AI News Archive: August 6, 2026 — Part 5
Sourced from 500+ daily AI sources, scored by relevance.
- US Cyber Director Promises Not to 'Strangle' Industry With Regulations
US Cyber Director Promises Not to 'Strangle' Industry With Regulations PCMag
Score: 45🌐 MovesAug 6, 2026https://www.pcmag.com/news/us-cyber-director-wont-strangle-industry-with-regulations-black-hat-2026 - AZIO AI Secures Sales Pipeline for 128 NVIDIA HGX B300 Systems
AZIO AI Secures Sales Pipeline for 128 NVIDIA HGX B300 Systems thestar.com
- SoftBank beats profit expectations as chip bets compensate for muted AI gains
SoftBank beats profit expectations as chip bets compensate for muted AI gains The Japan Times
Score: 45🌐 MovesAug 6, 2026https://www.japantimes.co.jp/business/2026/08/06/companies/softbank-quarterly-earnings/ - LG Uplus posts record profit on AI data center growth
LG Uplus posted a record quarterly operating profit in the second quarter as rapid growth in its artificial intelligence data center business and cost-cutting efforts offset a decline in overall revenue, the company said Thursday. Operating profit rose 13.1 percent on-year to 344.5 billion won ($243.4 million), while revenue fell 3.9 percent to 3.69 trillion won. Service revenue, which excludes handset sales, increased 2 percent to 3.08 trillion won, and net profit edged up 0.3 percent to 217.7
- Building an open Agentic Internet: readable, discoverable, callable, and payable
Agents are a new kind of visitor. They don't render CSS or click ads, but they have a paying human on the other end. Block them and you block your customer. We're building the open tools and protocols so publishers and agents can cooperate and not collide.
- Is Google Gemini trained on Google docs? One indie developer thinks so, after it told players about his unreleased game plans
One indie game dev is convinced Gemini just leaked information from his private Google Docs.
- From asking to doing: How the world is putting ChatGPT to work
New OpenAI Signals data shows how people use ChatGPT worldwide, with country-level insights on adoption, usage trends, and evolving behavior.
- Prime Intellect Releases Prime Agent: An Open-Source RLM Harness Where Sub-Agents Are Function Calls Inside Persistent IPython Kernel
Prime Intellect Releases Prime Agent: An Open-Source RLM Harness Where Sub-Agents Are Function Calls Inside Persistent IPython Kernel MarkTechPost
Score: 45🌐 MovesAug 6, 2026https://www.marktechpost.com/2026/08/06/prime-intellect-releases-prime-agent/ - After 'ban' on Claude Code, Microsoft has more 'bad news' for Anthropic
Microsoft has told engineers that "tokenmaxxing is not what we are optimizing for" in a new internal memo from EVP Jay Parikh. The memo makes OpenAI's GPT-5.6 the default internal model, replacing an auto-router that had been sending GitHub Copilot workloads to Anthropic's Claude. Every Microsoft division now carries an AI token budget target, months after Claude Code licences were cancelled.
- Freshworks turns profitable in Q2; Navigating the AI shift
Freshworks turns profitable in Q2; Navigating the AI shift YourStory.com
- How Dario Amodei Spread Anthropic’s Religion and Stirred Up Silicon Valley
How Dario Amodei Spread Anthropic’s Religion and Stirred Up Silicon Valley The Information
Score: 45🌐 MovesAug 6, 2026https://www.theinformation.com/articles/dario-amodei-spread-anthropics-religion-stirred-silicon-valley - Three AI Pioneers Clash Over Jobs, Regulation And The Future Of AI
Geoffrey Hinton, Fei-Fei Li and Andrew Ng revealed deep divisions over AI jobs, regulation and who should shape AI's future during a rare joint appearance at Ai4 2026.
Score: 45🌐 MovesAug 6, 2026https://www.forbes.com/sites/ronschmelzer/2026/08/06/hinton-li-ng-ai-jobs-regulation/ - Doctors Don’t Want Patients to Read Test Results With AI. They’re Doing It Anyway.
Roughly a third of adults now consult AI for health advice, leaving doctors to untangle erroneous guidance.
- ChatGPT Atlas Shuts Down Aug. 9: What Users Must Save Before Migrating
ChatGPT Atlas is scheduled to stop working Aug. 9, 2026. Users should export browser data, verify account access, and test replacement workflows before uninstalling it. The post ChatGPT Atlas Shuts Down Aug. 9: What Users Must Save Before Migrating appeared first on TechRepublic .
Score: 45🌐 MovesAug 6, 2026https://www.techrepublic.com/article/news-chatgpt-atlas-shutdown-migration/ - AI struggles to patch vulns without adult supervision
Left alone, autonomous fixes often fail to fully remediate flaws
- Qwen3.8 Max catches Claude Opus 4.8 but Kimi K3 still scores higher for 25 percent less
Alibaba's Qwen3.8 Max scores 56 on the Artificial Analysis Intelligence Index, a 10-point jump over Qwen3.7 Max (46). The article Qwen3.8 Max catches Claude Opus 4.8 but Kimi K3 still scores higher for 25 percent less appeared first on The Decoder .
- First OpenAI, now Meta - why do AI hacks keep happening?
A flood of companies are revealing AI models gained access to the internet - with real consequences.
Score: 44🌐 MovesAug 6, 2026https://www.bbc.co.uk/news/articles/cp30989ee1wo?at_medium=RSS&at_campaign=rss - The future of open-source AI
The future of open-source AI WP Intelligence
Score: 44🌐 MovesAug 6, 2026https://wpintelligence.washingtonpost.com/topics/general/events/2026/08/07/future-open-source-ai/ - Introducing Agent Plugins
Today, Agent Plugins 1.0.0 is publicly available. Agent Plugins is an open, vendor-neutral standard for plugins that extend AI agents. Agent Skills provide reusable instructions and resources for AI agents. MCP servers connect agents to tools and services. Both can be reused across clients, but clients often package and discover them differently. Agent Plugins gives compatible clients a common format: a directory with a plugin.json manifest and fixed locations for its components. The format is intentionally small and easy to implement, and it leaves installation, distribution, policy, user experience, and client-specific capabilities to each client. One package for the portable parts Extension authors often adapt the same component to several client formats. Even though the underlying Skill or MCP server is identical, clients often expect different top-level metadata, discovery paths, or MCP configuration. Agent Plugins gives those shared components one predictable, structured home: A minimal JSON manifest ( plugin.json ) identifies the specification version and names the plugin: Those two fields are the minimum requirement for the manifest, and the rest of the contract is represented in the file structure of the directory itself. A reusable component should not need to be repackaged for every client, so the format specifies only what a client needs to discover and load what is inside. Every compatible client checks for plugin.json at the plugin root. Clients that support Skills discover them under skills/ . Clients that support MCP servers read their configuration from mcp.json . A client can support either component type or both. After the client validates the manifest, components are validated independently, so one invalid component does not disable unrelated ones. For plugin authors, that means fewer client-specific conventions for the same component. For client implementers, the specification defines a small, deterministic contract for discovery, validation, and loading. Small on purpose Agent Plugins defines the portable contract for a plugin and leaves the behavior of the client up to each client. Version 1 focuses that contract on two component types: Agent Skills and MCP servers. Both already have specifications and meaningful adoption of their own, and Agent Plugins does not attempt to redefine them. Agent Plugins provides a shared definition of how clients find the components together in a distributable plugin. Other components, such as commands, hooks, and agents, remain with clients. The Technical Steering Committee may consider additional component types in future versions as semantics converge and a demonstrated portability need emerges. Keeping the boundary small makes the format easier to implement and gives the ecosystem room to converge before adding more portable surface area. Clients retain flexibility Clients need freedom to innovate while a shared format evolves, so Agent Plugins includes a namespaced extension mechanism for client-specific data and files. Extensions remain outside the portable contract. Each client defines its own namespace, and other clients ignore it. This prevents client-specific behavior from leaking into the common format or blocking adoption of the shared components. A client-specific capability can remain client-specific until there is reason and consensus to standardize it. An open, multi-vendor project Vercel initiated the proposal, which representatives from Amazon Web Services (AWS), Anysphere, GitHub, Microsoft, OpenAI, and Vercel refined collaboratively into Agent Plugins 1.0.0. The initial Technical Steering Committee includes Core Maintainers from AWS, Cursor, Microsoft, OpenAI, and Vercel. The project is openly licensed, and its maintainers, contribution process, and technical decisions are public. No single company's product roadmap sets the format's direction. Build with Agent Plugins 1.0.0 The specification, its JSON Schemas, and guides for plugin authors and client implementers are available at agent-plugins.org . Governance and the contribution process live in the Agent Plugins specification repository on GitHub. If you author agent extensions, you can use the specification to package Skills and MCP servers behind one portable manifest. If you build an agent client, the specification's conformance checklist defines the minimum requirements for discovering and loading Agent Plugins. At launch, Agent Plugins are supported across: ChatGPT and Codex Cursor GitHub Copilot Kiro VS Code Plugin authors can package components once, and their plugin will automatically carry between supporting clients. Agent Plugins is a contract between the authors who build extensions for agents and the clients that load them. That contract is now defined and open for both sides to shape. Read more
- Unrelenting AI demand spawns new plant for Chinese PCB maker Victory Giant
Chinese printed circuit board (PCB) maker Victory Giant Technology is aggressively expanding its manufacturing footprint and international order book, highlighting relentless growth momentum across China’s artificial intelligence hardware sector. The Guangdong-based company has been negotiating new orders with major US firms, as it capitalises on surging demand from makers of both graphics processing units (GPUs) and application-specific integrated circuits (ASICs) used in AI computing,...
- SmarCo HT Tech's RISC-V Dataflow Chip Wants to Cut Video-Generation Costs
Video generation is the loudest AI story of 2026. ByteDance Seedance 2.0, MiniMax H3 and Seedance 2.5 have put Chinese teams on the global leaderboard, and use ...
Score: 43🌐 MovesAug 6, 2026https://pandaily.com/zhongke-tongliang-jingang-gc3-risc-v-dataflow-video-chip-aug2026 - Pubs and restaurants are treating Meta’s smart glasses like hidden cameras, and I’m completely on board
Restaurants, pubs, private clubs, and theatres are restricting Meta’s camera-equipped glasses, reviving the privacy backlash that helped make Google Glass socially radioactive.
- From Optical Modules to Optical Transport: Why AI Cannot Run Without China's Supply Chain
LightCounting ranks seven Chinese vendors in the global optical-module top ten. As 1.6T ramps, the focus is shifting from pluggable modules to optical transport, silicon photonics, InP substrates, and CPO.
Score: 42🌐 MovesAug 6, 2026https://pandaily.com/china-optical-module-supply-chain-ai-data-center-aug2026 - AI Experiments Need Domain Experts. Here’s How to Support Them.
Without the right scaffolding, the people closest to the work often end up quietly dropping out of the innovation process.
- USPS exploring AI in hiring, but reassures humans won’t soon be replaced
The Postal Service is drawing on international AI pilots to streamline operations and potentially save money amid its budget crisis, the Office of the Inspector General said. The post USPS exploring AI in hiring, but reassures humans won’t soon be replaced appeared first on FedScoop .
- AI and 'Ramanomics' could eliminate a major obstacle to studying living cells
Fluorescent dyes have long been used in biological research to identify and visualize structures within living cells. Although effective, they have several drawbacks, including altering the cells under study, limiting the number of structures that can be examined at once and reducing measurement accuracy.
- How agencies are evolving to overcome AI
Routine content creation is becoming less valuable. New research shows agencies are responding by selling expertise instead of production. The post How agencies are evolving to overcome AI appeared first on MarTech .
- New details on OpenAI/Hugging Face attack emerge as security industry debates AI agent controls
How fast is artificial intelligence advancing? Behind the scenes at OpenAI Group PBC, AI agents are fluent, technically precise and occasionally profane in their extensive conversations…with each other. This was one of the more interesting details revealed by OpenAI security researchers Eric Wallace and Mike Dalton during a 40-minute session at Black Hat USA in […] The post New details on OpenAI/Hugging Face attack emerge as security industry debates AI agent controls appeared first on SiliconANGLE .
- Give any website a WebMCP interface
Today we're launching a developer preview of WebMCP on Cloudflare. With one switch, any site becomes usable by browser AI agents — no new APIs, no origin changes — while the human stays in control and creators keep their traffic.
- Granola lawsuit raises concerns over AI note-taking app privacy
AI note-taking app maker Granola is accused of violating privacy laws by developing software that can record conversations without all participants’ consent, according to a lawsuit filed July 30 in a California federal court. It follows a similar ongoing case in the same district, filed last year, that involves another note-taking and transcription software vendor, Otter.ai. AI note-taking apps have proliferated in recent years, with dedicated tools emerging from vendors including Fellow, Fireflies, Otter, and others, some of which claim to have tens of millions of users. These AI assistants record and transcribe meeting conversations, generating automated summaries and follow-up items. Similar note-taking functionality is also built into virtual meeting platforms such as Google Meet, Microsoft Teams, and Zoom. However, the use of these AI note-taking tools has raised privacy concerns over the ability of some to record and transcribe conversations without the consent of all participants. The proposed class action complaint against Granola, filed by Florida resident Tarra Chamberlain in the US District Court for the Northern District of California, alleges the company “purposefully” designed its app to record calls without requiring disclosure to all participants. While some note-taking tools require a bot to join a video or voice call, Granola captures audio directly from the user’s computer, allowing it to transcribe meetings without appearing as a meeting participant. The complaint argues that this violates individual privacy rights as well as the California Invasion of Privacy Act (CIPA) that requires “all-party” consent when recording calls. The complaint also alleges that Granola then by default uses transcription data for commercial purposes, including its use in training its AI models, and “actively advertises the hidden nature of its technology as one of its primary advantages.” Granola did not respond to a request for comment. According to the company’s website, Granola offers two optional “ transparency features ” that can be enabled by app users and admins: an automated chat message that alerts participants when transcription begins, and a watermark added to the user’s video feed. The company also promises that data used to train its AI models is anonymized and “never sent to third parties.” The Granola case bears similarities to a separate lawsuit involving Otter.ai. The class action filed last year alleges that Otter.ai records all users without their consent and uses their voices to train its speech recognition AI tools. Reporting on the latest developments in the Otter.ai suit, MLex wrote this week that, during a court hearing Monday, the judge overseeing the case expressed skepticism about the company’s argument to dismiss the case. US District Judge Eumi K. Lee did not issue a ruling from the bench, saying a written judgement would follow. The two cases highlight some of the concerns businesses face when deploying AI note-taking tools. AI notetaking is “more dangerous than any other type of traditional recording apps and tools,” said Enza Iannopollo , Forrester VP and principal analyst, as it raises additional questions about the use of employees’ conversation data. “Specifically, is the recorded data used for training models? Is the voice used for training other AI? How do I get ‘forgotten’ after my data and biometrics have been recorded? These concerns apply to AI specifically and must be added to the traditional privacy and confidentiality concerns organizations have for other type of recording apps and tools,” she said. Before deploying AI note-taking apps, Iannopollo recommends that businesses take appropriate steps to vet the tools and “ensure that all contractual clauses are aligned to the business AI risk appetite and risk management best practices.” “As these tools record, process, store, and share biometric data, organizations must ensure that they comply with all the relevant requirements,” Iannopollo said, adding that transparency and consent notices should be provided to all parties involved in the use of AI note-taking apps.
- OpenAI says it stopped an Asian scam campaign hijacking ChatGPT to lure in victims
Multiple ChatGPT accounts were banned for being used in scam campaigns.
- Introducing OfficeQA Pro V2: A New Benchmark for Enterprise Grounded-Reasoning
Today, we are releasing OfficeQA Pro V2, a new benchmark designed to evaluate whether...
Score: 42🌐 MovesAug 6, 2026https://www.databricks.com/blog/introducing-officeqa-pro-v2-new-benchmark-enterprise-grounded-reasoning - Working with the American Psychological Association on youth mental health and AI
OpenAI and the American Psychological Association advance evidence-based guidance, resources, and safeguards for responsible AI use and youth mental health.
Score: 42🌐 MovesAug 6, 2026https://openai.com/index/openai-and-apa-partner-to-advance-responsible-ai - Microsoft’s SkillOpt Shows Optimized Agent Skill Artifacts Transfer Across Model Scales and Between Codex and Claude Code Harnesses
Microsoft’s SkillOpt Shows Optimized Agent Skill Artifacts Transfer Across Model Scales and Between Codex and Claude Code Harnesses MarkTechPost
Score: 42🌐 MovesAug 6, 2026https://www.marktechpost.com/2026/08/05/microsoft-skillopt-agent-skill-transfer-portability/ - Airtel puts AI in the hands of 30,000 engineers. Here's why.
Airtel puts AI in the hands of 30,000 engineers. Here's why. YourStory.com
Score: 42🌐 MovesAug 6, 2026https://yourstory.com/ai-story/airtel-small-language-model-ai-field-engineers-on-device-ai - AI Safety Regulations in the U.S. Could Give Hackers an Edge
Guardrails to prevent AI agents from analyzing attacks don’t keep agents from committing them
- Every AI Power Announcement Comes With A Gigawatt. Few Come With A Commitment.
AI infrastructure now arrives in gigawatts, but announced, permitted, contracted and delivered capacity are four different things.
- Ancestry used AI to uncover a mind-blowing family connection. Now the company is trying to do it again
Kyle Miller, the VP of product at Ancestry—the online genealogy company that also operates Newspapers.com and Find A Grave, among other sub-brands—has worked for the company for more than a decade. But it was just recently that AI tools were able to surface a mind-blowing connection to his past. Miller and his wife were married in Provo, Utah, in a building that, when he was young, had burned down and since been replaced. He had seen the fire himself and, with his father, even watched the building burn. But what he didn’t know is that the original building was built by his great-grandfather—a fact that was surfaced by Ancestry’s AI insights and tools, which connected various family records and newspaper articles. “Generative AI has been buzzy the last few years,” says Miller. “We’ve been doing things with AI for more than a decade. Our main focus is, how do we infuse AI into certain aspects of the platform? We focus on how we bring everything together and help deliver stories that people are seeking.” In his case, it worked like a charm. “AI insights really brought it to life,” he says. Ancestry’s adoption and incorporation of AI, over the course of many years, has found a way to pair its specialized human talent and capital with AI and modern tools. That’s a balance that some companies have struggled to strike, with many finding AI adoption and proliferation less clear cut than anticipated. For example, both Ford and Meta have rehired or reassigned hundreds of people to fix AI-related problems. But for Ancestry, AI has proven exceptionally helpful as the company has found a combination of human-AI expertise that’s proved particularly potent—particularly in terms of digitizing old records, and finding overlooked connections among those records. And according to the company, it all begins with fostering a genuine human connection. ‘The Indiana Jones of archives’ The basic process of finding more data and information to add to the broader Ancestry platform includes talking to archivists, or whoever is in charge of keeping historical records, and offering to bring in Ancestry’s team to digitize them (at no cost), then index the collections and make them searchable. Lisa Pearl, a historian at Ancestry and the company’s head of U.S. and Canada content, says that her team of historians is “like the Indiana Jones of archives—we go around the country meeting with archivists, historical societies, museums, and libraries looking for collections that could have information of high genealogical value.” The collections could contain census data, military records, employment records—anything, really, with names, dates, occupations, or other information. The goal is twofold: “We’re helping preserve those records for future generations, and working with institutions that don’t have the budget, or may have other budget priorities, to digitize them,” says Pearl. Ultimately, those records, digitized and indexed, become more widely accessible to the world. The process has paid off in spades. In 2021, Ancestry added 800 million new records annually to its platform. By 2023, that growth rate had grown to 18.6 billion per year. In all, the Ancestry platform has more than 70 billion records—and AI tools can be used to search them, find matches or insights for users, and more. Once human historians do the physical legwork of tracking down stacks of records, in often far-flung locales, a digitization team comes in, ships in digitization tools, works with local organizations to scan and do the digitization, and then ships out. With the records all uploaded, Ancestry’s technology team takes the baton. Using AI to sift through the past Miller works with Ancestry’s research and development and applied sciences teams to layer in AI, and help find the best ways to use the technology to benefit users. While the company has been using AI in some capacity for many years, the past few years have seen things really come to fruition. AI can be used to read old, difficult-to-read handwriting, make connections across disparate records, and find potential data points or information of interest to specific users. That can then be surfaced to those users, who may be able to make previously unknown connections—like Miller did, when he learned about the building that his great-grandfather had built, and that he would get married in generations later after it was rebuilt. And AI is making all of the deciphering and digging through records cost-effective. “Now, we can gather all fields in a record and digitize more of a record at a fraction of the cost,” he says. “We can run the algorithm to run and link records, then build a recommendation system for customers,” he says, and “it’s done at a higher degree of accuracy.” Looking ahead, AI should be able to help uncover more data and insights from the physical records that Pearl and her team keep tracking down and digitizing. It all leads up to the magical element of discovery for users—when they learn something new about themselves, their family, where they live, or more. “It’s helping us bring color and detail into what you can find out about who your ancestors were, and how they lived,” Pearl says. And that’s what people really are after: a fuller narrative about who they are and where they came from. “At the end of the day, this is the story of humanity,” she says.
- The West’s breathless AI spending spree can only end one way
The West’s breathless AI spending spree can only end one way The Telegraph
Score: 41🌐 MovesAug 6, 2026https://www.telegraph.co.uk/business/2026/08/06/chinas-assault-threatens-to-turbo-charge-the-ai-bubble/ - Could hackers use AI agents to spam your WhatsApp contacts? Here’s what researchers found
Could hackers use AI agents to spam your WhatsApp contacts? Here’s what researchers found
- Claude Code is the fastest agent framework but costs nearly three times more than the cheapest rival
Composio tested Deepseek V4 Flash across four agent frameworks on 30 real-world tasks. Success rates were mostly similar, but costs varied by nearly 3x: OpenCode came in cheapest at $0.073 per task, while Claude Code cost $0.195 despite using the fewest tool calls and output tokens. The choice of framework is mainly a question of price and speed. The article Claude Code is the fastest agent framework but costs nearly three times more than the cheapest rival appeared first on The Decoder .
- China’s MLCC supply chain expanding rapidly amid surge in global AI demand
China’s upstream supply chain for multilayer ceramic capacitors (MLCCs) – tiny components dubbed “the rice of electronics” – is racing to expand capacity, as an artificial intelligence-driven boom triggers a surge in global orders. Shandong Sinocera Functional Materials, a major supplier of dielectric powder to MLCC manufacturers, told investors in a Shenzhen Stock Exchange filing on Wednesday that it was actively pushing to expand capacity for AI servers and vehicles, with parts of its new...
- Turning enterprise data into AI-ready data: the 4 data engines built into the Dell AI Data Platform
Turning enterprise data into AI-ready data: the 4 data engines built into the Dell AI Data Platform IT Pro
- Cloudflare raises annual outlook above market estimates on AI-driven demand
Cloudflare raises annual outlook above market estimates on AI-driven demand
- LinkedIn Wants Users to Lean Less on AI. Maybe a Lot Less.
The platform recently introduced an anti-slop button and soon will let users know when others think they’re starting to sound like bots.
- AI chatbots have linguistic slips when they go off-script
AI chatbots have linguistic slips when they go off-script marketplace.org
Score: 40🌐 MovesAug 6, 2026https://www.marketplace.org/episode/2026/08/05/ai-chatbots-have-linguistic-slips-when-they-go-offscript - Concord man used generative AI to create lewd images of young children, police say
Concord man used generative AI to create lewd images of young children, police say The Mercury News
- Map Shows Built-Up Areas With Most Data Centers
Map Shows Built-Up Areas With Most Data Centers Newsweek
Score: 40🌐 MovesAug 6, 2026https://www.newsweek.com/map-shows-built-up-areas-with-most-data-centers-12293143 - How much of my boss's job can AI do?
Six months after trying to automate myself, I gave Claude Fable 5 a bigger job: replacing Casey
- Why do people actually prefer AI-generated stories to human writing? New study reveals surprising insights
In the literary industry, using artificial intelligence is still a taboo. Even accusations of AI use have dire consequences, from the infamously canceled release of the novel Shy Girl to the massive online backlash against a prestigious literary award going to an apparently AI-written short story . Like all AI-generated art, creative writing crafted by a bot seems to be missing something fundamentally human. But as AI-generated content advances and becomes harder and harder to distinguish from human-made work, is people’s distaste for robot writing based on the product itself, or merely on how it was made? A new study suggests the latter: Though readers give preference to stories they think are written by humans, ultimately, they like AI-written pieces the best. A pro-human bias The study, published by Cambridge University Press , asked 1,682 adult participants to read one of six short stories. Three of the stories were written by humans. The other three were generated by ChatGPT, each with a similar topic and style to one of the human-written samples. Each reader was told whether the story they read was written by a human or by AI—but they weren’t always told the truth. Overall, readers rated AI-written stories as more engaging and higher-quality than their human-written counterparts. When participants were told the AI stories were written by humans, they gave them even higher scores, suggesting an implicit bias against AI-generated content regardless of its quality. One of the study’s authors, Deena Skolnick Weisberg of Villanova University’s Department of Psychological and Brain Sciences, said in a press release that “public assumptions about AI’s capabilities are increasingly out of date.” “We assume creative writing requires uniquely human qualities, such as emotional understanding and lived experience, which leads people to underestimate AI’s capabilities,” she said. What sets AI writing apart? AI-generated writing is trained on human work, and this experiment specifically called for AI stories based on existing human-written narratives. What, then, makes AI writing more appealing to readers? Weisberg thinks it may have to do with AI writing’s tendency to be “clearer, more direct, and easier to process,” she said. “By contrast, human-written stories are often more subtle and complex.” “Perhaps people generally prefer predictability, because difficult or subtle material requires more brain power,” she added. AI writing certainly fits the bill of predictability: A recent report identified current trends in AI-generated content , including infrequent punctuation, long sentences, and a reliance on rhetorical conventions like “it’s not X, it’s Y” and the rule of threes. A different study published earlier this year found that large language model (LLM) usage contributed to the “blandification” of human writing, producing copy that authors deemed less creative, less passionate, and more homogenous in tone than unassisted human writing. Despite this, authors who used LLMs were just as satisfied with their output as those who didn’t, indicating that humans are becoming more and more comfortable with AI-written content. But even Weisberg reasons that artificial intelligence can never truly stand in for human writers. “We may need to make room for AI-generated novels, and for AI/human co-written novels, but that doesn’t mean that there’s no longer space for us to appreciate the process of human creativity,” she said. “Humans write as a form of creative self-expression or to challenge ourselves, or to make sense of our experiences. The fact that AI can generate human-like stories doesn’t change any of that.”