'Digging the grave of my profession': the Hollywood creatives training AI to do their jobs H ollywood creatives are taking gig work to train AI models to replicate their skills in a bid to offset tightening earnings in a trend one compared to being "handed a shovel and asked to dig the grave of my profession". Experienced and award-winning writers, directors and producers are being paid from $12 to $200 an hour to teach AI models the intricacies of their jobs, from writing a screenplay to devising a shooting schedule. With feelings ranging from fatalism to guilt, the creatives have signed up with some of the booming training agencies, which have contracts with the biggest AI companies including Anthropic and OpenAI, to pass on hard-won human skills in industries such as finance, health, law and social work. While they wait for entertainment industry work, they give notes on the AI systems' attempts to do the tasks they would hope to be paid for themselves. It comes amid a slump in jobs in the motion picture and sound recording industries, where AI is starting to take roles from actors, editors and special effects artists.

George Dover poses for a portrait at his home in Beaverton, Oregon. Dover was laid off in 2024. George Dover poses for a portrait at his home in Beaverton, Oregon. Dover was laid off in 2024. Every weekday, Matt, a software engineer, looks forward to his four-hour train commute to Pawling, New York.

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The rapid advancement of diffusion models has enabled high-fidelity and semantically rich text-to-image generation; however, ensuring fairness and safety remains an open challenge. Existing methods typically improve fairness and safety at the expense of semantic fidelity and image quality. In this work, we propose RespoDiff, a novel framework for responsible text-to-image generation that incorporates a dual-module transformation on the intermediate bottleneck representations of diffusion models. Our approach introduces two distinct learnable modules: one focused on capturing and enforcing responsible concepts, such as fairness and safety, and the other dedicated to maintaining semantic alignment with neutral prompts. To facilitate the dual learning process, we introduce a novel score-matching objective that enables effective coordination between the modules. Our method outperforms state-of-the-art methods in responsible generation by ensuring semantic alignment while optimizing both objectives without compromising image fidelity. Our approach improves responsible and semantically coherent generation by ~20% across diverse, unseen prompts.

Existing post-hoc approaches can remove undesired concepts but often degrade useful signals. We introduce SPLINCE--Simultaneous Projection for LINear concept removal and Covariance prEservation--which eliminates sensitive concepts from representations while exactly preserving their covariance with a target label. SPLINCE achieves this via an oblique projection that "splices out" the unwanted direction yet protects important label correlations. Theoretically, it is the unique solution that removes linear concept predictability and maintains target covariance with minimal embedding distortion. Empirically, SPLINCE outperforms baselines on benchmarks such as Bias in Bios and Winobias, removing protected attributes while minimally damaging main-task information.

After decades risking arrest, South Korea's tattoo artists step into the limelight When Kim Tae-nam took the stage last Saturday in Seoul, it was a moment he had long been waiting for - the career he had chosen was no longer illegal. He couldn't stop smiling, the relief spilling into his voice: This was only possible because of our effort, all your sweat and tears. Let's hear it from everyone: Tattoos are art! They had gathered on a rooftop in Seongsu, a hip Seoul neighbourhood, for Ink Bomb: more than 90 local tattooists and artists openly celebrating body art, which had thrived in the shadows for decades. Just days before, South Korea's top court had overturned its 1992 ruling that defined tattooing as a medical act - bringing to an end Korean tattooists' decades-long fight for legitimacy.

Others say they don't need us. It's time for us to think of ourselves not as the high priests of health care but as what we have always been: healers. Not long ago, I cared for a middle-aged man I'll call Jim, who was generally healthy but had recently started to feel sluggish. One of his friends told him to try a hormone supplement. After Jim saw on social media that Robert F. Kennedy, Jr., the Trump Administration's Secretary of Health and Human Services, had endorsed supplements as a part of an "anti-aging" regimen, he ordered one from a telehealth company. A few months later, he noticed swelling and pain in his calf. ChatGPT warned him that he might have a blood clot.

We asked teachers about their experiences with AI in the classroom -- here's what they said Since ChatGPT and other large language models burst into public consciousness, school boards are drafting policies, universities are hosting symposiums and tech companies are relentlessly promoting their latest AI-powered learning tools . In the race to modernize education, artificial intelligence (AI) has become the new darling of policy innovation. While AI promises efficiency and personalization, it also introduces complexity, ethical dilemmas and new demands . Teachers, who are at the heart of learning along with students, are watching this transformation with growing unease. For example, according to the Alberta Teachers' Association, 80 to 90 per cent of educators surveyed expressed concern about AI's potential negative effects on education.