The Signal Foundation president recalls where she was when she heard Trump cabinet officials had added a journalist to a highly sensitive group chat. In March of this year, Meredith Whittaker was at her kitchen table in Paris when Signal, the encrypted messaging service she runs, suddenly became an international headline . A colleague sent their group chat the story ricocheting across the globe: "The Trump Administration Accidentally Texted Me Its War Plans." Of course, you know the rest: In the piece, The Atlantic's editor in chief, Jeffrey Goldberg, detailed how he'd been added to a Signal chat about an upcoming military operation in Yemen. Over the following days and weeks, the incident would become known as " SignalGate "--and created a legitimate risk that the fallout would cause people to question Signal's security, instead of pointing their fingers at the profoundly dubious op-sec of senior-level Trump officials. In fact, Signal's user numbers grew by leaps and bounds, both in the US and around the world. It's growth that, Whittaker thinks, is coming at a time when "people are feeling in a much deeper, much more personal way why privacy might be important." On this week's episode of, I talked to Whittaker, who also cofounded the AI Now Institute, about the aftermath of SignalGate, the trajectory of artificial intelligence, and the tech industry's current relationship with politics. Nice to see you, Katie. Nice to see you, too. Brace yourself, we always start these conversations with a little warmup, so I'm going to ask you some very fast questions. I knew you were gonna say that. What's the weirdest AI application you've ever seen? A chatbot that pretends to be your friend.

Large language models (LLMs) achieve remarkable fluency across linguistic and reasoning tasks but remain systematically prone to hallucination. Prevailing accounts attribute hallucinations to data gaps, limited context, or optimization errors. We argue instead that hallucination is a structural outcome of the transformer architecture. As coherence engines, transformers are compelled to produce fluent continuations, with self-attention simulating the relational structure of meaning but lacking the existential grounding of temporality, mood, and care that stabilizes human understanding. On this basis, we distinguish ontological hallucination, arising when continuations require disclosure of beings in world, and residual reasoning hallucination, where models mimic inference by recycling traces of human reasoning in text. We illustrate these patterns through case studies aligned with Heideggerian categories and an experiment across twelve LLMs showing how simulated "self-preservation" emerges under extended prompts. Our contribution is threefold: (1) a comparative account showing why existing explanations are insufficient; (2) a predictive taxonomy of hallucination linked to existential structures with proposed benchmarks; and (3) design directions toward "truth-constrained" architectures capable of withholding or deferring when disclosure is absent. We conclude that hallucination is not an incidental defect but a defining limit of transformer-based models, an outcome scaffolding can mask but never resolve.

Dialogue agents based on large language models (LLMs) have shown promising performance in proactive dialogue, which requires effective strategy planning. However, existing approaches to strategy planning for proactive dialogue face several limitations: limited strategy coverage, preference bias in planning, and reliance on costly additional training. To address these, we propose PRINCIPLES: a synthetic strategy memory for proactive dialogue agents. PRINCIPLES is derived through offline self-play simulations and serves as reusable knowledge that guides strategy planning during inference, eliminating the need for additional training and data annotation. We evaluate PRINCIPLES in both emotional support and persuasion domains, demonstrating consistent improvements over strong baselines. Furthermore, PRINCIPLES maintains its robustness across extended and more diverse evaluation settings. See our project page at https://huggingface.co/spaces/kimnamssya/Principles.

Trump drops bombshell Tylenol autism announcement as he vows to rip up'disgraceful' vaccine schedule in major medical shake-up Jimmy Kimmel Live! will return TOMORROW after host was canned over Charlie Kirk comments Tylenol maker responds to Trump's plans to link everyday drug to autism The six hidden messages in the texts between Charlie Kirk's'assassin' and his trans lover DECODED Top plastic surgeon reveals secrets behind Catherine Zeta-Jones' youthful appearance: 'This isn't what happens when we age' Common kitchen spice may reverse Alzheimer's disease, study suggests Barack and Michelle Obama arrive apart on Spielberg's yacht after ex-president's startling marriage confession Miley Cyrus shares the medicine that has kept her'grounded in a sober lifestyle' for 5 years Jimmy Kimmel steps in to'protect' Ivanka Trump from handsy comedian in resurfaced video Seven charities including Teenage Cancer Trust cut ties with Sarah Ferguson after leaked email showed her apologising to'supreme friend' Jeffrey Epstein Heather Locklear fans can't believe how amazing the Melrose Place vet looks at 63... 40 years after fame hit'Brazilian Josef Fritzl' makes chilling claim to police after'holding stepdaughter captive for 22 years' American'sexpert' deported from Indonesia after furious Muslim officials accused her of hosting KAMA SUTRA demonstrations Beloved actress who played loud, loving matriarch in 2002 romcom makes rare outing in LA...can you guess who? Face of man who tried to'murder Jeffrey Epstein' days before pedophile financier's mysterious suicide Candace Owens says she'll make Brigitte Macron submit to MEDICAL EXAM after'French first lady is a man' claim sparked lawsuit Blindfolded and awaiting death: Horrifying footage shows Hamas executing'Israeli collaborators' in Gaza streets as baying crowd screams'Allahu Akbar' All the'Biblical signs' pointing to the Rapture coming TOMORROW as believers spread fears the end is nigh New'loaded water' trend slashes cravings so you can lose weight... as expert reveals how to maximize benefits Clear and startling images of what appears to be a UFO were captured over Los Angeles, sparking fresh debate about what's flying over America's biggest cities. A pair of Los Angeles residents were on their balcony when they spotted a black, V-shaped craft covered in lights moving slowly over the city on August 28. The sighting went on for roughly 25 minutes, with the UFO flying south until the witnesses eventually lost sight of it around 11:38pm local time (2:38am ET). The pair was able to capture both pictures and clear videos with a cellphone camera, zooming in to see nine white lights along the UFO's hull.

On this episode of, we discuss OpenAI's new teen safety features, the right's retaliation against critics of the late Charlie Kirk, and more of the week's biggest stories. Charlie Kirk (R) shaking hands with US President Donald Trump as he speaks on stage at America Fest 2024 in Phoenix, Arizona. All products featured on WIRED are independently selected by our editors. However, we may receive compensation from retailers and/or from purchases of products through these links. In today's episode, our host Zöe Schiffer is joined by WIRED's senior culture editor Manisha Krishnan to run through five of the best stories we published this week--from OpenAI implementing teen safety features to how human design is the new astrology. Zöe and Manisha also discuss the reverberating reactions to Charlie Kirk's death and why the work of many creators, from comic book artists to late night show hosts, is getting cancelled.

Gabrielle surging into major hurricane as forecasters warn of'life-threatening' impact to East Coast Fed governor installed by Trump outlines bold case to slash interest rates to 2.5% in months So is Meghan Markle's former best pal about to tell all? Jessica Mulroney has an axe to grind and'knows where the bodies are buried', friends warn amid claims she's penning memoir Incredible secret DNA weapon that nailed Bryan Kohberger... and how no criminal can hide again Why Jennifer Aniston is'being silenced' from speaking out on close friend Jimmy Kimmel's firing Six charities including Teenage Cancer Trust cut ties with Sarah Ferguson after leaked email showed her apologising to'supreme friend' Jeffrey Epstein Will Smith's'nepo baby' son Jaden sparks outrage after landing coveted job at designer fashion brand I've had crippling anxiety for years. Heather Locklear fans can't believe how amazing the Melrose Place vet looks at 63... 40 years after fame hit Whoopi Goldberg claims The View is too fearless not to discuss Kimmel canning... despite completely avoiding subject at crucial moment There's a new dating trend that's great news for guys who struggle to get laid. Even divorce lawyers say it's the secret to happiness. But ladies, I promise it'll backfire I'm a 49-year-old beauty editor and menopause gave me hair loss and short, brittle locks that wouldn't grow.

Recommender systems (RS), which are widely deployed across high-stakes domains, are susceptible to biases that can cause large-scale societal impacts. Researchers have proposed methods to measure and mitigate such biases -- but translating academic theory into practice is inherently challenging. RS practitioners must balance the competing interests of diverse stakeholders, including providers and users, and operate in dynamic environments. Through a semi-structured interview study (N=11), we map the RS practitioner workflow within large technology companies, focusing on how technical teams consider fairness internally and in collaboration with other (legal, data, and fairness) teams. We identify key challenges to incorporating fairness into existing RS workflows: defining fairness in RS contexts, particularly when navigating multi-stakeholder and dynamic fairness considerations. We also identify key organization-wide challenges: making time for fairness work and facilitating cross-team communication. Finally, we offer actionable recommendations for the RS community, including HCI researchers and practitioners.

Spoken dialogue systems increasingly employ large language models (LLMs) to leverage their advanced reasoning capabilities. However, direct application of LLMs in spoken communication often yield suboptimal results due to mismatches between optimal textual and verbal delivery. While existing approaches adapt LLMs to produce speech-friendly outputs, their impact on reasoning performance remains underexplored. In this work, we propose Think-Verbalize-Speak, a framework that decouples reasoning from spoken delivery to preserve the full reasoning capacity of LLMs. Central to our method is verbalizing, an intermediate step that translates thoughts into natural, speech-ready text. We also introduce ReVerT, a latency-efficient verbalizer based on incremental and asynchronous summarization. Experiments across multiple benchmarks show that our method enhances speech naturalness and conciseness with minimal impact on reasoning. The project page with the dataset and the source code is available at https://yhytoto12.github.io/TVS-ReVerT

AI co-writing systems challenge long held ideals about agency and ownership in the creative process, thereby hindering widespread adoption. In order to address this, we investigate conceptions of agency and ownership in AI creative co-writing. Drawing on insights from a review of commercial systems, we developed three co-writing systems with identical functionality but distinct interface metaphors: agentic, tool-like, and magical. Through interviews with professional and non-professional writers (n = 18), we explored how these metaphors influenced participants' sense of control and authorship. Our analysis resulted in a taxonomy of agency and ownership subtypes and underscore how tool-like metaphors shift writers' expected points of control while agentic metaphors foreground conceptual contributions. We argue that interface metaphors not only guide expectations of control but also frame conceptions of authorship. We conclude with recommendations for the design of AI co-writing systems, emphasizing how metaphor shapes user experience and creative practice.

Peer recovery narratives provide unique benefits beyond professional or lay mentoring by fostering hope and sustained recovery in eating disorder (ED) contexts. Yet, such support is limited by the scarcity of peer-involved programs and potential drawbacks on recovered peers, including relapse risk. To address this, we designed RecoveryTeller, a chatbot adopting a recovered-peer persona that portrays itself as someone recovered from an ED. We examined whether such a persona can reproduce the support affordances of peer recovery narratives. We compared RecoveryTeller with a lay-mentor persona chatbot offering similar guidance but without a recovery background. We conducted a 20-day cross-over deployment study with 26 ED participants, each using both chatbots for 10 days. RecoveryTeller elicited stronger emotional resonance than a lay-mentor chatbot, yet tensions between emotional and epistemic trust led participants to view the two personas as complementary rather than substitutes. We provide design implications for mental health chatbot persona design.