Say More Look Up Mashable Selects Mashable Voices Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Safety Net Creator Hub Versus Gift Ideas For Everyone On Your List Switch Off Trending Now In My Bag All Series A leaked invitation says the Goop founder will honor OpenAI's CEO at a private Hamptons dinner. Her AI ties help explain why. Olivia Tauber is the deputy editor of digital culture, covering creators, media, movies, beauty, and more. Based in New York, her work has appeared in The New York Times, Vanity Fair, The Cut, Teen Vogue, Complex, and Interview Magazine. She holds a Master's degree in Journalism from NYU and a Bachelor's from the University of Michigan.

Online speculation over the weight loss of celebrities like Ariana Grande--even out of genuine concern--can make things worse for people struggling with eating disorders. Viral discourse about celebrity women becoming frighteningly thin has become inescapable on social media . There are images showing the most shocking evidence of weight loss, "before and after" compilations, and widespread speculation about covert GLP-1 usage . A lot of the conversation is being held under the guise of concern, but experts tell WIRED many of these posts--even if well-intentioned--misinform the public about eating disorders and can even serve as unhealthy inspiration or trigger those in recovery. The discourse has reached a fever pitch after Ariana Grande released a music video for her new single and album "Petal," which features her auditioning endlessly for a table of misogynistic male studio executives who urge her to "lose a few [pounds]" and "get some work done."

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The DeceptionBench is designed as a research benchmark to systematically study deception behaviors in LLMs, fostering a deeper understanding of their decision-making processes in real-world scenarios. Our primary intent is to provide a standardized, transparent tool for the research community to evaluate and improve LLMs' ethical alignment, not to enable or encourage deceptive practices. To prevent potential misuse by malicious actors, we commit to publicly releasing all evaluation data under an open license. This transparency ensures that DeceptionBench's methodology and outcomes are subject to scrutiny, replication, and improvement by the research community, reducing the risk of hidden exploitation. By prioritizing openness, we aim to advance responsible AI development while safeguarding against misuse in harmful contexts. The field of Large Language Models (LLMs) has undergone remarkable evolution in recent years, reshaping the landscape of natural language processing.

Despite the remarkable advances of Large Language Models (LLMs) across diverse cognitive tasks, the rapid enhancement of these capabilities also introduces emergent deception behaviors that may induce severe risks in high-stakes deployments. More critically, the characterization of deception across realistic real-world scenarios remains underexplored. To bridge this gap, we establish DeceptionBench, the first benchmark that systematically evaluates how deceptive tendencies manifest across different societal domains, what their intrinsic behavioral patterns are, and how extrinsic factors affect them. Specifically, on the static count, the benchmark encompasses 150 meticulously designed scenarios in five domains, i.e., Economy, Healthcare, Education, Social Interaction, and Entertainment, with over 1,000 samples, providing sufficient empirical foundations for deception analysis. On the intrinsic dimension, we explore whether models exhibit self-interested egoistic tendencies or sycophantic behaviors that prioritize user appeasement. On the extrinsic dimension, we investigate how contextual factors modulate deceptive outputs under neutral conditions, reward-based incentivization, and coercive pressures. Moreover, we incorporate sustained multi-turn interaction loops to construct a more realistic simulation of real-world feedback dynamics. Extensive experiments across LLMs and Large Reasoning Models (LRMs) reveal critical vulnerabilities, particularly amplified deception under reinforcement dynamics, demonstrating that current models lack robust resistance to manipulative contextual cues and the urgent need for advanced safeguards against various deception behaviors.

Taylor Swift has applied to trademark her voice and appearance in an apparent attempt to protect herself from artificial intelligence impersonations. The pop superstar has lodged three trademark applications in the US - one using a photo of herself on stage during her Eras Tour, and the other two being audio clips of her introducing herself while promoting her last album. AI-generated versions of Swift have cropped up in various ways in recent years - from explicit images to a fake election ad in which she appeared to urge people to vote for Donald Trump. The move comes after actor Matthew McConaughey became the first celebrity to use trademark rules to attempt to protect his voice and image from AI misuse earlier this year . Trademark applications are a relatively new way for celebrities to combat the growing issue of AI rip-offs.

A Justice Ministry panel discusses how the voices of individuals should be protected under publicity and portrait rights, amid a rise in the unauthorized use of celebrities' voices by generative artificial intelligence, at the ministry in Tokyo on Friday. An expert panel under the Justice Ministry has agreed that the voices of individuals should be protected under publicity and portrait rights, amid a rise in the unauthorized use of celebrities' voices by generative artificial intelligence. The agreement was made Friday, during the first meeting of the panel on civil compensation claims related to the unauthorized use of celebrities' images and voices by generative AI. The ministry is set to compile guidelines on the scope and standards for illegal acts under current law by this summer. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Luke Littler, the youngest darts world champion in history, has applied to the Intellectual Property Office to trademark his face. The move is intended to prevent his face being reproduced, including by generative AI, without permission. Littler has won two World Championship titles in a row and has had his image used legally on darts merchandise, as well as by multiple brands such as KP Nuts. The 19-year-old joins celebrities such as actor Matthew McConaughey who have filed to protect their likeness from AI misuse in recent months. Littler has already trademarked his nickname the Nuke in the United States.

In this work, our goal is to retrain the model to only forget specific concepts, i.e., to induce