{"id":5229,"date":"2026-09-15T13:12:02","date_gmt":"2026-09-15T13:12:02","guid":{"rendered":"https:\/\/cake.com\/blog\/?p=5229"},"modified":"2026-09-15T13:13:10","modified_gmt":"2026-09-15T13:13:10","slug":"ai-doesnt-hallucinate-it-bullshits","status":"publish","type":"post","link":"https:\/\/cake.com\/blog\/ai-doesnt-hallucinate-it-bullshits\/","title":{"rendered":"AI Doesn\u2019t Hallucinate. It Bullshits! (In the Psychological Sense)"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">In the context of AI, hallucination is a <strong>misleading metaphor<\/strong> that fools you into making incorrect assumptions about what AI is and how it works. By using humanlike language like &#8220;hallucination&#8221;, AI companies deflect accountability and build unwarranted hype around their product, making it seem much more capable than it is.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Let\u2019s unpack why the term hallucination isn\u2019t a good metaphor, why it\u2019s more accurate to call all AI output bullshit, and why what you call it matters.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Disclaimer:<\/strong> In psychology, bullshit means communication that\u2019s indifferent to both truth and falsehood. In this article, every time the word is used, it\u2019s referring to this kind of communication.<\/p>\n\n\n\n<ul class=\"wp-block-list key-takeaways\">\n<li>Calling undesired AI output hallucinations is misleading, as it implies hallucinations are bugs. Hallucinations in LLMs aren\u2019t bugs \u2014 the process that produces desired and undesired outputs is one and the same.<\/li>\n\n\n\n<li>LLMs hallucinate all the time; you only notice it when the output is particularly bad.<\/li>\n\n\n\n<li>Using humanlike language for AI terms creates a serious business risk by masking the technology\u2019s unpredictability.<\/li>\n<\/ul>\n\n\n\n<h2 id=\"metaphorical-extensions-what-they-are-and-how-theyre-supposed-to-work\" class=\"wp-block-heading\">Metaphorical extensions \u2014 what they are and how they\u2019re supposed to work<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Metaphorical extension is what you get when a word\u2019s meaning expands to include new concepts based on structural or functional similarities.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Take viruses, for example. A virus is a biological entity that invades a host organism and disrupts biological functions. A computer virus is malicious code that invades a host file or program and corrupts system operations.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">One may be biological and the other digital, but you can see how calling this malicious code a <em>virus<\/em> is helpful. It lets even people who don\u2019t know much about computers quickly and correctly intuit what a computer virus is.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This is a metaphorical extension at its best. And, if you think human hallucinations and <a href=\"https:\/\/www.ibm.com\/think\/topics\/ai-hallucinations\" target=\"_blank\" rel=\"noreferrer noopener\">AI hallucinations<\/a> share these kinds of similarities, think again.<\/p>\n\n\n\n<h2 id=\"hallucination-isnt-a-metaphorical-extension-its-glosslighting\" class=\"wp-block-heading\">Hallucination isn\u2019t a metaphorical extension \u2014 it\u2019s glosslighting<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Using the term hallucination for inaccurate AI output doesn\u2019t help you to intuit what AI hallucinations are. That\u2019s because it\u2019s not a metaphorical extension \u2014 it\u2019s <a href=\"https:\/\/arxiv.org\/html\/2604.21043v1\" target=\"_blank\" rel=\"noreferrer noopener\">glosslighting<\/a>.<\/p>\n\n\n\n<p class=\"has-background wp-block-paragraph\" style=\"background-color:#e5f6fe\">Glosslighting is a naming convention that deceptively uses evocative, humanlike words to build hype, obscure understanding, and shape public perception, all while hiding behind a narrow technical description for plausible deniability.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Let\u2019s see how this works by using AI agents as an example. The word &#8220;agent&#8221; suggests an autonomous entity with free will and intent. The narrow technical definition of an AI agent is \u201c<em>a program that maps inputs to outputs, possibly with a reward signal or iterative loop.<\/em>\u201d<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The humanlike term inspires more confidence and suggests grander capabilities than the technical definition. It also deflects blame from the company to the agent.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The same applies to every humanlike term used in AI, from intelligence and understanding to thinking and reasoning \u2014 they\u2019re all glosslighting; not one is a metaphorical extension that lets you intuit what\u2019s actually going on.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Glosslighting lets companies get all the financial and social benefits of tricking the public into thinking AI is practically human<\/strong>, while dodging legal, scientific, and moral accountability. Investors and politicians hear these impressive words and assume the technology is incredibly advanced, which helps the AI companies drive excitement, boost stock prices, and secure massive funding.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">And hallucination is the most harmful example of glosslighting for you, because it misleads you about the sheer scope of inaccuracy you should expect from AI. This can seriously harm your business and its reputation, so it\u2019s good to understand exactly what you\u2019re dealing with.<\/p>\n\n\n\n<div class=\"wp-block-group pro-tip\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<p class=\"wp-block-paragraph\"><strong>Further reading<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Check out this article to find out what makes a job AI-proof and position yourself as irreplaceable:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/cake.com\/blog\/ai-proof-careers\/\" target=\"_blank\" rel=\"noreferrer noopener\">AI-Proof Careers: Human Roles That AI Can\u2019t Replace<\/a><\/li>\n<\/ul>\n<\/div><\/div>\n\n\n\n<h2 id=\"so-what-are-hallucinations-really\" class=\"wp-block-heading\">So what are hallucinations, really?<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">In humans, a hallucination is an error in perception and neurochemistry. Something in your brain goes haywire, and you see or hear things that aren\u2019t real as a result. You can think of it like a bug. It\u2019s also binary \u2014 you\u2019re either hallucinating, or you\u2019re not.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">None of this is true with AI hallucinations \u2014 they\u2019re not bugs, and they\u2019re not binary.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The <a href=\"https:\/\/leonfurze.com\/2026\/06\/28\/what-are-ai-hallucinations\/\" target=\"_blank\" rel=\"noreferrer noopener\">technical definition of AI hallucinations<\/a> is: &#8220;<em>Output from a language model that is fluent and plausible but factually wrong, unsupported, or fabricated.<\/em>&#8221; This technical definition most closely resembles the <a href=\"https:\/\/link.springer.com\/article\/10.1007\/s10676-024-09775-5\" target=\"_blank\" rel=\"noreferrer noopener\">psychological concept of bullshit<\/a> \u2014 grammatically accurate text or speech that\u2019s indifferent to truth and lies.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A liar is someone who knows the truth and intentionally deceives. A bullshitter doesn\u2019t care either way if what they say is true or false. Large language models (LLMs) are bullshitters.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">But let\u2019s focus on the 2 key differences between human hallucinations and LLM bullshit, because they reveal a lot about the scope of the glosslighting at play here.<\/p>\n\n\n\n<h3 id=\"ai-hallucinations-arent-bugs-theyre-baked-in\" class=\"wp-block-heading\">AI hallucinations aren\u2019t bugs \u2014 they\u2019re baked in<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">To explain why hallucinations aren\u2019t bugs, let\u2019s quickly go over how LLMs work. An LLM is just a next-token predictor.<\/p>\n\n\n\n<p class=\"has-background wp-block-paragraph\" style=\"background-color:#e5f6fe\">Think of LLM tokens as words \u2014 it\u2019s not 100% correct, but it\u2019s close enough for you to completely understand the point.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The LLM looks at all the tokens in the conversation so far and outputs the next token based on complex statistical probability calculations. Because an <a href=\"https:\/\/www.ey.com\/en_nl\/insights\/ai\/ai-hallucinations-risks-causes-and-solutions\" target=\"_blank\" rel=\"noreferrer noopener\">LLM isn\u2019t a database<\/a>, it has nowhere to retrieve answers from, so the token-prediction process is basically guessing. The LLM just guesses one token at a time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Here\u2019s an example:<\/strong> When you ask an LLM what the capital of Japan is, it doesn\u2019t know the answer. Instead, it calculates that the token for <em>Tokyo<\/em> correlates the most highly with tokens for <em>Japan<\/em> and <em>capital city<\/em>. The math is more complex than I\u2019m making it out to be, but it always ends with the LLM assigning 1 token the dominant probability.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If it outputs &#8220;Tokyo&#8221;, we say that it\u2019s telling the truth, and if it outputs &#8220;Kyoto&#8221;, we say that it\u2019s hallucinating. But there is <a href=\"https:\/\/buttondown.com\/maiht3k\/archive\/how-to-talk-about-ai-without-adding-to-the\/\" target=\"_blank\" rel=\"noreferrer noopener\">no difference between desirable and undesirable outputs<\/a> to the LLM. The exact same process, working as designed, generates both outputs, which means the undesirable output isn\u2019t the result of a bug. It\u2019s the result of a gamble that didn\u2019t pay off.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To use a simple analogy, if you threw a die hoping for a 6, and it landed on a 1, you wouldn\u2019t say that the die hallucinated. It did exactly what it was supposed to; it generated a statistically probable output. (You just didn\u2019t like the output.)<\/p>\n\n\n\n<div class=\"wp-block-group pro-tip\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<p class=\"wp-block-paragraph\"><strong>Further reading<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To learn more about the state of AI in the workplace, check out the latest AI statistics:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/cake.com\/blog\/ai-statistics-2026\/\" target=\"_blank\" rel=\"noreferrer noopener\">The State of AI in the Workplace Statistics 2026<\/a><\/li>\n<\/ul>\n<\/div><\/div>\n\n\n\n<h3 id=\"ai-hallucinations-arent-binary-llms-always-hallucinate\" class=\"wp-block-heading\">AI hallucinations aren\u2019t binary \u2014 LLMs always hallucinate<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">It\u2019s better for AI companies if you think hallucinations are binary, because it frames hallucinations as rare errors produced by an otherwise truth-telling machine. But this just isn\u2019t the case. To quote former OpenAI founding member Andrej Karpathy: \u201c<a href=\"https:\/\/x.com\/karpathy\/status\/1733299213503787018\" target=\"_blank\" rel=\"noreferrer noopener\"><em>Hallucination is all LLMs do<\/em><\/a>.\u201d We only notice it when the output is especially obvious.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">To illustrate how this works, let\u2019s once again compare LLM outputs to dice rolls, only this time, we\u2019ll throw 10 dice. The sum total of this roll is anywhere between 10 and 60, with 35 being the average.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The LLM\u2019s output is only completely accurate when you roll 35. If you get a number that\u2019s way off from the average, like 13 or 54, it\u2019ll be obvious to you that the AI hallucinated. But what if the output is 27 or 39? <strong>The hallucination could be small enough that you don\u2019t notice it<\/strong>, but perhaps not so small that it can\u2019t cause harm.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">So, LLMs hallucinate all the time; it\u2019s just a matter of how much. Even if the output is completely factually accurate, it\u2019s still a result of the same gambling process \u2014 it\u2019s a dice roll that you got lucky on; bullshit that happened to be true.<\/p>\n\n\n\n<h2 id=\"why-calling-llm-output-bullshit-matters\" class=\"wp-block-heading\">Why calling LLM output bullshit matters<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Using glosslighting instead of proper metaphorical extensions for inaccurate outputs reframes a <strong>predictable failure mode of LLMs<\/strong> as a humanlike quirk. To paraphrase a <a href=\"https:\/\/unu.edu\/article\/concern-around-saying-ai-hallucinates\" target=\"_blank\" rel=\"noreferrer noopener\">United Nations University article<\/a>, this doesn\u2019t just mislead people and hinder public understanding of AI; it also \u201c<em>fuels both breathless hype and dystopian fear<\/em>.\u201d<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This can have actively harmful effects at both the business and personal levels (and at the societal level as well, though the effects there are more speculative).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">On a business level, undesirable LLM output can lead to monetary and reputational harm:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Lawyers who <a href=\"https:\/\/www.reuters.com\/legal\/new-york-lawyers-sanctioned-using-fake-chatgpt-cases-legal-brief-2023-06-22\/\" target=\"_blank\" rel=\"noreferrer noopener\">used ChatGPT to write a legal brief<\/a> went to court with invented case law citations and fictitious quotes, leading to embarrassment and sanctions.<\/li>\n\n\n\n<li>Alphabet Inc. <a href=\"https:\/\/www.reuters.com\/technology\/google-ai-chatbot-bard-offers-inaccurate-information-company-ad-2023-02-08\/\" target=\"_blank\" rel=\"noreferrer noopener\">lost an estimated $100 billion<\/a> in market value after their Bard chatbot claimed the James Webb Space Telescope took the first-ever picture of a planet outside the solar system \u2014 something that had been done 20 years prior.<\/li>\n\n\n\n<li>Deloitte had to pay a <a href=\"https:\/\/fortune.com\/2025\/10\/07\/deloitte-ai-australia-government-report-hallucinations-technology-290000-refund\/\" target=\"_blank\" rel=\"noreferrer noopener\">partial refund to the Australian government<\/a> after the $290,000 report they were hired to make was flagged as full of AI hallucinations.&nbsp;<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">On a personal level, <a href=\"https:\/\/www.bbc.com\/news\/articles\/cgerwp7rdlvo\" target=\"_blank\" rel=\"noreferrer noopener\">undesirable LLM output can be deadly<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">So let\u2019s call a spade a spade, which means calling both desirable and undesirable LLM output what it is \u2014 bullshit that sometimes just so happens to be true.<\/p>\n\n\n\n<div class=\"wp-block-group pro-tip\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<p class=\"wp-block-paragraph\"><strong>Further reading<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">AI companies were saying that AI would replace human labor, but it got so expensive that human labor is now cheaper than AI:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/cake.com\/blog\/human-labor-vs-ai-cost\/\" target=\"_blank\" rel=\"noreferrer noopener\">Human Labor Will Be Much Cheaper Than AI Tokens<\/a><\/li>\n<\/ul>\n<\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Learn why \u201challucination\u201d is a misleading metaphor for AI errors and how LLMs make errors so you can minimize business risks.<\/p>\n","protected":false},"author":10,"featured_media":5230,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[12],"tags":[],"class_list":["post-5229","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology-corner"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI Doesn\u2019t Hallucinate \u2014 It Bullshits (In the Psychological Sense)<\/title>\n<meta name=\"description\" content=\"Learn why \u201challucination\u201d is a misleading metaphor for AI errors and how LLMs make errors so you can minimize business risks.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/cake.com\/blog\/ai-doesnt-hallucinate-it-bullshits\/\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/cake.com\\\/blog\\\/ai-doesnt-hallucinate-it-bullshits\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/cake.com\\\/blog\\\/ai-doesnt-hallucinate-it-bullshits\\\/\"},\"author\":{\"name\":\"Vladimir Samolovac\",\"@id\":\"https:\\\/\\\/cake.com\\\/blog\\\/#\\\/schema\\\/person\\\/ea541ccb54551bf82ecf4ed2f740c709\"},\"headline\":\"AI Doesn\u2019t Hallucinate. 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(In the Psychological Sense)\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/cake.com\\\/blog\\\/#website\",\"url\":\"https:\\\/\\\/cake.com\\\/blog\\\/\",\"name\":\"CAKE.com | Blog\",\"description\":\"\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/cake.com\\\/blog\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"},{\"@type\":\"Person\",\"@id\":\"https:\\\/\\\/cake.com\\\/blog\\\/#\\\/schema\\\/person\\\/ea541ccb54551bf82ecf4ed2f740c709\",\"name\":\"Vladimir Samolovac\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/729742ee88df42d7aaed9d28d85521017f2a840de75e68fb6a7d59b77110fbfe?s=96&d=mm&r=g\",\"url\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/729742ee88df42d7aaed9d28d85521017f2a840de75e68fb6a7d59b77110fbfe?s=96&d=mm&r=g\",\"contentUrl\":\"https:\\\/\\\/secure.gravatar.com\\\/avatar\\\/729742ee88df42d7aaed9d28d85521017f2a840de75e68fb6a7d59b77110fbfe?s=96&d=mm&r=g\",\"caption\":\"Vladimir Samolovac\"},\"description\":\"Vladimir is a researcher and writer curious about all topics related to navigating the modern workplace. 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