbsp;assistance&nbsp;is that consequential choices are being driven by algorithmic outputs.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Nick notes that there is something strategically odd about Workday&#8217;s defense. If the argument to employers is that they bear full liability for how the&nbsp;tool&#8217;s&nbsp;outputs are used in decisions, that is essentially&nbsp;a caveat&nbsp;emptor message to the customers Workday is trying to sell to.&nbsp;It may be legally defensible, but it is not a comfortable position for a company whose growth depends on employer trust.&nbsp;<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The broader implication for HR leaders is practical. Both lawsuits expose a gap in how organizations are thinking about governance when&nbsp;<a href=\"https:\/\/www.wellable.co\/blog\/top-hr-ai-tools\/\" target=\"_blank\" rel=\"noreferrer noopener\">AI tools<\/a>&nbsp;are in the hiring or termination loop. Nick and Geoff both argue that HR leaders, alongside IT, need to be asking vendors direct questions: How does the tool handle protected class attributes? What bias testing has been conducted? Who bears responsibility if the tool&#8217;s outputs result in a disparate impact claim? Using AI in consequential employment decisions without clear answers to those questions is not a black box that insulates the organization from risk. It may be the opposite.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<h3 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"the-work-situationship-what-happens-when-companies-stop-investing-in-people\">The Work Situationship: What Happens When Companies Stop Investing in People<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The third story connects directly to the first two. A\u00a0<a href=\"https:\/\/zety.com\/blog\/workplace-situationships-report\" target=\"_blank\" rel=\"noreferrer noopener\">survey from Zety<\/a>\u00a0found that 59% of workers report having no clear long-term path and\u00a0not\u00a0looking forward to coming to work. Thirty-two percent say they have limited growth opportunities. Twenty-three percent describe feeling unfulfilled or frustrated. The term the research uses to describe the resulting dynamic is a &#8220;situationship,&#8221; borrowing from Gen Z relationship vocabulary: a casual arrangement with no clear commitment on either side<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Geoff and Nick are both clear that this is not purely a generational attitude story. The situationship exists for structural reasons on both sides of the relationship. Employees cannot leave because the current job market is difficult enough that testing it feels genuinely risky. Many have heard stories of hundreds of applications with no responses. But they also do not see a long-term future at their current company, because the signals of investment in their growth, development conversations, mentorship, career path clarity, are not there.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Nick connects this directly to the\u00a0<a href=\"https:\/\/www.wellable.co\/blog\/ai-digital-clone-middle-management-hiring\/\" target=\"_blank\" rel=\"noreferrer noopener\">middle management reduction<\/a>\u00a0trend. The managers who would traditionally have\u00a0been responsible for\u00a0those development conversations, who knew a young employee&#8217;s work well enough to sponsor them for a stretch assignment or advocate for their promotion, are the same layer being cut across the enterprise. And the energy that might otherwise go into talent development is being redirected toward AI agents and infrastructure.\u00a0The math\u00a0works in the short term. The long-term cost\u00a0shows up\u00a0years later, when companies look for experienced internal candidates to fill senior roles and find a bench that was never developed.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"frequently-asked-questions\">Frequently Asked Questions<\/h2>\n\n\n\n    <section class=\"faq-section\">\n      <div class=\"faq-accordion\">\n\n        \n        <div class=\"faq-item card card-faq\">\n          <button \n            class=\"faq-question\" \n            data-target=\"faq_1\"\n            type=\"button\"\n          >\n            What is the Meta AI layoff lawsuit about?            <span class=\"icon\"><\/span>\n          <\/button>\n\n          <div id=\"faq_1\" class=\"faq-answer\">\n            <p><span class=\"NormalTextRun SCXW105313584 BCX0\">Twenty-six current and former Meta employees have filed a lawsuit alleging that the company used a constellation of internal AI systems to score, rank, and select employees for termination during recent workforce reductions. The central claim is that these systems disproportionately affected workers who had taken protected\u00a0<\/span><span class=\"NormalTextRun SCXW105313584 BCX0\">leave, because<\/span><span class=\"NormalTextRun SCXW105313584 BCX0\">\u00a0the AI did not account for those absences when evaluating performance and productivity.\u00a0<\/span><span class=\"NormalTextRun SCXW105313584 BCX0\">Meta has denied that AI was used in a decision-making capacity, stating that workforce decisions were made by people.<\/span><\/p>\n          <\/div>\n        <\/div>\n\n        \n        <div class=\"faq-item card card-faq\">\n          <button \n            class=\"faq-question\" \n            data-target=\"faq_2\"\n            type=\"button\"\n          >\n            What does \"neutralize the inputs\" mean in the context of AI layoffs?            <span class=\"icon\"><\/span>\n          <\/button>\n\n          <div id=\"faq_2\" class=\"faq-answer\">\n            <p><span class=\"TextRun SCXW69469827 BCX0\" lang=\"EN-US\" xml:lang=\"EN-US\" data-contrast=\"auto\"><span class=\"NormalTextRun SCXW69469827 BCX0\">The term comes directly from the Meta lawsuit. It refers to the practice of adjusting or excluding certain data points from an AI evaluation to prevent protected attributes from influencing the outcome. In this case, the claim is that Meta&#8217;s AI systems scored employees on productivity and performance without neutralizing the impact of protected leave, meaning an employee who was on medical or parental leave during the evaluation period would be scored lower through no fault of their own.<\/span><\/span><\/p>\n          <\/div>\n        <\/div>\n\n        \n        <div class=\"faq-item card card-faq\">\n          <button \n            class=\"faq-question\" \n            data-target=\"faq_3\"\n            type=\"button\"\n          >\n            What is the Workday lawsuit about?            <span class=\"icon\"><\/span>\n          <\/button>\n\n          <div id=\"faq_3\" class=\"faq-answer\">\n            <p><span class=\"NormalTextRun SCXW221559950 BCX0\">Mobley v. Workday is a class action lawsuit arguing that Workday&#8217;s AI-powered hiring tools produce biased outcomes that disproportionately affect certain protected groups. The case&#8217;s central legal question is whether Workday, as the vendor whose platform functions as a substitute for decisions that would otherwise be made by employers directly, carries some of the liability for those outcomes. The court has refused to dismiss the case, finding the argument that the tool&#8217;s role goes beyond mere\u00a0<\/span><span class=\"NormalTextRun SCXW221559950 BCX0\">assistance<\/span><span class=\"NormalTextRun SCXW221559950 BCX0\">\u00a0to be legally credible.<\/span><\/p>\n          <\/div>\n        <\/div>\n\n        \n        <div class=\"faq-item card card-faq\">\n          <button \n            class=\"faq-question\" \n            data-target=\"faq_4\"\n            type=\"button\"\n          >\n            Who is liable when an AI hiring tool produces a biased outcome, the employer or the vendor?            <span class=\"icon\"><\/span>\n          <\/button>\n\n          <div id=\"faq_4\" class=\"faq-answer\">\n            <p><span class=\"NormalTextRun SCXW262912823 BCX0\">This is precisely what the Workday case is working to\u00a0<\/span><span class=\"NormalTextRun SCXW262912823 BCX0\">establish<\/span><span class=\"NormalTextRun SCXW262912823 BCX0\">. Workday&#8217;s position is that its tools only screen\u00a0<\/span><span class=\"NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW262912823 BCX0\">candidates<\/span><span class=\"NormalTextRun SCXW262912823 BCX0\">\u00a0and that final decisions rest with employers, making employers the\u00a0<\/span><span class=\"NormalTextRun SCXW262912823 BCX0\">appropriate defendant<\/span><span class=\"NormalTextRun SCXW262912823 BCX0\">. The court has pushed back on that framing, suggesting that a platform that effectively performs functions previously carried out by companies may carry\u00a0<\/span><span class=\"NormalTextRun SCXW262912823 BCX0\">commensurate<\/span><span class=\"NormalTextRun SCXW262912823 BCX0\">\u00a0responsibility. HR leaders should not assume that using a third-party AI tool insulates\u00a0<\/span><span class=\"NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW262912823 BCX0\">them from<\/span><span class=\"NormalTextRun SCXW262912823 BCX0\">\u00a0liability; the opposite may be true.<\/span><\/p>\n          <\/div>\n        <\/div>\n\n        \n        <div class=\"faq-item card card-faq\">\n          <button \n            class=\"faq-question\" \n            data-target=\"faq_5\"\n            type=\"button\"\n          >\n            What is a \"work situationship\" and why is it happening?            <span class=\"icon\"><\/span>\n          <\/button>\n\n          <div id=\"faq_5\" class=\"faq-answer\">\n            <p><span class=\"NormalTextRun SCXW226733105 BCX0\">The term describes a casual, uncommitted relationship between employees and their employers, one where neither side is fully invested in the long term. A\u00a0<\/span><span class=\"NormalTextRun SpellingErrorV2Themed SCXW226733105 BCX0\">Zeti<\/span><span class=\"NormalTextRun SCXW226733105 BCX0\">\u00a0survey found that 59% of workers have no clear long-term path at their current employer. The situationship persists because employees feel unable to\u00a0<\/span><span class=\"NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW226733105 BCX0\">leave<\/span><span class=\"NormalTextRun SCXW226733105 BCX0\">\u00a0in a difficult job market but see no meaningful investment in their development either. Nick and Geoff connect it to the hollowing out of middle management and the redirection of organizational energy toward AI infrastructure rather than\u00a0<\/span><span class=\"NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW226733105 BCX0\">people<\/span><span class=\"NormalTextRun SCXW226733105 BCX0\">\u00a0development.<\/span><\/p>\n          <\/div>\n        <\/div>\n\n        \n        <div class=\"faq-item card card-faq\">\n          <button \n            class=\"faq-question\" \n            data-target=\"faq_6\"\n            type=\"button\"\n          >\n            What should HR leaders do to protect their organizations from AI employment liability?            <span class=\"icon\"><\/span>\n          <\/button>\n\n          <div id=\"faq_6\" class=\"faq-answer\">\n            <p><span class=\"NormalTextRun SCXW248283480 BCX0\">Nick and Geoff\u00a0<\/span><span class=\"NormalTextRun SCXW248283480 BCX0\">identify<\/span><span class=\"NormalTextRun SCXW248283480 BCX0\">\u00a0three practical steps. First, ask vendors directly how their tools handle protected class attributes and what bias testing has been conducted. Second, ensure that consequential employment decisions, both in hiring and in terminations, have a documented human review process that is not purely derivative of AI outputs. Third, work with IT and legal to assess whether current AI tool usage creates disparate impact exposure, particularly in any process that evaluates large numbers of employees simultaneously.<\/span><\/p>\n          <\/div>\n        <\/div>\n\n        \n      <\/div>\n    <\/section>\n\n    \n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<h2 class=\"wp-block-heading\" class=\"wp-block-heading\" id=\"full-episode-transcript\"><strong style=\"color: transparent; visibility: hidden; opacity: 0;\">Full Episode Transcript<\/strong><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n    <section class=\"faq-section toc-helper-accordion\">\n      <div class=\"faq-accordion\">\n\n        \n        <div class=\"custom-accordion-item\">\n          <button \n            class=\"faq-question\" \n            data-target=\"transcript_1\"\n            type=\"button\"\n          >\n            <h2 id=\"full-episode-transcript\"><strong>Full Episode Transcript<\/strong><\/h2>\n            <span class=\"icon\"><\/span>\n          <\/button>\n\n          <div id=\"transcript_1\" class=\"faq-answer\">\n            <p><b><span data-contrast=\"auto\">Nick:<\/span><\/b><span data-contrast=\"auto\">\u00a0Welcome to the\u00a0Wellable\u00a0Weekly Podcast, where we talk about key topics and trends at the intersection of wellbeing, technology, and HR. Geoff, I\u00a0can&#8217;t\u00a0believe\u00a0it&#8217;s\u00a0the end of July.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Geoff:<\/span><\/b><span data-contrast=\"auto\">\u00a0No, summer is flying by. It always happens like\u00a0this\u00a0though, right? We get into June, it starts to warm up, and then all of a\u00a0sudden\u00a0we&#8217;re wrapping\u00a0up\u00a0the end of summer.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Nick:<\/span><\/b><span data-contrast=\"auto\">\u00a0I always feel like\u00a0that&#8217;s\u00a0the case, but this summer for some reason feels just a little bit quicker.\u00a0We&#8217;re\u00a0from Boston, so the end of summer means the coming of fall, which is\u00a0very nice, but then also means the coming of winter. Lots of exciting stuff happening this summer, including maybe some not so exciting news if you&#8217;re part of this process \u2014 a couple of big lawsuits related to AI that are worth talking about because it&#8217;s really HR&#8217;s use of AI that&#8217;s generated these two major lawsuits against two big companies.\u00a0We&#8217;re\u00a0talking about Meta and Workday.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Meta is interesting because the lawsuit was filed by a group of current and former Meta employees \u2014 26 of them \u2014 saying that the use of AI in these recent layoffs disproportionately affected certain workers, specifically workers who took protected leave in the last two years.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Geoff:<\/span><\/b><span data-contrast=\"auto\">\u00a0If Meta really did miss this, how did they not consider that as part of the criteria when they ran their process to shortlist workers for potential termination? I know it sounds like they were using internal AI tools to make the process more efficient, and\u00a0probably in\u00a0their minds more\u00a0accurate\u00a0\u2014 the idea being that AI can produce a truly objective output without human bias. Meta has categorically denied any wrongdoing. But it seems like one of those things where if they did run an AI-led termination program, how could you not consider gaps in productivity due to medical leave? It just seems too big to miss.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Nick:<\/span><\/b><span data-contrast=\"auto\">\u00a0It was someone&#8217;s job to think about something like this. The term in the lawsuit is that the company &#8220;did not neutralize the inputs.&#8221; To your point, protected leave would be an input you would need to consider when thinking about productivity over\u00a0a period of time.\u00a0What&#8217;s really interesting is that Meta&#8217;s spokesperson isn&#8217;t saying they used AI but took proper precautions.\u00a0The claim says Meta used a constellation of internal AI systems to score, rank, and select employees for inclusion on the termination list. And the Meta spokesperson says: workforce management and organizational decisions were made by people, not AI.\u00a0So\u00a0one of these groups is simply\u00a0right\u00a0and the other is simply wrong.\u00a0It&#8217;s a very clear factual divide.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Geoff:<\/span><\/b><span data-contrast=\"auto\">\u00a0And\u00a0it&#8217;s\u00a0a very deliberate use of language. You can picture how they would use an internal AI system for a process like this, given their very public commitment to applying AI across all forms of their business.\u00a0It&#8217;s\u00a0not beyond reasonable doubt that they would try to do something similar for an internal process like this. And Meta is not the only organization to come under fire recently for the use of AI tools in people-related activities. Workday, which we touched on in the Stanford study episode, has a class action lawsuit continuing to move through the courts. A recent Reuters and HR Brew article unpacked the Mobley v. Workday case, and\u00a0it&#8217;s\u00a0really interesting\u00a0to learn not only about the potential algorithmic biases at issue, but just how extensively companies are using AI in their talent acquisition processes today. That stat we mentioned before, that 90% of all companies are using AI in their talent acquisition process, keeps coming back up.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Nick:<\/span><\/b><span data-contrast=\"auto\">\u00a0Workday is a very well-known HR platform. Many of our listeners are\u00a0probably using\u00a0it. And as with most of these AI tools, they make the process more\u00a0efficient, but\u00a0can introduce bias in a variety of ways. In the Workday case, the judge has refused to dismiss the lawsuit. The core argument the court found credible is that Workday&#8217;s AI function effectively replaces jobs and responsibilities that would normally be carried out by the company itself. By doing that, Workday takes on some of that responsibility.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Workday&#8217;s response is that their AI tools for screening resumes and applicants do not make hiring decisions. They simply help screen candidates. The ultimate decision falls on the employer.\u00a0So\u00a0they are arguing\u00a0they&#8217;re\u00a0not liable \u2014 the company using their tool is the one liable. Which is interesting, because\u00a0you&#8217;re\u00a0effectively telling your customers: use our product, and if\u00a0there&#8217;s\u00a0an issue, you should be the one being sued.\u00a0That&#8217;s\u00a0an odd argument to make to your own customer base.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">The laws being touched here are significant: ADA, the Family and Medical Leave Act in Meta&#8217;s case, the Pregnancy Discrimination Act. AI is touching all of these because of the sheer volume of decisions being processed. The scale is what creates\u00a0the legal\u00a0exposure. I think HR leaders, alongside IT, need to be asking vendors direct questions about how their tools handle protected attributes, what bias testing has been done, and where liability\u00a0sits\u00a0if something goes wrong.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Geoff:<\/span><\/b><span data-contrast=\"auto\">\u00a0All of\u00a0that time and energy being poured into analyzing AI&#8217;s impact, both the efficiencies and the risks, means less focus on people. Good old-fashioned career development, mentoring, the\u00a0tried-and-true methods of workforce\u00a0management,\u00a0are getting less attention. That connects to the last article I wanted to talk about: how work is feeling like a situationship. A casual dating scenario \u2014 not something in the vocabulary of two happily married guys, but\u00a0it&#8217;s\u00a0certainly how Gen Z and others are describing how they feel about their employer. A lack of commitment in both directions, where employees\u00a0don&#8217;t\u00a0feel the company has a long-term plan for\u00a0them\u00a0and they\u00a0don&#8217;t\u00a0feel loyalty or long-term commitment to the company either.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Nick:<\/span><\/b><span data-contrast=\"auto\">\u00a0To put some color on it, the survey is from a company called\u00a0Zeti. Some stats: 59% of workers say they have no clear long-term path and\u00a0don&#8217;t\u00a0look forward to their current workplace. 32% say they have limited growth opportunities. 23% report feeling unfulfilled or frustrated.\u00a0That&#8217;s\u00a0the situationship.\u00a0They&#8217;re kind of just in a situation with their company.\u00a0And the reason they stay is that they\u00a0can&#8217;t\u00a0leave. The job market\u00a0isn&#8217;t\u00a0super attractive.\u00a0They&#8217;re\u00a0hearing stories about people\u00a0submitting\u00a0a hundred applications and not getting one response. Some of\u00a0it&#8217;s\u00a0true, some\u00a0is\u00a0perception, but the\u00a0perception\u00a0is\u00a0very clear: you\u00a0don&#8217;t\u00a0want to test the market right now.\u00a0So\u00a0they&#8217;re\u00a0staying somewhere they\u00a0don&#8217;t\u00a0see a long-term future, but\u00a0they&#8217;re\u00a0not out there searching for\u00a0what&#8217;s\u00a0next.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">We talked last week about middle managers being cut, but it&#8217;s the same concept. So many companies are focusing their best talent on developing AI agents rather than developing their people. You&#8217;re cutting the middle managers who could supplement talent development. You don&#8217;t feel the cost of that immediately, but eventually you come to your bench and ask: who&#8217;s our next up-and-coming star? Do they have the skills developed over the last five years to rise up? If you don&#8217;t invest now, you will feel it later. And the argument that you&#8217;ll just hire that talent externally misses something important: when you work with a young person for five or ten years, promote them to something senior, you have a history of knowledge about how they work and they have a history of knowing the company. That institutional alignment goes away when you only hire from outside.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">Geoff:<\/span><\/b><span data-contrast=\"auto\">\u00a0There was a quote in that article from an anonymous Workday executive, of all companies: AI may be rewriting the rules of work, but it cannot replace the value of engaged, motivated people. That sums it up well. When things are changing this quickly and the focus on technology is this strong, it&#8217;s harder and harder to keep people feeling genuinely invested. That seems like a good place to wrap up. Thanks as always to those who tune in. You can get Wellable Weekly on Apple Podcasts, Spotify, or wherever you get your podcasts. Be sure to subscribe to the Wellable Weekly newsletter. Thank you.<\/span><\/p>\n          <\/div>\n        <\/div>\n\n        \n      <\/div>\n    <\/section>\n\n    \n","protected":false},"excerpt":{"rendered":"<p>Wellable Weekly breaks down two landmark AI employment lawsuits against Meta and Workday, what they mean for HR leaders using AI tools, and why younger workers are describing their relationship with their employer as a &#8220;situationship.&#8221;<\/p>\n","protected":false},"author":1,"featured_media":35103,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[23],"tags":[],"class_list":["post-35089","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-podcasts"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.6 (Yoast SEO v27.7) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ 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