The proliferation of generative AI and deceptive synthetic media threatens the global information ecosystem, especially across the Global Majority. This report from WITNESS highlights the limitations of current AI detection tools, which often underperform in real-world scenarios due to challenges related to explainability, fairness, accessibility, and contextual relevance. In response, WITNESS introduces the Truly Innovative and Effective AI Detection (TRIED) Benchmark, a new framework for evaluating detection tools based on their real-world impact and capacity for innovation. Drawing on frontline experiences, deceptive AI cases, and global consultations, the report outlines how detection tools must evolve to become truly innovative and relevant by meeting diverse linguistic, cultural, and technological contexts. It offers practical guidance for developers, policy actors, and standards bodies to design accountable, transparent, and user-centered detection solutions, and incorporate sociotechnical considerations into future AI standards, procedures and evaluation frameworks. By adopting the TRIED Benchmark, stakeholders can drive innovation, safeguard public trust, strengthen AI literacy, and contribute to a more resilient global information credibility.

Satellite-based estimates of greenhouse gas (GHG) properties from observations of reflected solar spectra are integral for understanding and monitoring complex terrestrial systems and their impact on the carbon cycle due to their near global coverage. Known as retrieval, making GHG concentration estimations from these observations is a non-linear Bayesian inverse problem, which is operationally solved using a computationally expensive algorithm called Optimal Estimation (OE), providing a Gaussian approximation to a non-Gaussian posterior. This leads to issues in solver algorithm convergence, and to unrealistically confident uncertainty estimates for the retrieved quantities. Upcoming satellite missions will provide orders of magnitude more data than the current constellation of GHG observers. Development of fast and accurate retrieval algorithms with robust uncertainty quantification is critical. Doing so stands to provide substantial climate impact of moving towards the goal of near continuous real-time global monitoring of carbon sources and sinks which is essential for policy making. To achieve this goal, we propose a diffusion-based approach to flexibly retrieve a Gaussian or non-Gaussian posterior, for NASA's Orbiting Carbon Observatory-2 spectrometer, while providing a substantial computational speed-up over the current operational state-of-the-art.

Tools for Humanity, a startup co-founded by Sam Altman, has launched its its World eyeball-scanning identity verification system in the US. During an event in San Francisco, Altman reportedly said that World's technology provides "a way to make sure humans remained central and special in a world where the internet had a lot of AI-driven content." Altman is also one of the founders and is currently the CEO of OpenAI, which is perhaps the most prominent artificial intelligence company today. World was used to be known as Worldcoin until Tools of Humanity decided to focus on the digital ID aspect of the project rather than the cryptocurrency part, because the Biden administration didn't have a friendly stance towards crypto. The project uses basketball-sized spherical objects called the Orb to scan a user's irises, which it then turns into a unique IrisCode for them. It will then use that information to create a World ID for the user that they can use to log into integrated platforms, including Minecraft and Reddit.

Ukraine's parliament is expected to ratify a controversial minerals deal with the United States in a decisive step towards securing the latter's long-term commitment to the war-battered country amid stalled efforts to strike a Ukraine-Russia ceasefire. The deal, signed by Kyiv and Washington on Wednesday, pushed by US President Donald Trump and after protracted negotiations, marks an inflection point of sorts in the war, granting the US priority access to Ukraine's critical minerals as a means of deterring future Russian aggression. However, it stops short of offering specific security guarantees and questions remain over accessing minerals in areas under Russian control. Ukraine's Minister of Foreign Affairs Andrii Sybiha said on Thursday that the deal "marks an important milestone in Ukraine–US strategic partnership aimed at strengthening Ukraine's economy and security". "We're expecting it to be discussed and ratified by Ukraine's parliament later today," said Al Jazeera's Zein Basravi, reporting from Kyiv.

Following several months of numerous high-profile aviation accidents, new data suggest pilots are facing a specific threat when it comes to keeping airline passengers safe in the skies. Last year, drones accounted for approximately two-thirds of reported near-midair collisions with commercial aircraft taking off or landing within the country's 30 busiest airports, according to the Associated Press. The findings come as aviation safety data indicate drones accounted for the highest number of near-misses since 2020, with the first reports dating back to 2014. "The rise in recreational and commercial drone use has simply outpaced education and enforcement," aviation attorney Jason Matzus told Fox News Digital. "More people are flying drones without fully understanding the rules or the risks."

The enemy is attacking Odesa with strike drones. There is considerable damage to civilian infrastructure, particularly dwellings,

In an unusual twist in the governor's race, a wealthy Democratic businessman is suing former Los Angeles Mayor Antonio Villaraigosa over the use of a common phrase in political campaigns. Stephen Cloobeck, a philanthropist and Democratic donor who made his fortune in real estate and hospitality, filed a lawsuit against Villaraigosa this week after the former mayor repeatedly described himself as a "proven problem solver" in campaign materials. Cloobeck, who has applied for a federal trademark of the phrase "I am a proven problem solver," texted the federal lawsuit to Villaraigosa late Tuesday, though the former mayor has not been served yet. The lawsuit argues that Cloobeck has been using the phrase since March 2024, and that "it has acquired extensive goodwill, developed a high degree of distinctiveness, and become famous, well known, and recognized as identifying Cloobeck's campaign." "In light of the fame, acquired goodwill, and overall consumer recognition of [the phrase Cloobeck is seeking to patent, he] is very concerned that the public will likely be confused or mistakenly believe that Villaraigosa's campaign is endorsed, approved, sponsored by, or affiliated, connected, or associated with" Villaraigosa, the suit alleges.

Russian drones attacked Ukraine's Black Sea port of Odesa early on Thursday, killing at least two people and injuring five, the regional governor said. The attack sparked fires and damaged residential dwellings and infrastructure. In Kharkiv, Ukraine's second-largest city in the northeast, the mayor said another Russian drone had struck a petrol station in the city centre, triggering a fire. Ukraine's SBU security agency claimed responsibility for a drone strike on a defence manufacturing facility in Russia. The strike on Murom Instrument-Building Plant, 300km (186 miles) east of Moscow, sparked a fire and damaged two buildings, the region's governor reported.

Racial disparities in healthcare expenditures are well-documented, yet the underlying drivers remain complex and require further investigation. This study employs causal and counterfactual path-specific effects to quantify how various factors, including socioeconomic status, insurance access, health behaviors, and health status, mediate these disparities. Using data from the Medical Expenditures Panel Survey, we estimate how expenditures would differ under counterfactual scenarios in which the values of specific mediators were aligned across racial groups along selected causal pathways. A key challenge in this analysis is ensuring robustness against model misspecification while addressing the zero-inflation and right-skewness of healthcare expenditures. For reliable inference, we derive asymptotically linear estimators by integrating influence function-based techniques with flexible machine learning methods, including super learners and a two-part model tailored to the zero-inflated, right-skewed nature of healthcare expenditures.

The expansion of large-scale text-to-image diffusion models has raised growing concerns about their potential to generate undesirable or harmful content, ranging from fabricated depictions of public figures to sexually explicit images. To mitigate these risks, prior work has devised machine unlearning techniques that attempt to erase unwanted concepts through fine-tuning. However, in this paper, we introduce a new threat model, Toxic Erasure (ToxE), and demonstrate how recent unlearning algorithms, including those explicitly designed for robustness, can be circumvented through targeted backdoor attacks. The threat is realized by establishing a link between a trigger and the undesired content. Subsequent unlearning attempts fail to erase this link, allowing adversaries to produce harmful content. We instantiate ToxE via two established backdoor attacks: one targeting the text encoder and another manipulating the cross-attention layers. Further, we introduce Deep Intervention Score-based Attack (DISA), a novel, deeper backdoor attack that optimizes the entire U-Net using a score-based objective, improving the attack's persistence across different erasure methods. We evaluate five recent concept erasure methods against our threat model. For celebrity identity erasure, our deep attack circumvents erasure with up to 82% success, averaging 57% across all erasure methods. For explicit content erasure, ToxE attacks can elicit up to 9 times more exposed body parts, with DISA yielding an average increase by a factor of 2.9. These results highlight a critical security gap in current unlearning strategies.