Law
How to Make Apps and Websites Remove Your Nonconsensual Nudes
Starting May 19, tech platforms in the US will have to start complying with the Take It Down Act. Here's how more than a dozen of the largest platforms are handling takedown demands for your nudes. Abstract collage illustration of woman face partially obscured by a glitching pixelated effect on a green background. Starting on Tuesday, May 19, tech platforms have to provide a way for people to report nonconsensual intimate images and videos, or NCII, uploaded to their platforms. The new requirement is thanks to the Take It Down Act, a law backed by First Lady Melania Trump that passed last year with bipartisan support.
Elon Musk loses case against Sam Altman over OpenAI's overhaul
Elon Musk loses case against Sam Altman over OpenAI's overhaul Elon Musk arrives at the Ronald V. Dellums Federal Building for court in Oakland, California on April 30. A jury rejected Elon Musk's claims that OpenAI under Sam Altman's leadership betrayed its mission to benefit the public by morphing into a for-profit business, finding that he waited too long to sue the company. The verdict reached Monday in federal court in Oakland, California, follows a trial over the bitter feud between the entrepreneurs who worked together to launch the startup in 2015. OpenAI has since evolved into one of the world's most valuable and powerful artificial intelligence companies. "I think there is a substantial amount of evidence to support the jury's findings," U.S. District Judge Yvonne Gonzalez Rogers said when she accepted the nine-member jury's unanimous conclusion after about two hours of deliberations.
Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning
Troxell, David, Roemer, Noah, Montúfar, Guido
Differentiable optimization layers are traditionally integrated in predict-then-optimize frameworks where a neural model estimates parameters that subsequently serve as fixed inputs to downstream decision-making optimization problems. In this work, we introduce the concept of a "fairness layer": a differentiable optimization layer appended to a model's output layer that guarantees a chosen notion of output parity is satisfied when integrated into a neural network. Additionally, we introduce an online primal-dual inference algorithm that provides provable aggregate fairness guarantees for streaming predictions with arbitrarily small batch sizes, where traditional per-batch constraints become overly restrictive. Numerical experiments demonstrate the effectiveness of the fairness layer and associated algorithm, and theoretical analysis characterizes the layer's differentiability and stability properties during model training and backpropagation. Our code for these experiments is publicly available on GitHub (https://github.com/dtroxell19/FairDL-ICML-2026.git) and our public Python package documentation can be found online: https://dtroxell19.github.io/fairness_training/.
Adaptive Experimentation for Censored Survival Outcomes
Wang, Yuxin, Frauen, Dennis, Schweisthal, Jonas, Schröder, Maresa, Javurek, Emil, Feuerriegel, Stefan
Adaptive experimentation enables efficient estimation of causal effects, but existing methods are not designed for survival data with censoring, where event times are only partially observed (e.g., overall survival in cancer trials but with dropout). In this paper, we develop a novel framework for adaptive experimentation to estimate causal effects under right censoring. For this, we derive the semiparametric efficiency bound for the average survival effect curve as a function of the treatment allocation policy and thereby obtain a closed-form efficiency-optimal allocation policy. The policy generalizes classical Neyman allocation to survival settings by prioritizing patient strata where both event and censoring dynamics induce high uncertainty. Building on this, we propose the Adaptive Survival Estimator (ASE), an adaptive framework that learns the allocation policy and estimates the average survival effect curve sequentially. Our framework has three main benefits: (i) it accommodates arbitrary machine learning models for nuisance estimation; (ii) it is guided by a closed-form efficiency-optimal allocation policy; and (iii) it admits strong theoretical guarantees, including asymptotic normality via a martingale central limit theorem. We demonstrate our framework across various numerical experiments to show consistent efficiency gains over uniform randomization and censoring-agnostic baselines.
How Sam Altman's victory over Elon Musk clears way for OpenAI's trillion-dollar ambitions
Elon Musk, left, and Sam Altman. Elon Musk, left, and Sam Altman. How Sam Altman's victory over Elon Musk clears way for OpenAI's trillion-dollar ambitions OpenAI's plans now seem all but guaranteed, given that the world's richest man couldn't put a stop to them On Monday morning, a jury in Oakland, California, handed a resounding victory to Sam Altman and OpenAI in their long, bitter courtroom battle with Elon Musk. The federal jury found Altman, OpenAI and its president, Greg Brockman, not liable for Elon Musk's claims that they unjustly enriched themselves and broke a founding contract made with Musk when founding the startup. The unanimous verdict, delivered after less than two hours of deliberation, is a stark rebuke of Musk and his lawyer's claims that Altman "stole a charity" through his leadership of OpenAI.
Satellites and AI used to track UK hedgehogs in bid to slow decline
Researchers at the University of Cambridge are using satellite data and AI in an effort to slow the decline in Britain's hedgehog population. Using an AI tool called Tessera, which analyses detailed images of the UK gathered from space, experts can precisely determine locations of hedgehog habitats - and where these are disappearing. The resulting maps capture landscapes in minute detail, including down to individual hedgerows, while AI can accurately predict hedgehog-friendly places obscured by cloud cover. Those behind the project hope it will help to shed light not just on where hedgehogs live across the UK, but barriers preventing them from finding food and mates. The researchers say Tessera's outputs can be used to track the impact of new housing developments and other environmental changes on landscapes that could affect hedgehogs over time.
Jury hands victory to Sam Altman and OpenAI in battle with Elon Musk
The federal jury in Oakland, California, found Altman, OpenAI and its president, Greg Brockman, not liable for Elon Musk's claims that they unjustly enriched themselves and broke a founding contract made with Musk when founding the startup. The verdict, delivered after less than two hours of deliberation, is a stark rebuke of Musk and his lawyer's claims that Altman "stole a charity" through his leadership of OpenAI . It also provides the AI firm with a clear path ahead to pursue going public later this year at about a $1tn valuation . The jury's finding is a non-binding, advisory verdict that left Judge Yvonne Gonzalez Rogers with ultimate power to issue her own ruling in the case. Gonzalez Rogers immediately said that she would agree with the jury's decision and dismissed Musk's claims.
Disney faces a class action lawsuit over facial recognition tech
The complaint says park visitors don't get sufficient notice they're being scanned. Disney is being sued over use of facial recognition technology at its amusement parks. The class action lawsuit alleges that the entertainment brand does not adequately inform guests that it scans people's faces at the entrances to Disneyland and California Adventure. The complaint is seeking at least $5 million on behalf of park visitors. Guests should be able to expressly opt in to this type of sensitive facial recognition technology with written consent -- the onus of privacy rights should not be on the victim, writes Blake Yagman, a lawyer for the proposed class of visitors, in the complaint.
Elon Musk just lost another lawsuit. Will he keep fighting?
Elon Musk just lost another lawsuit. Elon Musk, the world's richest man, has not been winning in court lately. His loss on Monday in his lawsuit against OpenAI and its co-founder Sam Altman is the latest in a string of legal defeats or settlements. Late last year he agreed to settle with former Twitter executives and thousands of former employees of the social platform, which he has renamed X, after fighting for years to pay them nothing. Then in March, he lost a case brought against him by investors of Twitter, who claimed they were misled by public statements he made during the takeover.
Jury tosses Elon Musk's lawsuit against OpenAI and its boss Sam Altman
A California jury has tossed out Elon Musk's high-profile lawsuit against OpenAI and its boss Sam Altman. In a unanimous verdict, the case was thrown out because Musk had filed his lawsuit after a statute of limitations to bring such claims had expired. Musk had accused Altman of breaching a non-profit contract by shifting the ChatGPT-maker to a for-profit company after Musk donated $38m (£28.5m). Musk had argued Altman deceived him by accepting his money and then reneging on OpenAI's original non-profit mission to develop artificial intelligence (AI) technology for the benefit of humanity. Jurors spent three weeks viewing internal correspondence and hearing testimony, and arrived at a verdict on Monday after deliberating for roughly two hours.