Even LinkedIn is getting tired of your AI-written posts

Bland, AI-generated posts have made LinkedIn the butt of many an internet joke this year. The platform has heard its users’ complaints about lengthy, generic missives never touched by human hands loud and clear. As AI has made it easier than ever to create huge volumes of content cheaply and easily, that “slop” has flooded the internet. YouTube, Pinterest, Spotify and other platforms have all sought to limit the amount of spammy, AI-generated content their users see. But LinkedIn has been hit especially hard. Scrolling through the professional networking site earlier this year could mean being bombarded by bullet-pointed lists accented by emojis, references to “B2B sales,” and asks for a follow or comment for more. A report published in July by Pangram, a research firm that tracks AI content online, found that more than 40% of long-form posts on the platform were AI-generated, compared to around 30% on X and Medium and a smaller percentage on Reddit and Substack. So now, LinkedIn is upping its fight against slop. “I know you think you’re doing the right thing with your perfectly bulleted list and your hook at the top, and you followed all the advice from LinkedIn advisors across the internet,” LinkedIn Editor-in-Chief Dan Roth, who leads the platform’s content strategy, told CNN in an interview. “But what works is being human.” There is some irony in this, given that LinkedIn is owned by Microsoft. The tech giant has pushed for people to adopt its AI tools for everything from writing to coding, and it is up against steep competition from the likes of OpenAI and Anthropic. LinkedIn previously offered AI tools to edit or rewrite posts, although it recently scaled the offerings back. But low-quality AI posts are a business problem for LinkedIn. They all start to sound the same, Roth said. If users see too many generic AI posts, instead of content that really teaches them something or gives them a deeper understanding of a professional connection, LinkedIn risks losing them to other platforms. Fighting AI slop In August, LinkedIn rolled out a button letting users flag when a post “seems like AI slop,” which was clicked more than 1 million times within its first two weeks. Now, the company is trying to use its own AI systems to help weed out AI slop on the platform and to remind LinkedIn users how to post like humans. The company built a team largely made up of former journalists and social media experts who have an eye for recognizing generic, sloppy content. These experts help train LinkedIn’s AI model on what authentic, useful posts look like. If the model flags a post as low-quality, AI-generated content, it’ll be less likely to be distributed beyond that user’s direct connections. Also key to the strategy is a creator management team that acts as “content therapists” for executives, subject matter experts and other LinkedIn users, many of whom have gotten accustomed to the convenience of using AI to write what, on the surface, appear to be polished posts, Roth said. “A lot of times now today, they’ll run it through Claude or Gemini or wherever, they’ll post it on LinkedIn and it will perform poorly. And then they come to the team and they’re like, ‘Why did this do badly?’” Roth said. “And the best thing you can do is give it back to them and be like, ‘Did you enjoy reading this? Do you see yourself in this?” Instead, the team encourages users to embrace imperfection in their posts — to make videos by leaning a phone up against a coffee mug, rather than shooting in an expensive studio, or to dash off a post to start a conversation, even if it isn’t a complete thought. The efforts are showing early signs of success. Improvements to LinkedIn’s detection systems have resulted in a 40% decline in views of content classified as AI slop, the platform said last month. That’s not to say LinkedIn is entirely opposed to AI, Roth said, adding that “not everyone is a born communicator.” But failing to edit or personalize content means it’s less likely to reach a wide audience on the platform. “We just try to push people to be more human,” he said. “That is what is required to be able to cut through the noise.” By Clare Duffy

AI Has a New Name: Super Intelligence. Why You Should Start Using SI Right Now

An executive order directing federal agencies to use “Super Intelligence” and “SI” in place of “Artificial Intelligence” and “AI” has big implications. A new Super Intelligence Force was also announced last week to coordinate the federal response. This all makes SI more than a slogan. As I’ve written about before, language is a critical leadership lever that can shift mindsets and mobilize action. With SI now the official language of the U.S. executive branch, business leaders need to understand what changed and why, including the implications for leadership, innovation, and organizational transformation. The Definition of Super Intelligence SI is currently defined using the same basic definition as AI, while allowing 60 days for the Assistant to the President for Science and Technology to propose a formal federal definition. The concept of SI has been around for a while. In 1998, Nick Bostrom from Oxford University introduced the idea that superintelligence is intelligence that is much smarter than the best human minds in every field. Depending on your perspective, we might already have achieved this. For business leaders, SI works best as a strategic term. AI has become a catchall for chatbots, automation, and applications. SI raises the conversation to the level CEOs and boards should address: how a dramatic increase in intelligence could—and should—reshape the way a company makes decisions, operates, and competes. The SI Summit that created a word that will stick The White House summit assembled leaders from chipmakers, data centers, cloud platforms, and frontier model companies. David Sacks, chair of the President’s Council of Advisors on Science and Technology, called it the first gathering of the critical players across the industry’s full stack. Many were competitors. Some had deep disagreements. They still produced an agreement. Six companies signed the White House Accord on Super Intelligence. It calls for internal controls, an internal team to verify them, outside audits, and an independent board committee. Specifically: Implement robust internal controls to monitor the capabilities and alignment of its models during training and deployment around areas like cybersecurity, biosecurity, and chemical threats, and to ensure that its models do not hack or access technical systems in unintended ways. Empower an internal team to ensure all of the controls, monitoring, and detection are operating as intended, and that any issues are remediated. Partner with an independent external auditor or evaluator to carry out independent assessments of whether the controls, monitoring, and detection are operating as intended. Designate an independent committee of the board of directors to oversee and receive reports from the teams operating the controls and the internal and external auditors and evaluators, as well as to ensure any issues identified are remediated. The summit’s most useful lesson came from who was included. Anthropic CEO Dario Amodei attended despite sharp disagreements with many others in the room. All the key players who needed to sign up for voluntary controls on the future of AI (now SI) were present. That’s been a fundamental principle of change management. Engagement is key for buy-in and ultimately implementation. The new federal task force extends that pattern. Its leaders come from intelligence, the Federal Trade Commission, the Pentagon, and the Office of Personnel Management. It also plans outreach to consumers, public interest groups, religious organizations, infrastructure providers, and technology companies. Build Your Own Super Intelligence War Room Most businesses will never train a frontier model. But every business, small and large, will face choices about where these systems are used in strategy, innovation, operations, and more. And also what data they give access to the SI to use, and who carries the risk when things fail. The idea of “superintelligence” can be a forcing function to elevate AI from chatbot discussions to truly taking a look at the implications for business strategy. For example, a small company can bring together the owner, the salesperson closest to customers, the operations lead, and outside technology or legal advisers. A large company needs the leaders responsible for technology, business strategy, workforce decisions, customer experience, security, legal risk, and operations. Include at least one informed skeptic as well. Start with one important use case tied to the business strategy of the company. For example: how you develop new products, identify emerging competitors, monetize your business model, or anything else that’s mission-critical. Describe how a new “super intelligent system” could provide you with a step change in innovation and value, whether saving money or generating new revenue streams. Also explore what a system like this would ideally do on its own and where a person must review its work to help minimize risks. This is basically a strategic brainstorm, but anchored in real value creation and a recognition that SI might be here to stay – and play a critical role in business strategy. Names Matter Names matter. Use specific technical terms like chatbot, data center, open-weight model, or application to “declutter” the concept of artificial intelligence (e.g., making it more descriptive while simplifying what it means). Use “Super Intelligence” in strategy conversations to signal that the company is making choices about a new source of capability with consequences across the business. The first test of any SI strategy is simple: what will you do or create with real super intelligence? EXPERT OPINION BY SOREN KAPLAN, WSJ BESTSELLING AUTHOR, KEYNOTE SPEAKER, AND LEADERSHIP STRATEGY ADVISOR

They Won a Prestigious Writing Prize. Then These Key Giveaways Sparked Allegations of AI

A London-based literary competition is facing major scrutiny after three of five winners have been accused of using AI—partly or wholly—to write their prize-winning stories. The 2026 Commonwealth Short Story Prize selected one winner each from five regions that span Africa, Asia, Canada and Europe, the Caribbean, and the Pacific. Following publication of the winning entries in literary magazine Granta, online sleuths called foul. The Caribbean regional winner, Jamir Nazir, was praised for the “lyrical precision and haunting atmosphere” of his short story “The Serpent in the Grove,” as well as “the confidence and restraint of its voice,” according to a post on social media platform X by Commonwealth Foundation Creatives. But internet denizens allege that the very same voice that won the prize may not be human at all. Nabeel S. Qureshi, an AI marketing entrepreneur and a former visiting scholar at the Mercatus Center at George Mason University, flagged certain signs he said were AI tells such as “‘Not X, not Y, but Z’ sentences,” as well as the use of the word “‘hum,'” in a post on X. He concluded by writing: “A major milestone for AI, at any rate …” Following the allegations, Wired ran the text of “The Serpent in the Grove” through AI detection tool Pangram, which the publication notes has consistently outperformed other similar tools. It determined that the text was 100 percent AI-generated. It’s worth noting that no AI-detection tools are totally accurate. “The Serpent in the Grove” isn’t the only story under scrutiny. Pangram determined that “The Bastion’s Shadow” by John Edward DeMicoli, the winner from Malta, was also fully AI-generated and that “Mehendi Nights” by Sharon Aruparayil, the winner from India, was partially written using AI. Holly Ann Miller’s “Second Skin,” and Lisa-Anne Julien’s “Me and Ma’am,” however, were ruled “fully human-written” by Pangram, according to Wired. The regional winners were chosen from 7,806 entries, which the Commonwealth Foundation noted on its site is the “second highest number in the Prize’s history.” A final winner from among the five will be announced on June 30. Following the allegations, the Commonwealth Foundation released a statement on its website, acknowledging the challenges generative AI poses to literary and creative work. The statement also noted that the foundation’s judging process is robust, but judges do not currently use AI checkers in any stage. “We are aware of allegations and discussion regarding generative AI and our Short Story Prize. We take these claims seriously and are committed to responding to them with care and transparency,” the statement reads. “When they submit stories to the Prize, writers accept our entry rules and guidelines. These include confirming that their submission is their own original work. All shortlisted writers have personally stated that no AI was used and, upon further consultation, the Foundation has confirmed this.” The foundation also noted that until a reliable tool emerges with which the organization can screen unpublished work for AI, the prize competition “must operate on the principle of trust.” As always, Redditers had much to say about the subject, some assuming AI guilt, others questioning the accuracy of the AI checking tools, and many picking at the quality of the stories more broadly. “This…doesn’t surprise me given the state of contemporary literary prose. It honestly just reads like bog-standard ‘MFA voice,’” one Redditor wrote of Nazir’s story. A recent report from digital marketing agency Graphite found that since the debut of ChatGPT in 2022, there has been a meteoric rise of AI-generated content on the internet. The number of articles written by AI now equals that of human-written content, although the overall share seems to have plateaued. Axios reported at the time that the quality of AI-generated writing has meaningfully improved, not to mention that it can be difficult to determine what constitutes AI writing. Whereas some content is mostly or entirely AI-generated, some writers use AI tools throughout the process of drafting and editing. BY CHLOE AIELLO @CHLOBO_ILO

Anthropic Just Banned Being Cruel to Claude. The Reason Should Concern Us All

There are lots of reasons to have feelings about artificial intelligence. It seems like everyone thinks AI will replace human workers. There are real questions about the ethics and legality of scooping up basically the entire internet to train models. There are even questions about how they work and whether they could someday become dangerous. If you understand nothing else about AI chatbots, understand this: They do not have feelings. They are not people, and they don’t experience pain or frustration. They’re token-generation machines. You give them a prompt, they break it down into tokens, and then they generate new tokens one at a time using a predictive model trained on enormous amounts of human writing. At its basic level, it’s 1s and 0s running through transistors in a GPU in some data center in Boise, Idaho, or wherever. Sometimes those 1s and 0s come back out as tokens that sound a lot like feeling words. But, and this is important, using words to describe feelings isn’t the same thing as having feelings. Claude produces those words only because it was trained to produce a response the way humans would respond in a similar situation with similar language input. That doesn’t make it human or capable of human experiences. Which is why it’s worth noting that Anthropic issued an update to its usage policy that bans being cruel to its model. You cannot be cruel to something incapable of experiencing pain or suffering, and an LLM is capable of neither. Look, thinking that it’s absurd that Anthropic is making this a policy isn’t the same as condoning bad behavior. I don’t condone cruelty in any situation. No one should. But my reason is just that it’s bad to practice cruelty, not because you might hurt a chatbot’s feelings. In its updated usage policy, which takes effect November 12, Anthropic says it now prohibits “sustained and needless abusive or cruel behavior toward our models.” The company says the new policy applies only to what it calls extreme cases of repeated abuse, not ordinary frustration, criticism, or legitimate research. Apparently, you’ll still be able to tell Claude that it’s doing a bad job; you just can’t do it repeatedly and for no reason. On the one hand, that might seem like a relatively harmless policy. We can even all agree that antisocial or cruel behavior shouldn’t be encouraged. But I also think that you can believe more than one thing at a time. For example, you can believe it’s not useful for you or the experience of using the model to be overly aggressive, taunting, or insulting toward a piece of computer software. Likewise, if you find yourself drawn toward trying to repeatedly engage an AI chatbot in disturbing conversations, you might want to do some self-reflection and seek help. But I don’t think that is inconsistent with also believing that Anthropic’s policy raises a much bigger question about how AI companies want us to think about their products. Specifically, why would a company that builds software believe it needs to protect that software from cruelty? Anthropic’s stance on Claude’s feelings This isn’t the first time the company has said that its AI models might need some measure of moral consideration. Last year, the company announced that Claude could end conversations with users who are repeatedly abusive. At the time, Anthropic explained that the decision was motivated primarily by research into what it calls “model welfare.” Anthropic has contributed to this problem with its stance on whether its models are conscious or capable of subjective experiences. It has repeatedly suggested the possibility that they might be, and now it’s using that as a reason to establish rules about how people interact with its software. There is a meaningful debate about consciousness and why physical and chemical interactions result in a sense of self-being and subjective experience. It’s a big enough challenge that it’s even called the hard problem of consciousness. But it’s a leap to go from the idea that scientists and philosophers don’t fully understand consciousness to suggesting that a chatbot might be capable of experiencing cruelty. To be fair, there’s nothing wrong with Anthropic deciding that it doesn’t want people using Claude to practice abusive behavior. There are reasonable arguments for discouraging that sort of thing, especially if it might reinforce harmful behavior toward actual people. But that’s not the same thing as saying people shouldn’t be cruel to Claude. The people problem The bigger problem is that Anthropic is suggesting something that should concern us all: It’s conditioning us to think of chatbots as though they were people. We already know that users can develop emotional attachments to AI companions. AI chatbots are designed to communicate naturally, similar to the way a human would. For people who are lonely or emotionally vulnerable, the distinction between a simulated relationship and actual human connection can become increasingly difficult to discern. That’s why the language these AI companies use is especially important. When a chatbot tells someone it cares about them, the company behind it should be making clear that those words are just tokens generated by software, not evidence of some kind of personal connection or affection. But Anthropic is, instead, suggesting the possibility that the relationship might work both ways. If Claude can be treated cruelly, wouldn’t that suggest it can also experience kindness? If it can suffer, couldn’t it also care about the person it’s talking to? To be fair, Anthropic doesn’t explicitly make those claims. But suggesting that its models need to be protected from pain and suffering introduces a dynamic that points to only one thing—it sure seems like it wants you to think of it as a person. I would argue that’s exactly the sort of confusion AI companies should be working to prevent. Right now, AI companies are pushing their technology at a relentless pace. The result of that is that it is becoming far more useful. At the same time, it is becoming incredibly complex, and it’s getting harder to understand how it works. Those companies should be trying to help users understand the difference between language that sounds like human feelings and emotion, and actual human experience. Obviously, Anthropic has every right to set rules for how customers use its products. But that doesn’t mean we shouldn’t ask questions about those rules, especially when they reinforce potentially misleading ideas about what artificial intelligence is. In fact, the most concerning thing about Anthropic’s new policy isn’t whether Claude might someday develop feelings. It’s that one of the companies building the world’s most powerful AI systems is already asking us to behave as though it has. EXPERT OPINION BY JASON ATEN, TECH COLUMNIST @JASONATEN