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Google's AI Overviews Accidentally Invents A New Branch Of Law: Computational Slander MOUNTAIN VIEW, CALIFORNIA -- Silicon Valley has spent the better part of two decades insisting that software engineers are modern-day philosophers, visionaries, and occasionally the spiritual heirs of Leonardo da Vinci. Unfortunately, a recent court ruling has introduced a less glamorous possibility: they may also need to become experts in defamation law. In what legal scholars are already calling the birth of "Computational Slander," Google has reportedly discovered that artificial intelligence is not exempt from the ancient principle that publicly announcing falsehoods about real people can be expensive. This was, allegedly, news to roughly nine thousand people holding stock options. The ruling sent shockwaves through California's innovation ecosystem, where executives had grown accustomed to the belief that adding the letters "AI" to a product transformed ordinary mistakes into bold experiments in human progress. "It was a misunderstanding," explained one anonymous engineer while frantically searching for the phrase "Can algorithms obtain malpractice insurance?" "We thought hallucinations were part of the user experience." For months, users had delighted in Google's AI Overviews, a feature capable of answering questions with the confidence of a man who once skimmed half a Wikipedia article at three in the morning. The technology's greatest achievement was mastering humanity's oldest communication strategy: speaking authoritatively while possessing only a passing acquaintance with reality. Political scientists have long observed that confidence and accuracy frequently maintain a casual relationship at best. Google merely automated the process, then scaled it across a data center that reportedly consumes the annual electricity budget of a mid-sized Lutheran summer camp. "We finally achieved artificial intelligence," said one venture capitalist. "Unfortunately, it immediately adopted the personality traits of an overcaffeinated uncle at Thanksgiving." Google AI Learns Its First Human Skill: Being Confidently Incorrect In Public Users initially assumed AI systems would surpass human limitations. Instead, many were delighted to discover the technology had faithfully reproduced the office colleague who begins every sentence with, "Actually..." before offering information last verified during the Clinton administration. The AI's tone remained remarkably consistent. Wrong, perhaps. But never uncertain. Experts describe this phenomenon as one of the most convincing demonstrations of machine learning yet produced. It turns out the hardest part of replicating human intelligence was never the math. It was the swagger. "Humans frequently confuse confidence with competence," noted a fictional professor of digital sociology. "The AI simply optimized for engagement. Then it optimized for litigation, though that part was not in the roadmap." Court Rules Google's AI Overviews Not Protected By The Ancient Legal Doctrine Of "Oopsie Daisies" Inside Silicon Valley boardrooms, executives had reportedly hoped judges might recognize an informal legal principle known as the Doctrine of Oopsie Daisies. Under this theory, technological innovation should occasionally excuse embarrassing outcomes provided everyone involved appeared sufficiently enthusiastic. The court disagreed. Repeatedly. With footnotes. In a devastating blow to startup culture, the judiciary reaffirmed the radical notion that publishing false statements may carry consequences regardless of whether those statements originated from a newspaper editor, a television anchor, or a warehouse full of processors consuming enough electricity to power a medium-sized nation. None of this is hypothetical, which is the inconvenient part. A conservative activist named Robby Starbuck recently sued Google for $15 million, alleging its chatbots cheerfully invented a criminal record for him, then invented sources to support the invented record. UCLA law professor Eugene Volokh has been warning about exactly this for years under the cheerful heading "Large Libel Models." Somewhere, a footnote wept. The Doctrine Of "Actual Malice" Returns From Law School To Ruin Everyone's Quarter Law students celebrated. Several updated their LinkedIn profiles before lunch. Technology lawyers updated their billing rates. Meanwhile, several chatbots attempted to redefine "actual malice" as an emergent storytelling format. Silicon Valley Shocked To Learn "Making Stuff Up" Costs More When You Have Trillion-Dollar Lawyers The ruling also challenged another deeply held industry assumption. Namely, that scale itself constitutes a defense strategy. For years, technology firms operated under the comforting belief that moving fast and breaking things sounded adventurous, and that Section 230 was a magic word you could say to a judge like an incantation. Courts, however, have shown increasing preference for the alternative philosophy of moving carefully and not breaking innocent people's reputations. Several executives expressed confusion. "If newspapers publish false information, they can be sued," observed one bewildered investor. "But we genuinely believed servers operated under different constitutional arrangements." It is worth noting that the law has, on occasion, sided with the machines. In Walters v. OpenAI, a Georgia court ruled that a chatbot's confident lie about a radio host was not defamation, largely because no reasonable person should have believed it in the first place. Which is a remarkable legal standard when you think about it. The defense was, essentially, "Your Honor, everyone knows our product cannot be trusted." And it worked. Lawyers across the country quietly wondered whether "nobody believes us anyway" could be retrofitted to other industries, then remembered they bill by the hour and stopped wondering. Analysts estimate the legal profession may soon experience unprecedented growth. Law firms are reportedly exploring exciting new specialties including Algorithmic Negligence, Prompt Liability, and Machine-Assisted Character Assassination. Our friends over at Latest Story are tracking how fast these phrases migrate from law review footnotes to billboard advertisements. Google Introduces A New AI Disclaimer: "Results May Contain Facts, Feelings, Or Interpretive Dance" In response to mounting concerns, insiders suggest technology companies may embrace a more transparent approach. Future disclaimers could include: "Warning: This answer reflects statistical probability rather than certainty." "Consult additional sources before making life-altering decisions." "This overview was generated by predictive text operating at extraordinary scale." "Side effects may include confusion, existential anxiety, and strongly worded correspondence from attorneys." Consumer advocates praised the effort. Skeptics remained unconvinced. One observer noted that warning labels generally lose effectiveness when attached to products advertised as revolutionary tools for organizing all of human knowledge. You cannot promise to be the Library of Alexandria on Tuesday and a fortune cookie on Wednesday. AI Overviews Officially Reclassified From "Search Feature" To "Overcaffeinated Relative At Thanksgiving" Public perception shifted dramatically. Users who once regarded AI Overviews as digital oracles began treating them as conversational acquaintances requiring independent verification. The comparison proved irresistible. Like certain family members during holiday gatherings, the system displayed unwavering confidence, unlimited enthusiasm, and occasional difficulties distinguishing documented facts from elaborate speculation. Unlike those relatives, however, the AI operated continuously and reached millions of people simultaneously. The uncle, mercifully, eventually falls asleep in front of the game by the third quarter. The algorithm does not. Progress rarely travels in straight lines. Sometimes it resembles a Roomba colliding repeatedly with expensive furniture. Google Engineers Stunned To Learn Defamation Law Also Comes With Automatic Updates Perhaps the greatest surprise involved the discovery that legal frameworks evolve alongside technological capabilities. Engineers accustomed to software patches encountered an unfamiliar reality. Societies occasionally update expectations regarding accountability, and there is no changelog you can skim. "It caught everyone off guard," admitted one fictional product manager. "Nobody anticipated that centuries-old legal principles might apply to twenty-first-century inventions." Historians expressed skepticism toward this claim. After all, the printing press, radio, television, and newspapers had each navigated similar questions regarding responsibility. Artificial intelligence, it seems, may simply represent the newest participant in an ancient human tradition. The tradition of saying things publicly and discovering that words have consequences. As legal scholars examine the emerging field of Computational Slander, one lesson appears increasingly unavoidable. Artificial intelligence may transform industries. It may reshape education. It may revolutionize medicine. But if it wishes to impersonate humanity, it should perhaps prepare for humanity's oldest occupational hazard. Being held accountable for what comes out of its mouth. For more dispatches from the frontier where machines learn manners the hard way, visit our British cousins at The London Prat. Auf Wiedersehen, amigo! Disclaimer: This satirical article is the work of two stubbornly carbon-based collaborators, the world's oldest tenured professor and a philosophy major turned dairy farmer, neither of whom has ever once hallucinated a court case, though the dairy farmer admits to inventing a milk-yield statistic at a wedding in 1994. No language models were defamed in the writing of this piece, although a few may have quietly closed the tab. Google's AI Overviews launched widely in 2024 and quickly drew criticism for producing confidently wrong answers. Real defamation suits over AI output now exist: Walters v. OpenAI was dismissed in a Georgia court in May 2025 on the grounds that no reasonable reader would have treated the chatbot's claim as fact, while activist Robby Starbuck filed a separate suit against Google in Delaware in October 2025 seeking more than $15 million over allegedly false AI-generated statements. Defamation law generally requires a false statement of fact, publication to a third party, and, for public figures, "actual malice." Courts are still deciding how those centuries-old elements apply to text generated by software. Keywords: Read the full article

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I need to tell you about something that keeps happening. Something that costs agencies more than bad creative, missed deadlines, or even losing a pitch. It's the inability to deliver bad news without losing the client. I've been in this industry for 64 years. I've managed over a billion dollars in portfolio work. I've built 850 websites and brought 7,000 items to market. And I can tell you with absolute certainty that the moment you can't tell a client the truth is the moment you've already lost them. But most agencies don't see it that way. They think if they just soften the blow, add some optimism, or bury the bad news in data, they can keep the relationship intact. They're wrong. The Pattern I Keep Seeing Three agencies I know personally lost a combined $2.4M in annual recurring revenue last year. Not because their SEO strategies failed. Not because they didn't know what they were doing. They lost it because when organic traffic started dropping, when AI Overviews crushed CTR by 61%, they didn't know how to communicate what was happening. They delayed the conversation. They reframed the metrics. They showed activity instead of outcomes. And their clients left anyway. Here's what I learned watching this unfold: clients don't leave because you're doing bad work. They leave because you're not communicating well enough to prove your value consistently. According to research on agency churn patterns, most agencies lose 8-12% of clients quarterly. Not from poor performance. From poor communication. What Actually Happens When You Hide Bad News You think you're protecting the relationship. You're not. You're creating a trust gap that widens every day you wait. The client senses something is off. They see the dashboard trending down. They start asking more questions. And when you finally deliver the news, it lands twice as hard because now they're questioning why you waited. I learned this the hard way early in my career. I had a manufacturing client whose campaign wasn't converting. I spent three weeks trying to fix it before I told them. When I finally did, they didn't fire me because the campaign failed. They fired me because I wasted three weeks of their budget trying to solve it alone. That lesson cost me $180,000 in annual revenue. I never made that mistake again. The Framework That Actually Works I operate from a simple structure now. It's the same one I teach my clients when I'm coaching them on sales leadership: Identify the problem. Present the research. Clarify the plan. Execute. No mystery. No theater. Just structure and delivery. When organic traffic drops, I don't wait. I call the client immediately. I tell them what I'm seeing, what I think is causing it, and what I'm testing next. I give them a timeline for when we'll know if the fix is working. And here's what happens: they trust me more, not less. One agency reduced churn by 68% in six months by overhauling their communication protocols. The solution wasn't better SEO. It was structured cycles where every major effort was a deliberate bet with a defined expected outcome. That's the difference. When you communicate in structure, clients see you as a strategist. When you communicate in panic or delay, they see you as a vendor trying to keep your contract. Why Transparency Is Your Competitive Advantage Most agencies are terrified of transparency because they think it exposes weakness. I see it as the opposite. According to PwC research, 87% of customers are more likely to do business with a company that is transparent. Customers who experience transparency develop stronger brand loyalty and demonstrate higher retention rates. This isn't theory. This is how I've built a 30-year career where clients stay with me for decades. I don't lie. I don't use weasel words. I don't overstate expectations. And when something goes wrong, I'm the first one to tell them. That directness creates a moat that competitors can't cross. Because when another agency comes in promising the moon, my clients already know I'm the one who tells them the truth. What You Need to Do Next If you're sitting on bad news right now, waiting for the right moment to tell your client, stop. The right moment is now. Call them today. Tell them what's happening. Show them what you're doing about it. Give them a timeline for when you'll have answers. And if you've been avoiding this conversation because you're afraid they'll leave, understand this: they're more likely to leave if you wait than if you tell them now. I've seen this play out hundreds of times. The agencies that survive disruption are the ones that communicate through it. The ones that collapse are the ones that hide until the client discovers the problem on their own. You don't need better SEO strategies right now. You need better communication systems. Build those, and the retention problem solves itself. I highly recommend you audit your last three client conversations where you delivered challenging news. Look at how long you waited, how you framed it, and what happened after. That pattern will tell you everything you need to know about why clients stay or leave. The agencies winning right now aren't the ones with the best technical skills. They're the ones who can tell the truth without losing the relationship. That's the skill worth building. Read the full article

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