A New Mexico judge yesterday ordered Meta to pay $567 million for a fund that would alleviate the "public nuisance" created by its social media services. The order to pay for youth mental health care is in addition to $375 million in civil penalties that a jury ordered Meta to pay earlier in the same case.
New Mexico Attorney General Raul Torrez sued Meta in a Santa Fe County court in 2023. A jury found in March 2026 that Meta's social media platforms do not effectively protect kids from child exploitation and ordered the company to pay civil damages for violating state consumer protections and misleading parents about the safety of its apps.
The jury trial was just phase 1 of the case involving Meta, the owner of Facebook, Instagram, and WhatsApp. "The Phase 1 jury trial considered the State’s Unfair Practices Act claims and resulting civil penalties. The Phase 2 bench trial considered the State’s request for abatement based upon the State’s allegation that the Defendant, Meta, created a public nuisance," Judge Bryan Biedscheid wrote yesterday in the $567 million judgment. Meta reported $60.8 billion in revenue and $15.85 billion in net income in Q2 2026.
© Getty Images | Cavan Images
It won't come as a surprise that Trump's Department of Government Efficiency (DOGE) didn't save taxpayers nearly as much as it claimed. Analysis from outside the government showed savings claims were heavily inflated, and now the government's own watchdog has said it wasn't able to confirm savings claims made in DOGE's so-called "Wall of Receipts."
For example, DOGE reported savings of $49.2 billion from cutting grants, but almost none of it could be verified, the US Government Accountability Office (GAO) said in its report yesterday. The GAO is the auditing and investigating arm of Congress and issued the DOGE report in response to a June 2025 request from Sens. Gary Peters (D-Mich.) and Richard Blumenthal (D-Conn.).
"The Wall of Receipts did not provide sufficient information to verify the method DOGE used to calculate savings, or what the savings consisted of, for 13,553 of the 15,887 grants it reported as terminated. This corresponds to about 96 percent of the DOGE-reported grant savings," the GAO report said.
© Getty Images | Samuel Corum
'Most people don’t want pervert glasses that can film us without our consent,' said a spokesperson from activist group Everyone Hates Elon. The group has launched a series of guerilla adverts deriding non-consensual filming by the glasses as well as an email campaign encouraging people to legally object to being filmed by Meta glasses under general data protection regulations, which over 20,000 people have signed.
Rights groups have warned that the glasses threaten the right to privacy, while countries such as Germany are reportedly considering a ban.
And while Meta’s safety guidelines say smart glasses should not be used for 'harassment, infringing on privacy rights, or capturing sensitive information', women have taken to social media to share their stories of being filmed by men without their consent.
Watch as Guardian columnist and Opinion editor Kirsty Major dives into why fears of surveillance and 'creepy men' mean Meta can never convince her to love the glasses – and read more about the glasses via the link in the bio
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© Photograph: Guardian
© Photograph: Guardian
© Photograph: Guardian
Nature, Published online: 05 August 2026; doi:10.1038/s41586-026-10977-8
Editorial Expression of Concern: Tumour exosome integrins determine organotropic metastasisNature, Published online: 05 August 2026; doi:10.1038/s41586-026-10890-0
The RNA-binding protein ZFP36L2 mediates stress-adaptive plasticity in intestinal regeneration and colorectal cancer metastasis.Nature, Published online: 05 August 2026; doi:10.1038/s41586-026-10873-1
M12 is a metabolically activated molecular glue that recruits diverse proteins to DCAF11 for ubiquitin-mediated degradation, revealing a glutathione-dependent mechanism that broadens targeted protein degradation across multiple substrates.Nature, Published online: 05 August 2026; doi:10.1038/s41586-026-10887-9
Cell-type-specific opioid blockade in accumbal cholinergic interneurons abolishes morphine-reward learning without impairing analgesia and decouples morphine-evoked dopamine elevations from acetylcholine dips, suggesting pro-cholinergic strategies to limit early opioid reward acquisition.Despite most Australians supporting clean technology, the campaign against wind and solar infrastructure has proven to be effective, striking a chord with many of those living in remote and rural areas. So how do we bring everyone along on the transition to a renewable energy-focused future? And who’s putting up roadblocks?
The Guardian’s environment and climate correspondent Graham Readfearn joins Reged Ahmad to unpack Australia’s relationship with renewables
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© Composite: Carly Earl
© Composite: Carly Earl
© Composite: Carly Earl
Speak into a phone and an app can render your words in another language in seconds. AI-powered speech translation can be fast, convenient and fluent. But fluency does not guarantee that people will understand one another.
In the most recent census, 880,000 people in England and Wales (excluding tourists and other short-term visitors) said they could not speak English well, and 161,000 not at all. That’s more than a million residents who may need language support in their daily lives, including when trying to access essential public services.
The linguistic range is vast. London alone is home to more than 250 languages. Tight budgets and a shortage of interpreters for some languages can make it difficult to secure an interpreter with the right dialect and expertise for a pressing legal, health or social care matter.
Notice we say “interpreter”, not translator. In professional language services, translation typically deals with written texts, while interpreting facilitates spontaneous communication between users of different spoken or sign languages, whether face-to-face, by telephone or via video.
In a conversation, each person responds to what has come before and shapes what will follow. Added meaning emerges as they hesitate, restart or refer back to earlier points. Words are only part of this exchange – tone, pace, pauses and non-verbal cues can all shape how an utterance is understood.
Imagine a doctor asking a patient if they have missed any of their treatment sessions. The patient gives a hesitant “no” – perhaps because they are embarrassed, unsure or genuinely cannot remember.
On the surface, this reply sounds simple enough, whether the patient says nie in Polish, hayır in Turkish or hapana in Swahili. But would an AI-powered translation device spot the subtle inference in the hesitation?
AI systems work best when conditions are relatively stable: speech is clear, speakers take turns, and people say exactly what they mean. But human interaction is rarely so tidy.
In contrast, a professional interpreter would almost certainly understand the full meaning and context of this answer. They would preserve the hesitation, flag any ambiguities, and allow doctor and patient to repair a possible misunderstanding before it has any serious consequences.
As researchers in the field of public service interpreting, we are therefore concerned that any increase in adoption of AI translation services is done with due consideration for the skills and sensitivities that could be lost in the process.
Automated speech translation can offer some practical advantages, including on speed and availability. A 2024 survey of more than 2,500 workers across UK health and social care, legal and emergency services and the police found that a third of them had used machine translation at work.
Such systems use a process in which speech recognition converts verbal communication to text, machine translation renders it in another language, then text-to-speech software produces spoken output in the listener’s tongue.
Yet the appeal of instant solutions can obscure the complexities of human interaction, and the potentially serious consequences for those involved if communication goes wrong. In an asylum interview or a Mental Health Act assessment, for example, a language-related error could significantly affect a person’s health, legal status or liberty.
One approach is to reserve automated speech translation for apparently straightforward interactions. However, even a routine exchange is rarely low risk in some public services: an appointment booking may reveal alarming symptoms; a housing enquiry may uncover domestic abuse; a casual conversation with a social worker may raise a safeguarding concern.
We therefore believe technology should be introduced according to the risks of the specific interaction, with human oversight and a plan for escalation if the level of risk changes.
At the same time, human involvement does not automatically guarantee quality. Good interpreting depends on qualified professionals, effective procurement and public-service staff who know how to work with interpreters. So any responsible approach to language access means investing in both professional expertise and the systems that support it.
AI speech translation is likely to become ever-more accurate, fluent and useful. It could support qualified interpreters and, when none is immediately available, provide a temporary fallback. Ruling out its use altogether is both unrealistic and undesirable.
The more constructive questions concern when and where it is appropriate; who should supervise its use; when a human interpreter is essential; and who should be held accountable when an AI system causes harm.
It is also important to be realistic about how these systems may perform amid growing linguistic diversity. Some languages, dialects and accents are much better represented in training and test data than others. Research has documented systematic inequalities in language-technology performance worldwide as well as disparities in speech-recognition error rates within a single language.
The risks in public services are therefore uneven. Output for under-represented languages and varieties may be less accurate – and these are often the same languages for which expert interpreters may be unavailable.
As society learns to live with AI, it is important to cultivate communicative environments where technology supports and operates under human oversight, rather than replacing human expertise.
However fluent technology becomes, communication is never simply the transfer of words. Meaning emerges as an interaction unfolds: through what people say, how they say it, what they leave unsaid – and, crucially, their ability to repair misunderstandings.
These are distinctly human capabilities. Any responsible use of AI should strengthen rather than displace them.
AI has long been discussed as a threat to jobs and livelihoods. But what’s the reality? In this series, we explore the impact it is already having on different occupations – and how people really feel about their AI assistants.
Lucas N Vieira receives funding from UK Research and Innovation. He is the author of Translate: Multilingual Access to Critical Services in the Age of AI (Cambridge University Press, May 2026).
Natalia Rodríguez Vicente does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.
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