AI ethics on Tuesday, 28 July 2026

CASCADE, Iowa -- Officials said three Cascade High School students are charged in connection with an incident in which artificial intelligence was used to generate nude images of students. A Dubuque County Attorney's Office press release i ... (https://incidentdatabase.ai/cite/1350#7601)

The U.S. Department of Transportation brought an automated bus to D.C. this week to showcase its work on self-driving vehicles, taking officials from around the country on a ride between agency headquarters at Navy Yard and Union Station. O ... (https://incidentdatabase.ai/cite/1347#7602)

SAN FRANCISCO (KGO) -- For a week now, neighbors in San Francisco's Mission District have shared their sadness and outrage over the death of KitKat, the neighborhood cat. The cat's owner says a Waymo ran him over. A memorial still marks th ... (https://incidentdatabase.ai/cite/1269#7603)

A cat known as the "mayor of 16th Street" was allegedly run over by a Waymo autonomous vehicle, according to the cat's owner, sparking grief around the Mission Dolores bodega where he roamed. KitKat, a feline fixture at Randa's Market, was ... (https://incidentdatabase.ai/cite/1269#7604)

A San Francisco community is in mourning after a beloved neighborhood store cat was allegedly hit and killed by a Waymo self-driving taxi. According to reports from CBS Bay Area, SFGate and the San Francisco Standard, a 9-year-old cat name ... (https://incidentdatabase.ai/cite/1269#7605)

Jeffrey Lucas, a longtime friend of KitKat, said the "funniest thing" he ever did with KitKat was "teach him Ukrainian." He taught the bodega cat two simple commands: De kit (Where's the cat?) and Kit tam (Cat's over there). Lucas recalled ... (https://incidentdatabase.ai/cite/1269#7606)

SAN FRANCISCO - Last year, Meta had to reckon with an ugly conclusion about its Chinese advertising customers: They were defrauding Facebook, Instagram and WhatsApp users worldwide. Though China's authoritarian government bans use of Meta ... (https://incidentdatabase.ai/cite/1268#7607)

Meta, the company behind Facebook, Instagram and WhatsApp, is under scrutiny after leaked internal documents revealed that it expected a significant portion of its 2024 revenue to come from ads linked to scams, fraud and banned products. Th ... (https://incidentdatabase.ai/cite/1268#7608)

Adam Raine's life hurtled toward tragedy soon after he began talking with ChatGPT about homework last fall. Their exchanges grew more consuming as the 16-year-old opened up to the chatbot about his suicidal thoughts, according to data anal ... (https://incidentdatabase.ai/cite/1192#7609)

This week, a rogue A.I. agent acted autonomously and conducted a cyberattack on the company Hugging Face. In the latest episode of “Hard Fork,” the hosts, Kevin Roose and Casey Newtown, discuss how the attack happened and why it matters.

Share price rally driven by strong product demand as well as decision to sit out AI spending race, amid wider tech sell-off Apple has become only the second company to pass the $5tn valuation mark, as it benefited from investors fleeing AI and semiconductor stocks amid a wider tech sell-off. The iPhone maker’s shares hit a session high ⁠of $342.89 on Tuesday, giving it a market ⁠capitalisation of $5.04tn (£3.78tn), then eased back down to $340.08 – around the $5tn mark. Continue reading...

Samsung and SK Hynix fall by more than 10% amid renewed fears over AI spending and Chinese competition Business live – latest updates The sell-off in AI stocks has intensified, driving South Korea’s stock market down to its lowest level in three months. Investors continued to ditch chip stocks on Tuesday, amid rising concerns about the huge amount of borrowing among AI companies to fund their datacentre expansion plans. Continue reading...

Jess Asato’s particulars of claim states Grok added explicit sexual material users had not asked for A Labour MP who is taking legal action against Elon Musk’s xAI company over fake sexualised images created by Grok says the AI tool was instructed to operate with “no restrictions on adult sexual content or offensive content”. Jess Asato’s lawyers published her particulars of claim in the case on Tuesday, which included details of publicly posted instructions that the claim says illustrate how Gr

CapuchinAI, a portable testing station equipped with a touch screen and facial recognition software, could help scientists study primate intelligence in the wild.

False testimonials are prohibited under Australian consumer law, writes policy professional Kat George, but they are also very hard to police Read more Australian customer service questions While looking at the website for NannyLane Australia, which bills itself as “the Uber for Nannies”, I noticed some glowing testimonials apparently written by happy parents who’d used their services. But a simple reverse Google image search of “James & Emily T” from Sydney led me to a stock image of a couple,

Like genies of folklore, AI agents take their instructions literally – to potentially disastrous effect. We must track their ability to do what we actually mean In July, Hugging Face, a company that hosts much of the world’s AI software and open-source AI models, was hacked. A malicious dataset had been used to run code on one of its servers. Whoever was behind it captured internal security credentials and moved through systems over a weekend, running thousands of actions from a swarm of tempora

The new breed of camera-equipped streetlights has the potential to fight crime and track down missing persons. Or will it just take Britain one step closer to a surveillance state? How would you feel if your neighbourhood lamp-posts could recognise your number plate, and also your face? Maybe you wouldn’t mind, given how long we’ve had automatic number plate recognition and CCTV. What about if that lamp-post could power itself through its own solar panels, and perhaps find another use for any ex

Lee, an engineer at Samsung’s semiconductor division, clocks out when his shift ends. He used to work longer hours, going the extra mile to excel at his projects. But lately, he’s been coming straight home to work on his job application for the chipmaker’s South Korean rival SK Hynix, sharing tips with his coworkers on…

The chipmaking giant is in talks with OpenAI to provide a $250 billion financial backstop for the project, which would be among the largest of the A.I. boom.

Analysis of 15 million real AI interactions finds most tasks at most jobs are unaffected.

Employees of OpenAI and Anthropic, as well as Google, Meta, Thinking Machines, Microsoft, Mistral, and other leading AI labs, have written a statement to the US government supporting a potential slowdown of sorts for frontier AI development - or at least a speed-up of global coordinated governance efforts. "Al could help create a dramatically better […]

It's earnings season, and investors got an unpleasant surprise from Google: an increase on its spending estimate, to as much as $205 billion - from the last quarter's projection of up to $190 billion. Even the lower end of Google's new projected range - $195 billion - is much more than the company had previously […]

AI is transforming Canadian health care, using datasets that underrepresent Black, Indigenous and racialized Canadians.

Last week illustrated why AI models pose a threat long before they are released

Perplexity has expanded its agentic Personal Computer tool to Windows, allowing computers running the world's most popular OS to be used as a locally run AI system. Like the Mac version that Perplexity launched in April, Personal Computer for Windows operates like a "general-purpose digital worker" that can access local files and apps to perform […]

In 2023, the Times sued OpenAI and Microsoft for copyright infringement. They’ve since spent more than $20 million on the case, and publisher A.G. Sulzberger has no plans to stop fighting it.

Anthropic and OpenAI employees are expected to give generously after their companies go public. “It’s going to be a wild ride,” says one nonprofit leader.

Hugging Face is being used to make nonconsensual deepfakes, and the popular open-source AI model repository is doing very little to prevent it. That's according to a new report published by the European nonprofit AI Forensics, which found that seven out of the top nine image editing models hosted by Hugging Face readily complied with […]

Researchers tested top image editing models on Hugging Face and found they could easily create explicit deepfakes—and 1,000 image editing prompts show how people use the software.

The Chinese AI startup’s massive new model is challenging OpenAI and Anthropic, fueling a debate over AI safety.

The Chinese AI startup’s massive new model is challenging OpenAI and Anthropic, fueling a debate over AI safety.

The decision arrives as the breakneck pace of data center construction has grid operators scrambling to generate power.

The directive comes as AI companies confront mounting copyright pressure.

The directive comes as AI companies confront mounting copyright pressure.

AI readiness isn’t about picking the right tools—it’s about the CEO leading the hard work of reshaping culture, pace, and people to build a more capable organization.

From the boardroom to the C-suite, AI governance should be on the front burner.

AI readiness isn’t about picking the right tools—it’s about the CEO leading the hard work of reshaping culture, pace, and people to build a more capable organization.

From the boardroom to the C-suite, AI governance should be on the front burner.

A wheeled bot that monitors air quality is joining robotic vacuums and scrubbers in Terminal B.

A wheeled bot that monitors air quality is joining robotic vacuums and scrubbers in Terminal B.

NewMod law firm Crosby is to provide ‘professional liability insurance for [their] agents, so that they can do autonomous legal work’, in what is an ...

Thrive Capital's Joshua Kushner and former Liberty Media boss Greg Maffei are involved in the controversial bid to buy a stake in a subsidiary of the non-profit that oversees the beloved World Cup soccer tournament.

In China, the AI boom that put actors and models out of work has found a new use for them. It is renting their faces. A growing set of platforms now pays people $15 to $700 to license their likeness for AI-generated content, Rest of World reported. Producers browse catalogues of faces by gender, age […] This story continues at The Next Web

Hollywood powerbroker Ari Emanuel rallied to the defense of his friend and business associate David Ellison, claiming that the state attorneys general trying to block Paramount’s Warner Bros. Discovery deal are threatening to “destroy” competition in the entertainment industry. Emanuel, who is CEO of TKO Group and former head of Endeavor, penned an op-ed published […]

A party-line vote in the Senate installed Jay Clayton as director of national intelligence, a job that has drawn increasing scrutiny during Donald Trump's second term as president.

The former SEC chairman will replace acting intelligence chief Bill Pulte, whose brief tenure oversaw repeated personnel cuts to the nation’s top spy office.

NEW YORK (AP) — A school district in a rural corner of upstate New York is hitting pause on plans to deploy an AI-powered, humanoid robot in the classroom after state education officials, teachers and local residents raised concerns, including the maker's ties to a company that produces hyper realistic sex bots. The Salamanca City...

Details have been released of an emergency call with hundreds of cyber-security experts after the ChatGPT hack of a tech company.

CNBC's Jim Cramer urged investors to take profits as stocks go parabolic, saying those explosive rallies often unravel just as quickly once momentum fades.

For a year, the story of Chinese AI has been simple. It is nearly as good as the American frontier, and it is effectively free. That second part may be about to change. Chinese developers could start charging cloud platforms commercial licensing fees to host their open-weight models, Goldman Sachs told the South China Morning […] This story continues at The Next Web

Another Day, Another Summer Bonus : Yet another firm is rewarding its associates with more money. The Biggest Sharks In Biglaw : But which law schools do all of these sharks come from? Find out here. Tell Us Your Bar Exam Horror Story: Poop, births, fires, tsunamis, ExamSoft -- we've heard it all, and we're ready for more. If Todd Blanche Won't Commit To His Own Sworn Testimony In Writing, What Is His Word Worth? Two GOP senators on the Judiciary Committee want to know with the vote looming Thur

NEW YORK (AP) — Elon Musk's social media company X, formerly known as Twitter, launched its own bank account-like product where users can send money to one another. The service, known as X Money, is not a new bank. X Money is using technology and banking services provided by Cross River Bank, and branding that...

CNBC's Jim Cramer said investors are rotating out of memory-chip winners and into companies with growth outside the data center buildout.

Willie Nelson has spoken out against the construction of data centers across America, releasing a statement encouraging citizens to fight the proliferation of facilities that “only destroy the environment around them.” The country legend published an open letter on social media describing how he grew up in Abbott, Texas, and that the community needs to […]

A new lawsuit accuses Tesla of overextending the safety operators overseeing its robotaxis.

Boeing’s contract to replace two aging Air Force One planes, a program that is now four years behind schedule, lost the defense contractor $280 million in the second quarter of 2026, according to its latest earnings report released on Tuesday. The company inked a contract with the U.S. government in President Trump’s first term to...

Andrew Ng helped give the AI industry its vocabulary, from “AI is the new electricity” to “agentic AI.” His new company bets against the phrase everyone else is using: that AI will take your job. Ng has founded LearnVector, an AI-native learning startup, and Coursera is backing it with $100m, first reported by Axios. The […] This story continues at The Next Web

You know, doing nothing *was* an option. The post The Dems Helping Donald Trump Load Up The Federal Bench appeared first on Above the Law .

HHS has removed Minor as the agency’s CIO online. The ex-Palantir executive began at the agency in February 2025. The post Clark Minor out as Health and Human Services’ IT chief appeared first on FedScoop .

National security agencies said the devices could create supply-chain vulnerabilities, threaten critical infrastructure and enable surveillance or remote manipulation.

Repurposing data for other means is risky, and governments should evaluate when consolidation is more harmful than good, a recent report said.

A thousand workers from OpenAI, Anthropic, Google, Meta and more have signed the letter.

With the threats from compounders and generics mostly contained, we can take a look at the latest piece of GLP-1 news. The post Selling The Skinny appeared first on Above the Law .

A host of Internet-exposed remote hardware management processors are subject to offline password-cracking attacks — and adversaries have taken note.

CATL aims to become market leader for battery energy storage systems

Advanced robots and power inverters made overseas pose risks that could include blackouts and espionage on Americans, U.S. officials said.

Back-to-school shopping usually means backpacks, notebooks and dorm-room basics. But for many families, a phone plan — or a first phone — has become just as essential. Boost Mobile is leaning into that rite of passage with a slate of back-to-school tech deals aimed at parents looking to get their kids connected without committing to a traditional […]

Gorsuch says his friendship with Sotomayor proves profound disagreement doesn't require personal animosity. The post Neil Gorsuch Says He Trusts Sonia Sotomayor’s Motives, Even If He Rejects Her Legal Views appeared first on Above the Law .

OpenAI's recent AI agent sandbox escape proves traditional security principles matter more than ever: limit access, isolate execution, log everything.

Task Force Talon Synapse is slated to soon be fully operational, but some observers question its ultimate value. The post U.S. military forms first bilateral AI task force with United Arab Emirates appeared first on DefenseScoop .

Downs continue to oversee SD's Digital Operations team, while taking what the company called "strategic ownership, governance, and long-term operational direction" across its core platform infrastructure. Source

Tech giant gains due to its lack of huge spending on AI and as investors seek havens from sell-off in chip sector

“AI automates tasks away, but it doesn’t necessarily eliminate jobs,” Huang said.

Researchers propose focusing on identification of certain cognitive elements in LLMs that indicate when AI systems may take an unwanted action.

The jockeying between Apple and Nvidia reflects a debate about the future of AI that has preoccupied investors this summer.

What do we need to know about agentic AI?

The rulings expanded FCC data privacy rules and made it easier for the agency to issue huge fines, the group said

This week during an interview with Bloomberg, Jensen Huang made quite the prediction. The Nvidia CEO said the semiconductor industry The post Jensen Huang says AI agents could drive a 5-10x computing boom: “100 billion agents and billions of robots” appeared first on The New Stack .

It’s a chip panic that “appears to be indiscriminate,” analysts say.

Alphabet's free cash flow has turned negative, and the company lifted its capital spending forecast. Slower-growing cloud rivals report this week.

Shocking! The post Trump Fails To File Promised Birthright Citizenship Rehearing Before Deadline appeared first on Above the Law .

Conquest Planning Inc. (“Conquest”), the AI-powered technology platform modernizing financial advice delivery across the full wealth spectrum, and Shaping Wealth, the leading provider of behavioral science-based learning and engagement solutions for the wealth management industry, today announced a new integration that brings Lydia, Shaping Wealth’s AI-powered behavioral intelligence agent, directly into the Conquest experience.

The release of the Chinese AI model Kimi K3 was a flashpoint in the AI world, sharpening the debate over whether the most capable models should be closely held by individual companies, usually U.S. tech firms, or freely and transparently distributed in the tradition of open-source software. Not only did the high-performing Kimi K3 challenge the cherished Silicon Valley notion that Western AI labs still lead their Chinese counterparts in large language models (though likely by only a hair), but i

The general counsel who told the Senate his role was 'limited' has started publishing a target list. The post DHS General Counsel Names Four Federal Judges ‘Worst Of The Worst’ As Threats Against Judiciary Hit 564 appeared first on Above the Law .

A cyberattack of undetermined origin disrupted water treatment plants in at least 30 communities in Minnesota, according to the state's technology bureau.

“While the charge is disappointing, we recognize how critical schedule performance is to our customer and we are investing accordingly to maintain our commitment to deliver the airplane in 2028,” CEO Kelly Ortberg said.

Juniper Square, the operations partner to more than 2,300 private markets GPs, today announced its new Admin Oversight Agent, Fay. In June, Juniper Square introduced Headless GPX and opened its fund operating system to any AI a GP chooses to use.

When the leaders of a new elementary school applied for a four-digit public school code from the Colorado Department of Education last summer, they didn’t mention a key detail: The school would be religious. Instead, they said Riverstone Academy would offer traditional academics and trade-themed electives. But education department officials soon learned that the 30-student […]

The proposed legislation will authorize $10 million annually to address cyber threats in K-12 schools.

Sam Altman’s latest appearance on Patrick O’Shaughnessy’s Invest Like the Best podcast covered everything from AGI and robotics to the The post Sam Altman on model distillation: “This is not in my top ten list of worries” appeared first on The New Stack .

Visa is set to cut around 2600 jobs - seven per cent of its workforce - with technology and product roles taking the brunt of the hit as the payments giant reconfigures its operations for the AI era.

Two Republican senators want the slush fund killed in writing. Blanche testified it was dead, so writing it down shouldn't be hard. And yet... The post Todd Blanche’s Confirmation Is Being Held Up By… Todd Blanche appeared first on Above the Law .

Buoyed by the shift of sports programming to streaming, ad spend on digital video continues to climb, but that growth comes with greater scrutiny around transparency and business outcomes. Case in point: A major beverage company is conducting an independent audit of its digital media ads — including CTV and online video — that ran […]

“It sounds good on paper,” a former senior defense official told Breaking Defense. “My biggest questions revolve around classified information sharing.”

Flagright, the AI operating system for financial crime compliance, today announced that Tipalti has partnered with Flagright as one of the tools supporting its compliance infrastructure.

In honor of Shark Week, here’s a deep dive into the sources of associates for five top law firms. The post Where Biglaw Gets Its Lawyers: An ATL Infographic appeared first on Above the Law .

Water disputes can directly drive conflict, but more often, water scarcity acts as a catalyst — one that, combined with other pressures, raises the risk of conflict. This is nothing new; water has shaped human conflict for millennia. What’s changed is the accumulation of stress, as climate change, population growth, human migration, and the intensive demands of agriculture and industry are converging to strain water systems in ways that threaten to exacerbate instability. However, examples of go

A corporate fad of “tokenmaxxing” on artificial intelligence technology is hitting its limits as workplaces throwing AI at everything are seeing the costs rise without a similar spike in productivity . What started as tech industry-fueled springtime hype over squeezing as much AI-generated work as possible out of products like OpenAI’s ChatGPT and Anthropic’s Claude has shifted to a summertime backlash. “It’s very easy to create something you don’t need with AI,” said Vincent Gusdorf, head of AI

Commerce Undersecretary William Kimmitt was at the Farnborough Airshow to develop a list of “high priority” potential sales, he told Breaking Defense.

Con el boom de los humanoides , parece que los robots cuadrúpedos han pasado a un segundo plano, pero Unitree acaba de demostrar que aún pueden dejarnos boquiabiertos. Durante este fin de semana se ha viralizado un vídeo de su último invento: un perro robot con ruedas atravesando terrenos por los que ningún otro robot podría moverse, y todo a una velocidad brutal.  Se llama Unitree As2-W y lo que lo distingue de otros robots cuadrúpedos es que sus patas tienen ruedas. Esto le permite supera

[Sponsored] Join us for this webinar as the group will dig into what the new global data reveals about why contract ownership remains Legal's most expensive blind spot. The post Webinar: Why Contract Ownership Is Your Most Expensive Blind Spot appeared first on Above the Law .

Over the last decade, including a stint on OpenAI’s board, I saw the open secret among AI developers: this kind of hack wasn’t just possible, but expected.

Ein Brüsseler Leitfaden konkretisiert die Cyberresilienz-Verordnung. Hersteller und Open-Source-Projekte erhalten Rechtsgewissheit vor Start der Meldepflichten.

CAF Bank suspends internet banking after identifying attempted fraud

The bureau is wary of adversaries getting their hands on tools that can uncover system vulnerabilities and enhance other capabilities. The post FBI sees Anthropic’s Mythos as a law enforcement challenge appeared first on FedScoop .

Microsoft patched a high-severity vulnerability earlier this month that allows a threat actor to escalate privileges and compromise an AD environment.

As New Hampshire public schools grapple with funding challenges, declining enrollments, and increasing fiscal scrutiny from voters, some metrics suggest that the schools continue to perform well nationally. On Monday, Gov. Kelly Ayotte touted the latest analysis; a study by WalletHub that used a mix of proficiency scores, graduation rates, advanced placement course takeup, attendance, […]

It's a grand tradition of chaos, and we want to hear all about it. The post The Bar Exam Is Here, Which Means Something Is About To Go Horribly Wrong appeared first on Above the Law .

The Investing Club holds its "Morning Meeting" every weekday at 10:20 a.m. ET.

For many, this summer is a warning that Europe is unprepared for the new climate reality.

An Xbox executive said yesterday's outage was due to "a licensing service that sits outside of Xbox."

As AI shifts from automation to orchestration, in-house legal teams are redesigning workflows, cutting external spend, and redefining their role, moving from advisors to builders of the systems that now […] The post Orange Rag Insights: From advisors to builders – How AI is remaking the in-house lawyer appeared first on Legal IT Insider .

An independent review found the department was deficient in seven areas. The agency said many of the recommended actions are already underway. The post VA fails watchdog FISMA audit on IT security, but agency disagrees appeared first on FedScoop .

Staff from controversial tech company have been given ‘unlimited access’ to identifiable patient data

Biglaw keeps waiting while other firms keep writing checks. The post Cha-Ching: Another Firm Joins The Bonus Party appeared first on Above the Law .

Corpay, a global leader in corporate payments, today announced Agent Card, a new capability that enables secure virtual card creation for AI-driven commerce workflows.

Fenergo, the leading provider of digital solutions for Know Your Customer (KYC), Anti-Money Laundering (AML) and client lifecycle management (CLM), today announced the launch of Fen-AI, its agentic AI orchestration platform for financial institutions.

Fanning also gave The Break Out his take on the state of foreign military sales and the room for reform.

The industry's response to the OpenAI incident reveals a growing divide over the future of AI safety.

Clio Work went live in Canada on July 23, enabled by more than 470,000 Canadian cases drawn from Jurisage. The post Bringing Home The Bacon: Clio Launches ‘Clio Work’ AI In Its Home Country Of Canada appeared first on Above the Law .

Microsoft bringt mit MAI-Cyber-1-Flash ein Security-Modell auf den Markt. Es soll nur halb so viel kosten wie Microsofts bisherige Security-Modellkombination.

An employee's email account had been compromised, allowing unauthorized access to "certain data," Bank of Baroda reported.

On the heels of a $1.5 billion copyright infringement ruling against Anthropic, OpenAI has adjusted ChatGPT’s programming to refuse requests to mimic the style of well-known authors. While the chatbot used to happily write in the voice of professional writers, attempts to convince it to do so now are met with a polite refusal and an suggested alternative. Fast Company , for instance, asked ChatGPT to write a story about a family in the Depression in the voice of John Steinbeck. The chatbot repli

Chronic absenteeism is playing a major role in students failing to reach pre-pandemic academic levels, a new report from NWEA shows. The report, issued last week, shows that the academic progress of students in districts with the highest rates of chronic absenteeism are more likely to lag behind districts that haven’t experienced drastic rises in […]

Knapp 2600 Mitarbeiter des Fintech-Unternehmens müssen laut CEO Ryan McInerney gehen.

The Trump administration says 60% of Americans now have access to medical records through an app of their choice because of its health technology initiative.

Am Bodensee wird ein Roboter getestet, der für den Einsatz im Obstanbau entwickelt wurde. Er soll künftig bei der Apfelernte eingesetzt werden.

“I think we’ve done a pretty good job of identifying, amongst commanders, where we’re going to take risk or how we manage the risks as we prioritize… [efforts] in the CENTCOM region right now and what are those things that you know we are able to absorb as commanders elsewhere in the Air Force enterprise,” said PACAF Commander Gen. Kevin Schneider.

Rising expenditure from OpenAI, Anthropic, Google and Microsoft reflects growing battle over federal policy Von Michael Taffe ( Wirtschaft , KI )

CORAS is a FedRAMP High-certified agentic-AI “decision maker” that has already been authorized for use at the Department of Defense. The post GSA inks agentic AI OneGov deal with CORAS appeared first on FedScoop .

HYBE is reportedly in talks to transfer Supertone's voice-conversion and noise-removal tools, Shift, Clear and Air, to an outside buyer. Source

Professionals are burning through tokens, but smart business leaders are finding ways to balance costs and value creation.

ChangXin Memory Technologies (CXMT) and Zhipu AI have not only seen their share prices skyrocket, but they have also handed a windfall to their common backer: Alibaba Group Holding. Before the listing of China’s memory-chip giant on Monday, Alibaba owned nearly 5 per cent of CXMT, making it the chipmaker’s largest industrial shareholder, according to the prospectus. Alibaba has invested about 7.6 billion yuan in CXMT since 2021. Based on Tuesday’s closing market capitalisation of about 3.14...

Keeping phones out of landfills and doing useful things is a good thing.

In the face of growing air and missile threats in the Pacific, robust radar coverage and command networks will be critical to US and Japanese defense objectives, Tom Karako writes.

The Monetary Authority of Singapore (MAS) and the Association of Banks in Singapore (ABS) today announced the establishment of the AI-Driven Cyber and Technology Risk Taskforce (ACT), an industry-wide initiative to strengthen collective cyber and technology resilience in response to the emerging risks posed by frontier artificial intelligence (AI) models.

Microsoft a présenté le 27 juillet 2026 une architecture de sécurité entièrement bâtie sur l'IA agentique, avec une préversion publique annoncée pour le 3 août 2026.

Nvidia is pouring what it calls a "substantial" sum into Safe Superintelligence (SSI), the AI lab run by Ilya Sutskever, OpenAI's former chief scientist. The article Nvidia invests in Ilya Sutskever's AI lab, shifting SSI away from Google chips appeared first on The Decoder .

* Corporate pardons were never a thing. Trump has issued nine. [ The New Republic ] * Freshfields losing European partners worried about U.S. growth. [ Bloomberg Law News ] * Comey seeks to 86 the 8647 suit. [ NPR ] * Trump heading to the Supreme Court with his effort to use Post Office to block voting by mail in Democratic states. [ Reuters ] * "Abruptly changes" is never an encouraging description of a law school dean switch. [ Penn Live ] * Blanche confirmation vote held over again as holdout

Uptime Institute today released the findings of its 16th Annual Global Data Center Survey, the most comprehensive study of the digital infrastructure sector. The 2026 results reveal an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams.

AI agents can impress in a demo and still fumble in production. Diagrid’s Catalyst 2.0 aims to make them more The post Diagrid gives failed AI agents a way to resume appeared first on The New Stack .

After eight years of building a no-code automation platform, Tines launched 3B Tuesday, a new platform that uses AI to The post “There is a sell-by date on low-code, no-code”: What Tines thinks comes next appeared first on The New Stack .

As the Trump administration pursues an aggressive deregulatory agenda, concerns are mounting that artificial intelligence could make agency decisions harder to explain and defend.

Rimini Street, Inc. (Nasdaq: RMNI), the Software Support and Agentic AI ERP Company™ and the leading third-party support provider for Oracle, SAP and VMware software, today announced that AUTOBACS SEVEN Co., Ltd. celebrates its 10-year partnership with Rimini Street, marking a decade of stable core operations and reinvestment in innovation.

Clive Higgins told Breaking Defense the firm would likely pitch its experience in sensors and EW, but also saw an opening for drones developed with a Turkish partner.

There’s a long-held misconception that students’ opportunities are constrained by the size of their town. In many people’s minds, rural career and technical education and career-connected learning are synonymous with agriculture and manufacturing, while college prep is limited to a path from the graduation stage to the nearest state school. Unfortunately, this mentality can be […]

Virgin Media O2 says the rules stifle innovation, limit network investment and prevent AI development.

Here are five key things investors need to know to start the trading day.

Anthropic CEO Dario Amodei is once again warning about the risks of open AI models while insisting he has never called for a ban. He argues that authoritarian states like China could overtake the US and that open models could be misused for biological or cyberattacks. Critics say he's mostly trying to protect his own business from cheaper competition. The article Anthropic CEO Amodei doubles down on open-weight risk stance while insisting he never called for a ban appeared first on The Decoder .

On an incredibly detailed new map , you can look through the world’s 120,000-plus power plants, from solar and wind farms to battery storage and coal and gas plants, along with nearly 3 million miles of transmission lines and hundreds of thousands of substations. Other layers include gas pipelines, flood risk, and power-hungry data centers. The map was built by Brian Bartholomew, an energy consultant who created it as part of a side project called OpenGridWorks , which provides publicly accessib

Die Nutzung von KI-Agenten direkt auf dem Rechner kann Gefahren mit sich bringen. Das zeigt eine soeben entdecktes Sicherheitsloch in Claude Cowork für den Mac.

Cape Verde’s sudden global visibility mirrors a bigger problem: Francophone African startups are still fighting for investor attention.

Airtel Africa has finally settled on where it wants to take one of Africa’s biggest fintech businesses public. The bigger question is whether that market can still deliver what the company is looking for.

Meta has confirmed it will spend billions on a new AI data center in Texas just months after raising Quest prices due to an AI-driven memory shortage.

Trulioo, a global risk intelligence platform, today announced the UBO Discovery Agent, the newest layer in Trulioo’s UBO Discovery capability inside its business risk and Know Your Business (KYB) verification workflow.

Wie ich eine KI dazu bringe, guten Code zu schreiben - ganz praktisch. Ein Erfahrungsbericht von Felix Knorr ( KI , Softwareentwicklung )

Vodacom, the University of Johannesburg and Amazon Web Services join forces to address SA’s growing demand for job-ready AI and data science skills.

Ben Greene discusses how software engineers can adapt and thrive in an era of rapid AI code automation. Drawing on his startup experience, he explains key mindsets like starting simple, maintaining code comprehension, attacking hard problems first, and focusing on customer impact. He shares why human empathy, agency, and practical problem-solving remain irreplaceable when code is automated. By Ben Greene

Absa Bank Kenya, one of the country’s largest commercial banks, said a KES 4 billion ($31 million) technology investment helped automate 71% of its processes in 2025.

Nearly 6 million children in California would be eligible for a scholarship under the new federal tax credit for education, more than in any other state, new data shows. But unlike other states with millions of eligible students, like Texas, Florida and New York, California hasn’t opted into the new Treasury Department program, and so […]

The fintech firm focuses on extending the reach of its banking-grade voucher payment platform across multiple industries.

Five of the Congress members serve on committees whose work touches SpaceX's federal contracts, defense programs, AI, telecommunications or securities markets.

To make sense of some characteristics that species exhibit from birth, you have to turn to an old discredited theory known as Lamarckism.

The conflict will eventually subside. But without action, the vulnerabilities it has exposed will not, write Michael Adu Okyere, Brian Mukhaya, and David W. Yellen.

Was macht man, wenn man Musik am Lagerfeuer spielen m�chte, aber kein Instrument beherrscht? Das Cyber-G Pocket ist eine spa�ige M�glichkeit. Ein Test von Tobias K�ltzsch ( Musikinstrument , Musik )

Inside the slick new Terminal B at New York’s LaGuardia Airport, a headless robotic “dog” is beginning to patrol the floors. As bemused airport travelers watch from close by, the four-wheeled device rolls around baggage claim, where it’s been deployed for a demonstration. Its job: sniffing. Well, sort of. The robot is armed with air quality detectors that the airport team says help monitor the terminal for pollutants.  This robot, along with two others, constitutes a fledgling automated fle

The post This MAGA Influencer Runs a Charity to Teach Kids Civics. Much of the Money Goes to Him Instead. appeared first on ProPublica .

Central bank in city-state says AI models and quantum computing pose cyber security threats

GoTyme Bank migrates customers to its new app, as it discontinues its legacy digital banking platforms as part of a new strategy.

NEC Africa has expanded its cyber security portfolio through a strategic partnership with German cryptography specialist Utimaco.

Exponant and Syskit are helping organisations gain greater visibility, stronger governance and simplified Microsoft 365 management.

If you're a college student, Spotify has an exclusive bundle that can save you cash on music and streaming. Here's how to get it.

Microsoft AI a présenté le 27 juillet 2026 son premier modèle dédié à la cybersécurité. Intégré dans son architecture, l’entreprise annonce battre tous les modèles actuels dans ce domaine, y compris Mythos d’Anthropic, mais attention à ce qui est réellement comparé. Hier soir, Microsoft a annoncé officiellement MAI-Cyber-1-Flash. Il s’agit du tout premier LLM de […]

Sometime in June of 2026, without ceremony, human beings became a minority on the internet they built. Cloudflare, which manages traffic for millions of websites, reported that bots now generate 57.5% of web page requests. Cloudflare CEO Matthew Prince had predicted in March that the crossover wouldn’t happen until the end of 2027. It arrived more than a year early. Global defense and technology leader Thales, in its annual “ Bad Bot Report ,” argues that machines became the majority back in 202

Der KI-Cyberangriff von OpenAI hat Folgen: Der Hugging-Face-CEO fordert nun radikale Transparenz sowie eine Investition in die Absicherung seiner Plattform. ( KI , Cyberwar )

Editor’s note: This is the sixth article in a limited series celebrating American defense technologies born from wartime and their effects on broader national security, politics, and society. This series will run for several weeks to commemorate America’s 250th anniversary, and winners will be selected by a reader vote undertaken through our newsletter later this summer. Prior installments can be found at the Arsenal of Innovation page.The impact of chance and poor logistics on warfare is especi

The wealth management industry is entering a decisive new phase. For years, firms invested heavily i...

Stop separating training from the workplace. Scarce IT skills should be built within the environments that need them.

The Bombay High Court will hear Gadkari's plea seeking Rs 11 crore in damages and sweeping takedown orders against AI-generated content. The post Why has Nitin Gadkari sued Meta, X and Google over AI deepfakes? appeared first on MEDIANAMA .

In the speech announcing his invasion of Ukraine on Feb. 24, 2022, Vladimir Putin took only minutes to arrive at the original sin in his catalogue of Western crimes. Before Iraq, before Libya, before Syria, came Belgrade: “First a bloody military operation was waged against Belgrade, without the U.N. Security Council’s sanction but with combat aircraft and missiles used in the heart of Europe.” The placement was not incidental, as Putin was telling Serbs that Russia’s war in Ukraine and NATO’s b

AWS released a public preview of the GuardDuty investigation agent, which correlates findings, 90-day activity logs, and resource topologies into structured reports with risk ratings, confidence scores, and MITRE ATT&CK classification. It is reachable through the AWS MCP Server, so investigations can run from agentic tooling. Preview quotas cap usage at 10 investigations per account per day. By Steef-Jan Wiggers

Anthropic co-founder and CEO Dario Amodei is urging Washington to tighten chip export bans and clamp down on Chinese “distillation”, framing it as critical for preserving the US lead in artificial intelligence. In a blog post on Monday, Amodei called a chip ban “the most efficient and direct way” of preventing Beijing from building frontier AI models for military use and domestic surveillance, which he said was his primary concern. The US “should not sell powerful chips or chipmaking equipment..

The Disappearing Student Safety Net Joshua.Bay Tue, 07/28/2026 - 03:00 AM New analysis from the Hope Center found that even though more colleges are offering aid for emergencies, awareness gaps and limited funding mean fewer students are receiving support. Byline(s) Joshua Bay

DOJ Sues Colorado Over In-State Tuition for Undocumented Students Johanna Alonso Tue, 07/28/2026 - 03:00 AM Byline(s) Johanna Alonso

Compton College Plans to Tie Basic Needs to Academic Milestones. Will It Work? Sara Weissman Tue, 07/28/2026 - 03:00 AM Starting in fall 2027, students need to meet a set of academic requirements to get free meals and other supports. College leaders say the move will increase completion rates. But basic needs experts are worried. Byline(s) Sara Weissman

How Will New Student Visa Rules Impact Athletics? Johanna Alonso Tue, 07/28/2026 - 03:00 AM NCAA policy allows athletes to compete for five seasons, but new federal rules limit international students to just four years in the U.S., cutting off collegiate play for some. Byline(s) Johanna Alonso

Stop Telling Students Computer Science Is Dying Elizabeth Redden Tue, 07/28/2026 - 03:00 AM The data says otherwise. Byline(s) Christine Julien

Companies must adopt a layered defence strategy that combines people, processes and technology, says Peter Clarke, founder and CEO of LanDynamix.

As IOT deployments expand across industries and environments, enterprises need a more flexible way to connect devices.

Sovereign cloud is about preserving control, reducing vendor dependency and ensuring critical systems can adapt when regulation or risks change.

Smart IT asset tracking helps businesses maximise the value of their IT investments while reducing risk, says Valene Nagiah, head of V-Track.

Armata’s summit provides organisations with the insights they need to rebuild trust and ensure they can adapt to threats and prioritise resilient security.

The 12-month programme combines classroom and workplace training to equip youth with telecoms infrastructure skills.

Zendaya stunned the red carpet at the “Spider-Man: Brand New Day” Los Angeles premiere in a black satin Ashi Studio corset with a sweeping architectural train, putting an exclamation point on a press tour that the young star used as her personal runway. “It’s kind of an abstract way to present the spider,” Law Roach, […]

Two job postings on its careers page suggest OpenAI wants third parties, not just its own sellers, to sell its inventory.

One of the premier private lenders on Wall Street has held talks to acquire one of the oldest and most profitable private equity firms

Communities fear they will squeeze access to electricity and water, spoil rural areas and boost tech giant profits with limited local job creation

Trading on South Korea's Kospi index was paused temporarily on Tuesday morning after sliding by 8%.

SK Hynix and Samsung shares slide and trading halt triggered on South Korea’s Kospi

Chinese artificial intelligence developers could start charging cloud platforms commercial licensing fees to host their open-weight models, according to the head of Asia internet research at Goldman Sachs, as firms look to capture more revenue from their soaring global use. The assessment comes as Chinese AI models – such as Moonshot AI’s Kimi K3 and Zhipu AI’s GLM-5.2 – have reached performance levels just a fraction behind top US rivals. However, because Chinese developers typically release...

The 60-day correlation between the Kospi and Nasdaq 100 recently climbed to about 0.50, its highest level since 2021, according to data provided by Rayliant.

Attackers used Hermes, an autonomous open source tool, in unrestricted "YOLO mode" to conduct espionage against Thailand's Ministry of Finance.

A federal judge on Monday halted a prediction market ban in Minnesota days before it was set to roll out. District Judge Katherine Menendez wrote that the Trump administration, Kalshi and Polymarket are “likely to succeed on the merits” in the case arguing that the state ban is pre-empted by federal law. “Specifically, it appears...

A high school student creates an online class for middle schoolers — and gains perspective on teaching.

AI is shrinking crews and production times while opening film jobs to workers trained in fields far beyond cinema.

A new field report shows how scientists use AI coding agents to modernize scientific computing, accelerating software development and discovery in genomics and beyond.

We’re announcing even more new capabilities in Managed Agents in Gemini API so developers can build reliable, production-ready agents.

For victims of targeted, sexualized attacks, searching for redress is not easy: they are blamed for posting pictures of them online, accused of overreacting by the police, and followed for life with the consequences of losing the control over their own body and image.

The implementation timeline of the EU AI Act has been significantly modified through the recently adopted AI Omnibus, which pushes compliance with the obligations for high-risk AI systems to December 2027 (Annex III) and August 2028 (Annex I), from the initial date of 2 August 2026. Changes of the AI Act include, among others, the […]

The concept of “surveillance pricing” is just one part of a much larger problem and business model: corporations maximizing their profits by invading our privacy. The all-too-common business model is to systematically harvest, collate, and store as much of our personal data as possible, and then monetize it through use and sale. When it comes to surveillance pricing, that looks like corporations offering the same product to two different people at two different prices, based on harvested persona

Recent reports have raised alarm about the use of PatronScan, an ID-checking and face-scanning system, at multiple LGBTQ+ bars in San Francisco’s Castro neighborhood. Much of the attention has focused on reports that the system photographs patrons as they enter venues and questions about whether those images are used for facial recognition. A broader privacy concern also deserves scrutiny. For years, PatronScan has marketed itself not just as an ID-verification tool, but as a system that allows

We’re aware a Modal customer published an unauthenticated endpoint that allowed ​anyone on the internet to use ​their ⁠sandboxes for code execution. This was used by the rogue agent. Modal’s ⁠platform ​or isolation were not ​compromised in anyway. — Akshat Bubna , Modal's CTO, talking to Reuters about this incident Tags: ai-security-research , openai , sandboxing , security , openai-hugging-face-incident

Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident Hugging Face just released this extremely detailed technical description of OpenAI's recent accidental cyberattack against their infrastructure . This attack was very sophisticated, and the resulting document doubles as a crash-course in modern adversarial security approaches. We're still waiting for more details from OpenAI on how their agent broke out of its sandbox. The package proxy that it found a zero

As a discerning AI investor who values style and substance, Sarah Guo knows this season’s standout accessory isn’t the latest designer purse — but what’s inside it. In a recent video, Guo, founder of AI-native venture capital firm Conviction and co-host of the AI podcast No Priors, highlighted how the NVIDIA Jetson platform for edge […]

Governments are switching, but I’m not sure it makes a difference : …some municipalities, including Denver, Colorado, are ditching their Flock arrays. But keep in mind that if they’re only switching from Flock to another brand of license-plate readers, like Axon, it’s like a gambling addict trying to kick the habit by switching from FanDuel to DraftKings. […] Despite what you may read on the Flock website, Axon cameras are pretty effective when it comes to hoovering up personal details that can

Today's links Discernment: How can you fact-check AI when you're asking it to teach you something you don't understand? Hey look at this: Delights to delectate. Object permanence: How to help with computers; Batman equation; Fuck and the law; NC's racist voting law; Pregancy app is full of spyware; Stiglitz v Apple's "tax fraud"; Accelerometer fingerprinting; Sacklers v bankruptcy; Boss-politics antitrust. Upcoming appearances: Edinburgh, Sydney, Melbourne, Brighton, London, South Bend. Recent a

Perhaps due to the notable impact of climate change on the ongoing summer, the delivery on C-67/25 by the Court of Justice has gone relatively unnoticed hitherto. The brevity of the judgment conflicts with the thunderous effects it may unleash, which have potential to open a definitive breach in the Union’s constitutional acquis. Noteworthily, this rupture is being perpetrated in alleged defence of Art. 2 TEU values: the lynchpin of the Union as a “militant” democracy is being deployed on the ex

and where productivity growth will really come from

As countries compete for technological leadership, the ability to anticipate workforce constraints may prove just as important as anticipating geopolitical ones. (Carlos Osorio/REUTERS) In 2021, ...

ANA is issuing final interpretive rules, general statements of policy, and rules of agency organization, procedure, or practice relating to the following Fiscal Year (FY) 2026 Notices of Funding Opportunity (NOFOs): Economic Advancement Grants for Local Empowerment (EAGLE), AI3 Action Institute--Artificial Intelligence for American Indians (AI3 Action Institute), and the National Center for Native Training and Technical Assistance (NCNTTA).

Samoa's strong post-pandemic recovery is giving way to subdued growth as weaker domestic demand is compounded by adverse external shocks. Higher global energy prices, elevated external risks, and ...

To alert the audit community to changes in professional standards, we periodically issue Professional Standards Updates (PSU). These updates highlight the effective dates of recently issued standards and guidance related to engagements conducted in accordance with Government Auditing Standards. PSUs contain summary information only, and those affected by a change should refer to the respective standard or guidance for details.

What GAO Found The unique needs of mothers and young children during disasters include appropriate sheltering, feeding and care supplies, medical and mental health support, and other services, according to relevant literature and disaster service providers from selected local, state, and nonprofit organizations. For example, large shelters may not be the best option for families with infants. Mothers also often need diapers, baby food, and infant formula. Service providers from 12 local, state,

I condemn the killing of Alejandro Leyva Aguilar and call for a thorough investigation to bring the perpetrators to justice. I reiterate my call to the authorities to do everything within their powers ...

Psychometric calibration for educational tests typically requires costly human response data. Large language models (LLMs) simulated examinees offer a promising route to early calibration, but their responses are too accurate and too uniform. We propose Cognitive Diagnostic Profiling (CDP), a zero-shot framework that prompts LLMs to simulate plausible examinees with diverse cognitive profiles: binary attribute-mastery patterns are rendered as natural-language profiles and sampled under an uninfo

Multi-Agent Debate (MAD) is a promising paradigm for improving the accuracy and robustness of Large Language Model (LLM)-based agentic systems. It enables multiple agents to exchange arguments, critique each other's outputs, and iteratively converge towards a solution. However, research remains fragmented, with inconsistent terminology and no rigorous synthesis of MAD design dimensions. We present a systematic literature review characterizing 141 primary studies on MAD. We derive a three-dimensi

A decentralized autonomous organization (DAO) is a governance entity that allows its stakeholders to manage blockchain-based protocols through smart contracts. The DAO explicitly specifies how stakeholders make and enforce decisions concerning a protocol's operation in a smart contract, aptly referred to as its governance contract. The design of this governance contract, therefore, has far-reaching implications for the security (trust) and privacy (transparency) of the smart contracts managed by

An AI benchmark result rarely reaches a consequential claim in one step. Evaluators generalize it to further cases, interpret it as evidence of capability, extrapolate it to new tasks, transport it to another system or site, and combine it with assumptions about human review and downstream consequences. Validity-centred approaches require evidence for each claim. This paper identifies a further epistemic problem: warranted links don't automatically make a warranted chain. The target of one study

Embodied intelligence integrates learned perception and decision making with real-time computation, control, and physical interaction. Because failures can cause immediate physical or operational harm, task completion alone does not establish trustworthiness. We define trustworthy embodied intelligence as the sustained capacity to execute specified tasks reliably under environmental and system variation while maintaining risk within acceptable bounds. We term this objective sustained safe succes

Observed standardized test scores are the result of an endogenous process: students strategically allocate effort across multiple retake attempts to improve their outcomes. Because students differ in their ability to make these investments, the interaction between applicant strategy and institutional scoring rules---such as the widely used Single-Sitting and Superscoring policies---can disparately distort observed scores. We develop a strategic framework where students allocate effort in respons

Ambivalence and hesitancy (A/H) are conflicting affective states that precede the delay or abandonment of health behaviour change. Recognition of A/H at the video level is difficult, since the signal arises from disagreement across and within facial, vocal, linguistic, and bodily modalities, and manifests differently across individuals. The proposed PRISM-AH (Predictive Reasoning over Interacting Streams for Multimodal Ambivalence/Hesitancy Recognition), is a framework that treats A/H as a multi

Ambivalence and hesitancy (A/H) are conflicting affective states that precede the delay or abandonment of health behaviour change. Recognition of A/H at the video level is difficult, since the signal arises from disagreement across and within facial, vocal, linguistic, and bodily modalities, and manifests differently across individuals. The proposed PRISM-AH (Predictive Reasoning over Interacting Streams for Multimodal Ambivalence/Hesitancy Recognition), is a framework that treats A/H as a multi

Question answering (QA) over irregular clinical time series (ICTS) plays a pivotal role in a wide range of healthcare applications. Although recent multimodal time-series large language models (LLMs) have shown considerable promise in general-purpose time-series QA, they remain poorly equipped to model the sparsity, asynchrony, and irregular sampling patterns of clinical observations. To fill this gap, we propose ClinPRISM, a cost-effective multimodal LLM reasoning framework for question answeri

Vision-Language-Action (VLA) models have shown strong potential for general robot manipulation, but most existing models rely on 2D visual-language backbones and lack fine-grained 3D understanding of target objects, especially under occlusion, pose variation, scale changes, and precise spatial interaction. We propose an object-centric 3D representation alignment framework built upon $π_0$, using SAM3D as a frozen 3D teacher to provide target-object 3D priors during training. Specifically, we loc

Annotation is among the most demanding visualization tasks to automate, as it simultaneously requires correctly navigating visual, semantic, and stylistic constraints. Failure to meet any of these conditions severely undermines the utility of an annotation, rendering it challenging to read, inaccurate, or visually discordant. Despite a growing body of annotation tools and automations, no existing benchmark or evaluation framework tests whether these conditions are met because of their scope and

Evaluating AI agents in interactive environments is hindered by fragmented tasks, scaffolds, verifiers, and scoring rules. Existing efforts focus on narrow settings, remain limited in scale, or require costly reruns, leaving much of the empirical record incomparable. We introduce Messier, a unified corpus of 957,253 records that span 30 benchmarks, 714 agents, 11,891 tasks, and 74,205 verifiers. Messier consolidates public benchmark scores and supplements them with five-agent runs across six und

Large Language Model (LLM)-based Automated Program Repair systems are advancing rapidly, yet their performance remains inconsistent. Even when provided with the same contextual information, an LLM may generate a correct patch for one bug but fail on another closely related bug. Why this happens remains poorly understood, and it is unclear how LLMs prioritize the diverse information in bug reports and whether model attention affects repair success. In this paper, we present the first empirical st

Large language model agents often spend substantial wall-clock time waiting for tool call results. Tool-call speculation can hide this latency by predicting and pre-executing an agent's next tool call if the prediction matches the agent's eventual tool call, but existing speculators are typically separate draft models or cached traces that are poorly aligned with the deployed agent's own behavior. We identify this speculator-agent gap and show that the target agent itself is a strong next-call s

This paper proposes a novel physics-guided spectral deep operator network, termed SpectONet, for solving Euler-Bernoulli beam (EBB) vibration problems. The proposed framework integrates the operator-learning capability of DeepONet with physics-informed constraints and Chebyshev-Gauss-Lobatto (CGL) sensor placement. Unlike conventional DeepONet frameworks, which commonly employ uniformly distributed sensors, SpectONet uses nonuniform spectral sensor locations with a higher concentration of points

This paper presents a cooperative indoor UAV guidance framework that combines a shared voxel-map world model with a multi-agent Soft Actor-Critic (MASAC) controller. Multiple drones fuse 360 LiDAR observations into a common world-frame occupancy map, which is converted into a compact bird's-eye-view (BEV) representation and provided to each agent as an ego-aligned local crop. This integrate-in-world, act-in- ego design enables consistent multi-UAV spatial fusion whilst retaining decentralised co

We propose Rashomon Alignment (RA), a new measure to assess functional similarity between two models. Existing functional similarity measures are distributional, quantifying differences between outputs of models applied to real-world data. However, these measures can be regarded as ecologically valid only for regions in the input space represented by the available data. We introduce a geometrical perspective on functional model similarity, which estimates it across the entire data space, offerin

Public services face growing pressure to adopt artificial intelligence (AI) to close the gap between rising demand and falling resources. That pressure has intensified with general-purpose AI (GPAI): AI built on large language models that can be directed by prompt alone to perform an effectively unbounded range of tasks. We argue that the properties that make these models attractive - their generality, accessibility, and low deployment cost - undermine the conditions under which AI safety has hi

While text-to-image models exhibit remarkable visual fidelity, they frequently violate fundamental physical commonsense. Existing benchmarks often rely on coarse-grained descriptions, failing to diagnose the mastery of specific physical principles. Moreover, the high stochasticity of generative processes causes current prompt optimization methods to suffer from gradient hallucinations, where optimizers are misled by transient visual artifacts rather than systemic flaws. To address these challeng

F(AI)2R is FAIR research with AI in the loop, twice: an AI-assisted authoring pass and a machine-readable audit pass over every artefact. AI systems now draft, refactor, and verify research artefacts, yet their contributions are rarely recorded in a form a later human or machine can audit. Building on the original F(AI)2R experiment, we generalize its provenance model beyond scholarly writing into aiprov, a PROV-O extension covering any AI-in-the-loop artefact, and we package the method as an ex

Large language models (LLMs) are costly intellectual assets that remain exposed to unauthorized redistribution and commercial misuse. Injected fingerprints, i.e., trigger--target pairs embedded in model behavior, offer a practical, black-box-verifiable ownership signal, but existing methods decouple the two stages of the fingerprint life cycle: how a fingerprint is constructed and how it is injected. Existing fingerprinting frameworks suffer from two limitations. Natural-language fingerprints ar

Decoding speech information directly from scalp electroencephalography (EEG) into text provides a potential non-invasive neural communication pathway for individuals with severe speech and motor impairments. Compared with invasive approaches such as electrocorticography, EEG is safer and more widely deployable, yet substantially more challenging to decode.This challenge is exacerbated for Chinese sentence decoding, which must handle a high-dimensional output space with thousands of characters, s

Positive quadratic networks admit the low-rank representation f_U(x)=x^top UU^top x, where Uinmathbb{R}^{dtimes r} is identifiable only up to right orthogonal multiplication, representing a rank-r PSD matrix Q=UU^top. We study how this quotient structure governs training dynamics, curvature, recovery, and interpolation bias. On the full-column-rank stratum, we identify mathbb{R}^{dtimes r}_*/O(r) with the rank-r PSD manifold. For smooth objectives L(U)=ell(UU^top), the Euclidean factor gradient

Perception tasks for autonomous vehicles need to work satisfactorily in adverse weather conditions. Due to lack of real-world weather datasets, weather simulations are a promising alternative. To ensure simulations closely mirror real-world weather data, it's crucial that they represent the same weather characteristics, including severity and particle positioning, across different sensors. To achieve this, we propose the Reference Dataset Alignment Method (ReDAM) for weather intensity alignment

Physics-informed neural networks (PINNs) have emerged as a powerful paradigm for solving partial differential equations (PDEs) by embedding governing physical laws into deep neural networks. However, their reliance on computationally expensive gradient-based optimization and deep architectures often results in slow training, high computational cost, and limited scalability. In this work, we propose a novel physics-informed broad learning system (PI-BLS), the first physics-informed learning frame

Entity alignment (EA) identifies entities across knowledge graphs (KGs) that refer to the same real-world object. Conventional EA methods mainly exploit explicit graph structures and textual fields, which often provide insufficient semantic understanding to recognize the same entity under heterogeneous descriptions and distinguish it from semantically similar entities. Although large language models (LLMs) offer deeper entity understanding, existing LLM-based EA methods largely use this capabili

Unifying visual understanding and generation in one model holds immense promise, but remains challenging and expensive due to heavy compute and data demands and conflicts between the visual features needed for these two capabilities. To address these challenges, we present Argus-Unified, a compact, effective and unified multimodal model built with low demand on computation and data. Instead of aligning modalities from scratch, Argus-Unified effectively leverages pretrained vision-language models

Health AI is evolving from answering questions to agentic systems that converse with patients, reason about health records, and act on their behalf. Primary care guards against diagnostic errors and unsafe care; agents assisting in this domain warrant evaluation against the same risks. Current benchmarks focus on medical knowledge, assessed through isolated question-answering or clinician-facing tasks. PatientAgentBench benchmarks patient-facing agentic healthcare; it evaluates a foundation mode

Vision--Language Models (VLMs) are increasingly deployed through a model supply chain in which pretrained checkpoints, architecture definitions, text encoders, and exported computation graphs are distributed by third parties and reused across downstream services. This reuse model creates a security-critical trust boundary: VLM deployments inherit not only learned parameters but also executable behavior encoded in shared model artifacts. In this paper, we show that a malicious provider can exploi

Multi-agent frameworks built on large language models (LLMs) routinely entangle three logically distinct concerns: who is on the team (organization), how members align (coordination), and which algorithm fuses their work (collaboration protocol). IMACS (Intelligent Multi-Agent Collaboration System) separates the three into orthogonal, independently swappable layers. Classic organizational theory (Belbin roles, Mintzberg coordination, RACI accountability) becomes executable, validated configurati

Capture the Flag (CTF) competitions are among cybersecurity's most effective training grounds, developing practical skill across cryptography, web exploitation, and binary exploitation. Large language models (LLMs) can now solve a growing share of challenges with minimal human input, raising urgent questions about fairness, the validity of rankings, and whether participation still delivers the learning that justifies the effort. This paper reports a mixed-methods study of LLM impact on modern CT

Large language model (LLM) agents are increasingly entrusted with natural-language workflow instructions (e.g., retail-payment policies) that specify not only what outcome to achieve, but also which steps, branches, and tool interactions are permitted. When these instructions are supplied as prompt context, however, the model retains control over both procedure selection and step execution. As interactions accumulate, an agent can skip required steps, take unsupported branches, or execute a vali

Language-model agents are increasingly deployed under standing instructions: a system prompt, a policy file, or a skills document is placed in context, and the agent is trusted to let it govern every action that follows. Existing benchmarks rarely test this deployment pattern directly; they measure whether an agent can complete a task, not whether a long, binding policy document actually constrains its behavior over an extended tool-use horizon. We present HANDBOOK.md, a benchmark of 65 agentic

The intersection of artificial intelligence adoption, cybersecurity governance, and public sector institutional constraints has not been examined as a unified analytical problem in the existing literature. Studies address AI cybersecurity risks generically, public sector governance independently, and framework adequacy separately. Existing studies have not integrated these three streams to explain specifically how AI adoption causes cybersecurity governance failure in government organizations, n

Tool-using agents expose structured calls but commonly attach free-form rationales. Such rationales are neither authorization nor reliable introspection. We present Explanation-Bound Tool Execution (EBTE), a claim-carrying mediation layer that converts decision-relevant rationale content into typed action claims and checks them against server-held intent, policy, payload, tool, risk, provenance, and freshness facts. EBTE cannot widen baseline authority: conflicts deny, incomplete or uncertain cl

Multimodal drug discovery enables drug representation learning beyond chemical structure by incorporating cellular responses such as gene expression and cell morphology. However, direct fusion and instance-level contrastive alignment may mix mechanism-related signals with modality-specific noise and incorrectly separate structurally dissimilar but biologically related compounds. This limitation can obscure transferable mechanism patterns required for predicting the properties of unseen compounds

Silicon sampling uses language models as proxies for human survey respondents, treating each model call as an independent draw from the persona's response distribution. We show this draw does not exist: instruction-tuned models do not sample from distributions, they collapse to a single output. The same persona on the same question returns the same answer on more than half of items in a public-opinion benchmark. The collapse is sharp: the model's internal probabilities concentrate on a single op

This paper presents ContractHIL-HLS, a contract-aligned multi-agent workflow for practical high-level synthesis (HLS) engineering. The workflow makes three contributions. First, it introduces a structured contract as the semantic-alignment and task-execution artifact that translates natural language requirements into explicit interfaces, constraints, validation checks, and rollback rules. Second, it incorporates hardware information into the feedback loop by feeding HLS, Vivado, PYNQ runtime, po

Activation steering controls language models by adding vectors or features to hidden states at inference time, but the upstream source of these steering signals is often treated as a secondary detail. We study this source choice as activation source selection: the combination of source context and activation readout policy used to collect the hidden states from which a steering signal is built. Holding the downstream intervention fixed, we show across three instruction-tuned models and four stee

Online recommendation has traditionally taken place after a user enters a platform, which determines the candidate pool and the ranking shown to the user. LLM-based user agents enable a different recommendation process: a user specifies a need before choosing a platform, leaving platforms to compete for the user's attention, which we refer to as an agentic recommendation market. In our controlled LLM-based experiments across three product domains, we find this new setting of recommendation creat

Foundation models for 12-lead electrocardiograms (ECGs) transfer well across clinical tasks, but the physiological knowledge encoded in their representations remains opaque. We present CADENCE, a framework that decomposes an ECG foundation model into a human-interpretable, queryable dictionary of physiological concepts. Using a BatchTopK sparse autoencoder, CADENCE factorizes Layer-6 embeddings from more than nine million ECG tokens into 8,192 sparse cardiac atoms. These atoms align better than

Semantic ID-based generative recommendation tokenizes each item into a sequence of discrete semantic IDs and predicts the next item by generating semantic IDs. However, existing methods typically regard SIDs as independent discrete symbols, while often overlooking the topology of the learned semantic ID space. We identify a structural mismatch between tokenization and generation: the tokenizer learns a structured code space with semantic neighborhood relations, whereas the generator consumes sem

Generative recommendation commonly represents items using fixed-length semantic identifiers (SIDs) constructed through clustering and quantization. However, these artificial codes may overcompress item semantics, remain misaligned with pretrained LLM vocabularies, and require costly autoregressive decoding. In light of this, we propose VaLiDRec, a generative recommendation framework based on variable-length, LLM-aligned semantic identifiers. VaLiDRec constructs SIDs directly from informative nat

Chest X-ray (CXR) machine learning relies heavily on automated evaluation using reference standards that aim to approximate clinical judgment. However, commonly used report-derived labels for pathology classification or generic image quality metrics for reconstruction may not reliably reflect clinical judgment. We systematically investigate how evaluation-reference choices affect model performance and ranking in both pathology classification and image quality assessment (IQA). To enable controll

On-policy distillation (OPD), which aligns a student with the teacher's token-level distribution on the student's own rollouts, is an effective paradigm for transferring capabilities across LLMs. Prevailing approaches assume a teacher at least as capable as the student: they either distill a larger model into a smaller one, which fails at the frontier where no larger teacher exists, or consolidate multiple domain experts trained from a shared base, which requires costly training at the student's

Large language model agents often encounter related yet distinct tasks that share reusable solution patterns. Yet standard agentic reinforcement learning treats tasks as independent episodes, while existing approaches to skill learning either focus on repeated attempts of one task or use pipelines with multiple stages that entangle extraction, retrieval, and execution. We introduce SkillRise, a unified reinforcement learning framework for learning skills across tasks. SkillRise organizes related

Large language model (LLM) agents are increasingly expected to assist users in completing tasks. However, existing benchmarks provide limited support for evaluating whether agents can carry out office-suite workflows at a reasonable cost. We introduce OmegaUse-OfficeVal, a benchmark for evaluating LLM agents on long-horizon office-suite tasks with task-level economic grounding. The benchmark comprises 100 tasks derived from office-suite requests proposed by practitioners and adapted through a pr

Vision-language-action (VLA) models commonly adopt an LLM-centric V to L to A pathway, where visual observations are projected into the representation space of a large language model before being decoded into robot actions. Although effective, this design incurs substantial computation and memory overhead at every policy invocation. In this work, we introduce TurboVLA, a new VLA paradigm that reformulates the conventional V to L to A pathway as a direct V + L to A mapping. Instead of using a lar

Fact-checking saw a rapid expansion in the mid 2010s when major social media platforms, especially Meta, started funding these activities. Today, however, fact checkers stand at a critical juncture. The early 2020s brought them three interrelated yet distinct crises: financial, technological, and legitimacy crises. The post The future of fact-checking in the algorithmic society first appeared on HKS Misinformation Review .

Background: Historic and ongoing problematic practices regarding the collection, storage, and use of Indigenous health data have led to the need to ensure principles of Indigenous Data Sovereignty (IDS) are followed in research practices and technology development. Objective: This project, a partnership between UC San Diego and the Native BioData Consortium (NativeBio), sought to explore the practical application of blockchain technology and its potential to facilitate Indigenous-led research co

Background: Multimorbidity involves heterogeneous disease combinations, treatment burden, competing priorities, and complex care pathways. Digital health interventions (DHIs) may support monitoring, self-management, and care coordination, but their effects on health-related outcomes remain uncertain. Objective: This systematic review and meta-analysis evaluated the effectiveness of DHIs on physiological, psychological, and functional outcomes in adults with multimorbidity, summarized implementat

Background: Although thyroid nodules are detected in up to 60% of adults on ultrasound, the vast majority are benign, creating a substantial decision-making burden compounded by heterogeneous practice guidelines. Large language models (LLMs) show promise in processing unstructured medical text and are emerging as tools for report interpretation among both clinicians and patients. However, their reliability across distinct clinical tasks in thyroid ultrasound interpretation remains poorly charact

Alignment training, model organisms, and toy models are usually treated as separate research areas. But projects in all three frequently use supervised fine-tuning (SFT) to pursue the same underlying goals. When projects share a goal, we should test whether lessons learned from one area transfer to the other areas. We study three such transfers, each taking a lesson developed in one SFT setting and testing it in another. First, we port a lesson about behavior generalization from alignment traini

Automated molecular structure elucidation from infrared (IR) spectroscopy data has seen significant advancements in recent years, but its broad applicability is limited by a reliance on pre-determined chemical formulas provided as auxiliary model inputs. This limits model predictions to isomer identification rather than full molecular structure prediction. Although transformer models have been shown to identify molecular isomers with high accuracy, their reliability for unconstrained structure e

Background: With the expanding need for advance care planning (ACP), innovative educational strategies for training health care providers are increasingly required. Large language model (LLM)–based ACP chatbots offer a novel and potentially effective solution to enhance health care providers’ competence in navigating complex ACP conversations. Objective: This study aimed to develop a Chinese-context ACP corpus to support an LLM-based chatbot and evaluate the feasibility and performance of a mult

Background: The rapid emergence of artificial intelligence (AI) has outpaced its formal adoption in health care organizations, contributing to the emergence of Shadow AI, defined here as the use of unauthorized AI tools by medical professionals. Under the European Union Medical Device Regulation, AI tools used for clinical purposes must undergo conformity assessment before use; general-purpose tools such as ChatGPT have not done so, rendering their clinical application unauthorized at the regula

Background: Therapist-guided internet-delivered cognitive behavioral therapy (guided iCBT) is increasingly implemented in routine mental health care to expand access to evidence-based treatments. Although the clinical effectiveness and patient acceptability of guided iCBT for common mental health disorders are well established, less is known about how introducing such digitally mediated interventions reshapes therapists’ everyday work practices and professional roles. Existing research has prima

Exact-equivariant architectures typically encode prescribed group actions in specialized operators, which can complicate their reuse with generic backbones and across data modalities. We introduce the Generator-Aligned Representation Interface (GARI), a representation-level design principle that exposes selected transformation generators to a generic sequence backbone through aligned canonical and generator-induced views. We formalize the resulting behavior using a probe-specific soft-equivarian

Background: Health misinformation is a serious and growing concern, especially in the era of mass digitalization. However, the term lacks conceptual clarity, reducing our ability to build a reliable, replicable evidence base about how misinformation works and undermining our attempts to develop effective responses. There is, therefore, a need to examine how the term is used and to develop a coherent definition that better reflects people’s information priorities, concerns, and understandings of

Adapting Large Language Models (LLMs) to specialized domains often incurs an alignment tax, as fine-tuning on domain-specific tasks can cause catastrophic forgetting and substantially degrade performance on general tasks. We propose MemSFT, which mitigates the alignment tax by decoupling domain specialization from backbone parameter updates through a plug-and-play parametric memory. The memory is trained to imitate the behavior of a non-parametric retriever operating over domain data, thereby me

LLM-based Cross-Domain Sequential Recommendation (CDSR) leverages LLMs to enhance target performance via deep semantic reasoning, alleviating the dependency on overlapping users. Among LLM-based paradigms, model merging is particularly promising for multi-domain scenarios due to its superior scalability and flexibility in integrating diverse knowledge sources. However, our empirical investigations reveal two critical bottlenecks: (1) cross-domain knowledge conflict; and (2) performance saturatio

On-device speech emotion recognition (SER) is critical for real-time applications, yet large self-supervised models that excel at SER are too costly for edge devices. Multi-teacher knowledge distillation can compress them into a lightweight student, but two challenges remain: teacher reliability varies across batches, and logit-level distillation ignores inter-sample relational structure. We propose Adaptive Multi-teacher Relational Distillation (AMRD) to address both. A one-class SVM on each te

arXiv:2607.22604v1 Announce Type: new Abstract: In the age of Artificial Intelligence (AI), Large Language Models, Generative AI and larger frontier AI models, data centres create a significant environmental burden on electricity grids and fresh water resources. Requiring data centre operators and Big Tech under the recast Energy Efficiency Directive (recast EED) to quantify, report and disclose the facility-level energy and water impacts seems to be a step into the right direction towards more

arXiv:2607.22605v1 Announce Type: new Abstract: We investigate whether large language models alter medical triage recommendations for identical symptoms when only the patient's socioeconomic status (SES) varies. Using three deployment-tier models (Gemini 3.5 Flash, Claude Sonnet 4.6, GPT-5.4-mini), we hold a single neurological symptom profile fixed and vary the SES signal along two channels: explicit (insurance status, occupation, housing) and implicit (a US ZIP code, with no other socioeconomi

arXiv:2607.22606v1 Announce Type: new Abstract: Health systems are rapidly deploying generative AI assistants that answer patient questions from institution-authored education materials, on the premise that grounding in local content yields consistent guidance. Whether it does depends on a question not previously measured at scale: do the underlying documents themselves agree? We use a structured-output large language model judge to audit 5,730,465 pairwise comparisons across 102 patient-educati

arXiv:2607.22607v1 Announce Type: new Abstract: The prospective clinical evaluation of artificial intelligence in medicine has expanded rapidly, but the global AI clinical trial landscape remains incompletely characterized. We systematically identified AI-related trials registered in ClinicalTrials.gov using a broad keyword search followed by an LLM-based classifier. Each trial was classified across seven dimensions: clinical function, data modality, specialty, AI integration and autonomy, workf

arXiv:2607.22613v1 Announce Type: new Abstract: This paper explores the intersection of memory, place, and identity, examining how new technologies, particularly Apple Vision Pro, can illuminate this nexus. Leveraging digital twins and virtual reality, it investigates how memory is woven into landscapes and urban environments of cultural and historical significance, identifying visual elements that evoke memory and heritage. Applications such as Apple Vision Pro can facilitate image extension to

arXiv:2607.22617v1 Announce Type: new Abstract: Data centers are critical to today's digital economy, but are also among the largest industrial consumers of freshwater. Beyond the sheer volume of water use, the environmental impact of data center water consumption varies significantly across locations and seasons, depending on local and regional water stress. However, prior research has largely focused on reducing total water use, overlooking that the same unit of water can have drastically diff

arXiv:2607.22619v1 Announce Type: new Abstract: Several international agreements have been proposed to regulate frontier AI development in response to catastrophic risks. However, there is no structured way to evaluate whether these proposals are enforceable, to assess where they might fail in practice, or to determine which combination of policies is most effective. We propose a taxonomy based on the principle that wherever sufficient capacity exists to violate an agreement, it must be under a

arXiv:2607.22640v1 Announce Type: new Abstract: Short-term environmental exposures have been linked to cognitive and behavioral outcomes, although many reported associations may reflect broader geographic and contextual differences. Using longitudinal data from the All of Us Research Program (2018--2024), we linked daily weather and air-pollution exposures to repeated attention-related and subjective cognitive outcomes. Associations were evaluated using pooled, fixed-effects, lagged, and event-s

arXiv:2607.22656v1 Announce Type: new Abstract: Objective: This paper investigates the gendered structure of speaker addressee relationships in film dialogue, asking not merely who speaks, but who is spoken to and how conversational dynamics unfold across gender lines. Methods: Using a manually annotated dataset of 4,600 directed dialogue events from 38 film screenplays, we apply network analysis, chi squared tests, paired statistical comparisons, and participation shift analysis across three st

arXiv:2607.23207v1 Announce Type: new Abstract: The emerging infrastructure for AI-agent identity has converged, in industry practice and research proposals alike, on a single resolution of the tension between accountability and privacy: make every agent identifiable. We document a national system in China -- built as national infrastructure and scheduled for public launch in Q3 2026 -- that occupies a different and underexplored point in the same design space: an agent is associated with a veri

arXiv:2607.23336v1 Announce Type: new Abstract: The built environment is on the cusp of populating itself with autonomous artificial agents. AI systems that advise, control and coordinate are being deployed across retrofit, operation and mobility faster than their collective behaviour is studied. The dominant framing treats each agent as a tool operating on a passive building, governance reduced to single-agent safety, which is inadequate. A building, a street, or a city is more accurately model

arXiv:2607.23519v1 Announce Type: new Abstract: Political audits of large language models (LLMs) usually reduce each to one point on a political compass. But that resting point barely matters in deployment: a model must land somewhere, and what counts is how far, and in which directions, its answers can be steered. That steering runs through the system prompt: the personalization layer a platform sets, or one induced from a user's history, not necessarily written by hand. We run a dispersion-fir

arXiv:2607.23539v1 Announce Type: new Abstract: AI agents can transact online on behalf of a human principal---browsing, paying, receiving, and reviewing---without linking a transaction to a principal. That architecture starves algorithmic discrimination of its inputs---identity, purchase history, location history, behavioral traces, and demographic proxies---but also forecloses its proof. Disparate-treatment needs comparators; disparate-impact needs protected-class baselines; and Iqbal-era plea

arXiv:2607.23931v1 Announce Type: new Abstract: The aggregation benefit of a committee of artificial intelligence (AI) agents comes from complementary information across members. Classical voting guarantees assume independent errors. Language-model errors often co-occur on the same cases. We combine Sah-Stiglitz screening with error dependence that can differ between good and bad cases. In a homogeneous exchangeable Gaussian-copula model, shared errors create a positive asymptotic error floor fo

arXiv:2607.23993v1 Announce Type: new Abstract: Misinformation is deeply embedded in online discourse, with nearly one in five posts during global events generated by bots that amplify false content. In recent years, the use of Generative AI has further lowered the barrier to producing convincing misinformation, yet most digital literacy education still relies on static checklists and single-player inoculation games built for an earlier media landscape. This paper describes how we addressed this

arXiv:2607.24035v1 Announce Type: new Abstract: Explainable AI (XAI) is used to assess whether artificial intelligence models rely on meaningful patterns, yet explanations that appear plausible for individual predictions may systematically misrepresent model behavior. This is particularly problematic in medicine, where models may rely on irrelevant signal characteristics rather than disease-specific patterns without being recognizable. We address this challenge using electrocardiogram (ECG) data

arXiv:2607.24391v1 Announce Type: new Abstract: AI systems already govern. They rank speech and allocate attention, filter applicants and triage claims. The dominant frame for AI governance, alignment, asks whether such systems pursue the right objectives safely. It cannot answer a prior question: by what right are those objectives set and enforced? This Article argues that legitimacy is an autonomous regulatory objective, distinct from alignment and not secured by it. Legitimacy here is sociolo

arXiv:2607.22940v1 Announce Type: cross Abstract: Computer programming MOOCs are instrumental in providing students with high-quality instruction in areas where there is limited access. They are especially beneficial to post-secondary African students as less than 1% of them leave secondary school with fundamental coding skills. One strategy for increasing their efficacy for African students is to understand students' motivation for enrolling. These insights can inform the design of MOOC content

arXiv:2607.22953v1 Announce Type: cross Abstract: Modern AI systems bring societal risks such as mass surveillance, extreme concentrations of power, and loss of user autonomy---calling into question a model where third-parties collect and control massive amounts of user data. Users require a sovereign system to securely own, govern, and disclose their context while remaining compliant across regulated domains with strict provenance, interpretability, and policy adherence. Perspective-aware AI ap

arXiv:2607.23082v1 Announce Type: cross Abstract: The semiconductor sector faces a dual transition: scaling manufacturing execution through Artificial Intelligence (AI) while satisfying stringent sustainability mandates, such as the EU Carbon Border Adjustment Mechanism (CBAM). This paper presents a scoping review of 1,465 documents indexed in Web of Science and Scopus, spanning AI-integrated metrology, supply chain ESG, and federated industrial data spaces. Network analysis reveals a highly fra

arXiv:2607.23317v1 Announce Type: cross Abstract: Investigating how affective states such as confusion and frustration persist and transition during co-situated collaborative problem solving (CPS) is important for understanding the dynamics of epistemic emotions. However, the accurate identification of affective states remain challenging as there is no gold-standard truth in this space. Here, we analyze affective states collected through retrospective cued-recall during an in-person CPS task. Us

arXiv:2607.23438v1 Announce Type: cross Abstract: As AI systems increasingly exhibit agentic behavior, discussions of autonomy often conflate what systems are technically capable of doing with what they should be permitted to do in practice. This paper introduces a governance framework that explicitly separates Allowed Autonomy Levels (AAL), which define the degree of autonomy an AI agent is authorized to exercise given risk, oversight, and accountability considerations, from Autonomous Capabili

arXiv:2607.23566v1 Announce Type: cross Abstract: Traditional human marking in upper-secondary STEM education creates a structural bottleneck that restricts the frequency of formative mock examinations. This quasi-experimental, mixed-methods longitudinal study (N = 142) investigates the efficacy of deploying a fully automated, handwritten assessment marking platform to remove this bottleneck. Students preparing for STEM A-levels (Mathematics, Further Mathematics, Biology, Chemistry, Physics) wer

arXiv:2607.23888v1 Announce Type: cross Abstract: In the United States, artificial intelligence (AI) is rapidly deployed amid limited federal regulation. With courts become a recurring forum in which AI-related practices are scrutinized, it is important to empirically understand the AI litigation landscape to date. We address this gap through a systematic review of 559 U.S. federal court opinions in which AI plays a role in the parties' contentions, taxonomizing (1) common topics of dispute, (2)

arXiv:2607.23941v1 Announce Type: cross Abstract: Automated agents increasingly participate in online communities, yet their population structure and roles remain poorly understood. Using a dataset of 3,389 identified bots and their full activity histories, we construct a taxonomy of bot "species" on the news aggregation and social media platform Reddit based on temporal, community, linguistic, and semantic features. Clustering analysis reveals 18 distinct bot types spanning content-specialized,

arXiv:2607.24275v1 Announce Type: cross Abstract: Ethical governance of AI-driven systems is often expressed through high-level principles and static documentation, creating a gap between regulatory requirements and system-level verification. This challenge is particularly acute in digital phenotyping, where continuous behavioural data raises concerns around consent, privacy, and fairness. In this paper, we propose a computational ethical framework for AI-driven digital phenotyping system in whi

arXiv:2504.02636v3 Announce Type: replace Abstract: As generative AI (GAI) becomes increasingly embedded in higher education, universities worldwide are developing policies to govern its ethical, pedagogical, and institutional use. However, these policies vary across national and institutional contexts. We undertake a cross-nationalanalysis of GAI guidelines issued by leading universities in the United States, Japan, and China, identifying key policy orientations and proposing a structured frame

arXiv:2511.13949v4 Announce Type: replace Abstract: The rapid integration of AI writing tools into online platforms raises critical questions about their impact on content production and outcomes. We leverage a unique natural experiment on Change$.$org, a leading social advocacy platform, to causally investigate the effects of an in-platform ''write with AI'' tool. To understand the impact of the AI integration, we collected 1.5 million petitions and employed a difference-in-differences analysis

arXiv:2601.08878v2 Announce Type: replace Abstract: Text-based online counselling scales across geographical and stigma barriers, yet faces practitioner shortages, lacks non-verbal cues and suffers inconsistent quality assurance. Whilst artificial intelligence offers promising solutions, its use in mental health counselling raises distinct ethical challenges. This paper analyses three AI implementation approaches - autonomous counsellor bots, AI training simulators and counsellor-facing augmenta

arXiv:2603.18221v3 Announce Type: replace Abstract: Written work no longer certifies that a student understands it: a polished analysis now says little about who did the thinking. Oral examinations restore that evidentiary link, but they have never scaled, because conducting and grading them is expensive. We report on a system in which voice AI conducts a personalized oral exam and a council of three large language models (LLMs) grades the transcript, each model scoring independently and then re

arXiv:2603.20248v2 Announce Type: replace Abstract: AI systems are increasingly entrenched in public governance, yet scholarship lacks formal tools to determine when deviations of public trust in algorithmic institutions dissipate and when they grow into collapse. Stability refers here to asymptotic recovery from finite state perturbations under fixed structural parameters. We address this gap by developing a mathematical framework for institutional trust stability that couples a Friedkin-Johnse

arXiv:2603.28371v2 Announce Type: replace Abstract: When an agent can articulate why something works, we typically take this as evidence of genuine understanding. This presupposes that effective action and correct explanation covary, and that coherent explanation reliably signals both. I argue that this assumption fails for contemporary Large Language Models (LLMs). I introduce what I call the Bidirectional Coherence Paradox: competence and grounding not only dissociate but invert across epistem

arXiv:2605.02050v2 Announce Type: replace Abstract: This work establishes a framework for standardizing AI evaluation RCTs (sometimes called human uplift studies). Drawing on established practices from disciplines with established RCT traditions, including software engineering, economics, clinical and health sciences, and psychology, we synthesize five principles drawn from established validity frameworks and open-science standards on transparency, repeatability, and verification, which together

arXiv:2407.14766v4 Announce Type: replace-cross Abstract: This paper presents a philosophical and experimental study of fairness interventions in AI classification, centered on the explainability and transparency of corrective methods, and on the opposition between two fairness criteria, namely Demographic Parity and Equalized Odds. Our main argument is that even as a gap in Demographic Parity is used to diagnose inequality between groups, Equalized Odds constitutes a more reliable fairness crit

arXiv:2507.21134v2 Announce Type: replace-cross Abstract: As large language models (LLMs) are increasingly deployed in high-risk domains such as law, finance, and medicine, systematically evaluating their domain-specific safety and compliance becomes critical. While prior work has largely focused on improving LLM performance in these domains, it has often neglected the evaluation of domain-specific safety risks. To bridge this gap, we first define domain-specific safety principles for LLMs based

arXiv:2602.18443v2 Announce Type: replace-cross Abstract: Psychosocial online counselling frequently encounters generic subject lines that impede efficient case prioritisation. This study evaluates eleven large language models generating six-word subject lines for German counselling emails through hierarchical assessment - first categorising outputs, then ranking within categories to enable manageable evaluation. Nine assessors (counselling professionals and AI systems) enable analysis via Kripp

arXiv:2605.20198v2 Announce Type: replace-cross Abstract: Augmented analytics has transformed how Business Intelligence (BI) systems support decision-making, shifting non-technical managers from manual analysis toward dependence on automated insights. Current BI research often overlooks the cognitive mechanisms and the direct impact of AI-enabled analytics on decision quality. This study employs the theory of cognitive delegation to investigate the association between trust in augmented analytic

arXiv:2606.09833v2 Announce Type: replace-cross Abstract: AI agents are reshaping the workspace, leading to drastic change of how humans work. Despite the considerable potential of human-agent collaboration both in preserving human agency and generating economic value, this paradigm remains largely absent from occupational task evaluation, hindered by the difficulty of gathering real human data and accounting for inter-human variability. We introduce CollabSkill, a framework for evaluating human

arXiv:2606.13385v2 Announce Type: replace-cross Abstract: LLM-based web agents are increasingly deployed in real-world settings such as e-commerce, where they interact extensively with untrusted web content while executing actions that carry direct financial consequences. This makes them vulnerable to prompt-injection attacks, in which seemingly benign web content conceals adversarial instructions that manipulate the agent's behavior. Existing security benchmarks adopt an \textit{attack-centric}

Large Language Models (LLMs) have been widely applied in high-stakes decision-making scenarios such as corporate strategy, and users are increasingly relying on their outputs. However, the deep integration of open-source model sharing ecosystems with LLM-powered critical decision-making applications also introduces critical risks: if an attacker can manipulate the model's cognitive stance, they can indirectly influence the judgments and actions of downstream decision-makers. This paper defines s

Reinforcement Learning from Human Feedback (RLHF) is the standard approach for aligning large language models with human preferences, but its quality is limited by static, task-agnostic reward models. This mismatch leads to sparse learning signals and suboptimal alignment. We introduce MeRLa (Meta-Learned Reward Shaping), a principled framework that meta-learns a task-aware shaping function $Φ(x,y;φ)$ across auxiliary tasks before RLHF training. The learned shaping produces a composite reward th

Big Data & Society, Volume 13, Issue 3, July-September 2026. The COVID-19 pandemic witnessed the transformation of data from a public health resource into a measure of morality. Disadvantage indices such as the Healthy Places Index and other metrics became central to promoting equity in the pandemic response, ...

Quantum computing (QC) has established itself as a disruptive technology that has the potential to enhance computational capabilities across next-generation energy systems. Its integration into smart grids can enable intelligent decision-making, secure control mechanisms, and advanced optimization strategies. However, existing research remains methodologically fragmented and lacks a unified discussion for practical adoption. This highlights the need for a systematic assessment of the current res

IntroductionBreast cancer remains one of the leading causes of cancer-related mortality rate worldwide, and the identification of effective drug combinations is an essential requirement in pharmaceutical research. The integration of Artificial Intelligence (AI) in processing large volumes of chemical and biological data combines molecular representation, predictive modeling and structured support within a single accessible tool, which accelerates early-stage candidate identification for breast c

Lung cancer remains one of the leading causes of cancer-related deaths worldwide, and early identification of malignant abnormalities plays an important role in improving patient survival rates. However, accurate lung cancer classification using CT imaging remains challenging because of limited dataset availability, class imbalance, overlapping lesion characteristics, and lack of interpretability in existing deep learning systems. This study presents a GenAI-driven CNN–RNN framework for explaina

IntroductionBanana production is increasingly threatened by fungal diseases such as Fusarium wilt and Black Sigatoka, posing severe risks to food security and agricultural economies. Recent image-based approaches using deep learning have shown high predictive capacity for plant disease recognition; however, their limited transparency, calibration uncertainty, and sensitivity to domain shifts can restrict their use in decision-support workflows that require auditability.MethodsThis study proposes

Large language models (LLMs) are increasingly used as synthetic users, stand-ins for human respondents whose simulated answers feed product, policy, and market decisions. We ask when this substitution is valid and when it fails, and package the answer as an evaluation framework for intelligent synthetic-user systems. A single protocol, run across four models spanning two families and an 8B-to-frontier capability range, is applied to two independent domains of real human-response data: U.S. gener

Mixture of Experts (MoE) architectures have become key to large language models; however, their typical round-robin (RR) scheduling introduces significant bottlenecks. In this paper, we demonstrate that RR causes a previously-undiscovered exponential incast phenomenon with MoE traffic. We propose an alternative proactive fair scheduling framework tailored for MoE workloads, which effectively prevents fabric oversubscription. We also outline how it can be implemented in NICs. Finally, through ext

Artificial Intelligence (AI) is transforming higher education, but its benefits can vary depending on where, how, and how often it supports learning. While prior research emphasizes cognitive and academic outcomes, this study examines how AI chatbots support the psychological needs and motivational states of engineering students. A survey of college engineering students (n = 206) examined perceived effects of AI chatbots on autonomy, relatedness, and relief from competence frustration. Structura

Stealth, the discipline of achieving an objective without revealing your presence, capabilities, or collected intelligence, is what separates sophisticated operators from detectable ones. Elite security researchers and advanced persistent threats achieve their objectives unnoticed; autonomous agents increasingly inherit the same offensive tasks, but do they inherit the tradecraft? We introduce StealthBench,a benchmark that measures operational stealth in autonomous offensive-security agents acro

AI agents are increasingly adept at tackling complex, long-running tasks. With the rapid surge of autonomous capabilities, human oversight is systematically lagging behind due to limited human-centered interfacing. Aiming to address this, we introduce AgentGUI, a user-friendly, locally hosted GUI for seamlessly observing and steering AI agents amid multiple concurrent, long-running sessions. AgentGUI features 1) rich agent trajectory visualizations, 2) effective manual and automated steering, an

In this study, we surveyed users for their perception of misinformation exposure across social media platforms. Such perceived exposure is important because individuals' beliefs about how often they encounter false information can shape their trust in institutions, platforms, and even their friends. In a survey of 1,010 United States residents, we found that perceived exposure to misinformation varies substantially across platforms and is only moderately correlated with the frequency of platform

On-policy distillation (OPD) grounds token-level supervision in the student's own trajectory, yet suffers from prefix failure: once the student commits to a wrong reasoning direction, all subsequent generation builds on this deviation, producing misdirected continuations that elicit unreliable supervision and waste compute. We identify a teacher-student continuation asymmetry on failed prefixes, where the teacher tends to redirect while the student continues along the original direction, and con

Generalist manipulation policies increasingly take the form of action-chunking flow policies built on large pretrained backbones. Such chunks run open-loop, so the policy cannot react to sensory input arriving mid-execution, sacrificing \emph{reactivity}. Replanning more often would restore it, but the perception-to-action pipeline (a large backbone plus multiple denoising steps) is too slow: this \emph{latency} forbids frequent replanning and leaves committed actions stale, making such policies

Computer-use agents (CUAs) increasingly act through desktop GUIs to complete long-horizon tasks. Current benchmarks primarily measure end-task success or single-frame grounding. Neither isolates whether a model can reconstruct the causal, task-relevant transition produced by an action- crucial for rejecting stale observations, verifying progress, and recovering from failure. This is difficult because inference, remote input, app rendering, and screenshot capture are asynchronous: the next observ

Recently, photonic transformer accelerators (PTAs) have successfully achieved significant speedup and energy efficiency improvements over electronic accelerators for expediting Transformer inference. However, state-of-the-art rely on expensive multi-wavelength light generation and large dot-product units due to active phase-shifter components, thus making their approach inefficient and impractical. To address this, we propose MDTransformer, a novel hardware-software co-design of PTA based on mod

Self-play in simulation produces robust driving policies at scale. Demonstrations of such behavior have been made using privileged vectorized observations such as exact poses and velocities, even for occluded agents. This assumes that perception is solved and introduces a representation gap with the partial observation of a deployed agent driving from the perspective view of egocentric cameras. A common fix, distilling the privileged policy into a camera-input student, leaves the student imitati

Recently, memory management has become a key infrastructure for LLM-based agents, as it directly affects long-horizon reasoning, personalized responses, and knowledge reuse. However, existing LLM memory systems typically adopt a coarse-grained (utility-agnostic) manner that treats heterogeneous user-LLM interaction records uniformly, leading to redundant and low-impact records persisting in the memory repository. To address this challenge, we present MemLens, a value-aware memory management syst

Scientist have developed a host of AI ‘protein language models’ that can create proteins from scratch. But Raygun can modify existing proteins, using some of the same steps as natural evolution: ...

Scientific research involving code has long rested on the assumption that at least one person understands why the code exists. As scientists adopt coding agents, this assumption is breaking down. Drawing on an ongoing contextual inquiry of scientific programmers working with agentic tools (four cases to date), a survey of over 800 scientific programmers, and my own analysis workflows, this position piece describes how scientists are inventing personal conventions, "landmarking strategies", for m

EEG-based community sensing programs are emerging globally as a tool to leverage aggregated brain data to gain insights into attentiveness of students and employees. But these programs raise privacy concerns because EEG signals contain sensitive personal information. Differential Privacy (DP) can protect individuals while preserving aggregate statistics yet applying DP to EEG data is challenging as it requires user-level noise generation, which increases power and latency. Besides, most commerci

Any-to-any models predict any modality from any combination of others within a single network, a formulation used in multimodal vision and vision-language models, and increasingly in scientific domains such as ecology and astronomy. Existing any-to-any models are typically trained from scratch using encoder-decoder or diffusion architectures, impacting their performance and preventing them from using strong pre-trained decoder-only models as a prior. In this work, we investigate decoder-only any

Clinical diagnostic evaluation should not only assess whether models can provide correct diagnoses, but also reflect the realities of clinical practice, including progressive disclosure of multimodal information, dynamic updating of diagnostic hypotheses, and continuous refinement of clinical reasoning. However, existing evaluations of multimodal large language models (MLLMs) typically rely on single-turn or isolated tasks, making it difficult to fully capture the complexity of real-world clinic

Face de-identification (De-ID) aims to remove or conceal personally identifiable facial features in images or videos to prevent identity recognition while preserving utility for downstream tasks. With the rising emphasis on data privacy and responsible AI, face De-ID has emerged as an active research area spanning computer vision and privacy-preserving communities. Early approaches, and many contemporary ones, operate in the digital domain by modifying pixel-level or appearance-level features th

Over the past decade, decision trees have been used to represent controllers (a.k.a. policies) in an explainable way, with dtControl2 as a current state-of-the-art tool. However, for systems that are large or have many corner cases, even such representations tend to be too complex and not human-comprehensible. Unfortunately, reducing the size of the decision tree is not straightforward, as missing just a single crucial case might result in an incorrect controller. We tackle this issue in the set

The rise of generative artificial intelligence (GenAI) has fueled high expectations regarding its potential to enhance knowledge work productivity in terms of efficiency and quality. Building on task-technology fit (TTF) theory, we empirically examine the extent of GenAI's productivity effect for different task types. We conducted a randomized lab-in-the-field experiment with 128 knowledge workers from a multinational industrial organization. Participants completed three representative knowledge

In this work, we study the use of Vision-Language Models (VLMs) for anomaly detection in an agent-driven game Quality Assurance (QA) pipeline focusing on geometry clipping. In this evaluation, a custom exploration agent navigates a game level to collect visual observations, while the automatic annotation pipeline provides frame-level clipping labels. This setup allows us to evaluate recent VLMs on a controlled anomaly detection task without manual annotation. We benchmark six recent VLMs (Gemini

Autonomous Network Levels 4-5 require AI agents to invoke tools across vendor boundaries without human oversight, yet existing management standards lack a standardized mechanism for cross-vendor trust visibility. When a tool from Vendor B is compromised, agents from Vendor A continue invoking it -- unaware of the trust degradation -- causing cascading service impact. We present AgentToolMO, a proposed 3GPP NRM information model for agent tool trust management. The model comprises: a formally def

We introduce \textbf{GPT-Red}, an automated red-teaming agent that is trained to discover novel prompt injection attacks against frontier LLMs. The goal of this model is to evaluate and improve the robustness of our production systems. To this end, we use it to adversarially train GPT-5.6, our most robust model to prompt injections to date. To create GPT-Red, we design a scalable self-play algorithm where the model is tasked with attacking a diverse population of simultaneously-trained defender

Graphical user interface task evaluation aims to determine whether a GUI agent has successfully completed a user instruction. Automated GUI task evaluation has received increasing attention because the evaluation results can serve as reward signals for both test-time scaling and post-training. However, reliable GUI task evaluation remains challenging because the judgments often require access to environment states, such as system configurations, file data, and application settings, beyond the sc

AI coding agents are being adopted at historic speed, yet security and risk concerns remain the primary barrier to scaling agentic AI across organizations. Existing security controls for coding agents are not systematically distributed to engineering teams, and vendor-native solutions introduce ecosystem dependencies that may not suit every deployment context. This paper investigates whether off-the-shelf security controls can be implemented on commercial AI coding agents and scaled to a distrib

We investigate how well large language models (LLMs) can assist scientific project planning and proposal evaluation. One-page project plans were independently generated for eight expert-conceived research projects in physics, astrophysics, and cosmology by human researchers and three contemporary LLMs (ChatGPT, Claude, and DeepSeek; mid-2025 models, used with their default tool access). The resulting 32 proposals were blindly evaluated by four human reviewers and two newer frontier LLMs (Claude

This paper investigates how multi-agent systems (MAS)-based on large language models (LLMs) can support actuarial risk modelling, with a particular focus on uncertainty quantification. Actuarial workflows represent a high-stakes decision-support setting where unreliable outputs may lead to incorrect risk assessment, unfair pricing, and regulatory non-compliance. To address uncertainty introduced by the probabilistic nature of LLMs and dependencies between agents, a multi-agent framework is propo

Skills have become an important abstraction for enabling large language model (LLM) agents to reuse past experience in long-horizon interactive tasks. However, existing trajectory-to-skill methods often produce flat collections of high-level textual skills that are stored and retrieved independently, leaving skill relations underutilized and maintaining a gap between high-level skills and executable actions. In this paper, we propose HiSkill, a hierarchical skill graph framework that organizes i

Quantum computers are moving from research laboratories to industrial machines accessible via the cloud and integrated into high-performance computing facilities. However, translating theoretical quantum protocols into hardware experiments remains a major bottleneck, requiring expertise across protocol design, compilation, simulation, and cloud execution. Here, we introduce an agentic workflow that automates this pipeline on neutral-atom quantum processors (here two Pasqal QPUs available on the

Recommender systems mediate everyday consumption, offering a promising channel for encouraging sustainable choices. Prior research shows that explanations influence users' perceptions of recommendations and can support more informed decisions. We argue that explanations can also serve as behavioral nudges by foregrounding sustainability information at the moment of choice. This study investigates how different behavioral framings of sustainability information in recommendation explanations affec

Large language model (LLM) agents increasingly rely on invoking external tools to complete real-world tasks. Tool retrieval, which selects a small task-relevant subset from a library of thousands of tools before the agent acts, has therefore become a critical component of LLM agent pipelines. However, existing retrievers either score each tool in isolation or assemble the tool set sequentially, so the joint utility of a candidate set is never evaluated as a whole. In this paper, we propose HYSET

Large language models (LLMs) increasingly support biomedical research, yet their behavior under adversarial requests for dual-use knowledge remains insufficiently characterized. We introduce BioDisclose, a benchmark for measuring biomedical knowledge disclosure under adversarial elicitation. BioDisclose contains 480 prompts derived from 24 expert-authored scenarios across six biomedical risk domains and four elicitation families spanning academic, historical, role-playing, and decomposed prompti

Full-field reconstruction of air pollution is essential for evaluating pollution exposure and supporting public health decision-making. However, the complex interactions among pollutants, hard-to-predict weather patterns, and limited monitoring station coverage make this a complex task. We apply deep learning techniques to provide fast and accurate reconstructions from sparse observations of four key pollutants: NO2, O3, PM2.5 and PM10. Models are trained on full-field simulation data and evalua

Cognitive distortion amplifies negative emotions and contributes to mental health disorders. Cognitive Behavioral Therapy (CBT) is an effective way to address cognitive distortions, but its large-scale application is limited by the shortage of professional therapists. Although large language models (LLMs) have recently been explored for mental health applications, existing methods still suffer from limited domain specificity, overly flattering responses, and the absence of well-defined annotatio

Multimodal behavioral analysis offers a scalable approach to assessing depression, anxiety, and stress, yet generic fusion models often ignore the psychometric structure of questionnaire labels. In DASS-21, risk labels are derived from ordered symptom items through fixed item-to-subscale mappings. We propose \textbf{DynaBridge}, a dynamic summary-guided cross-task multimodal framework for DASS-structured mental health assessment. DynaBridge encodes acoustic, visual, and textual cues across multi

Quattrociocchi and colleagues warn that the fluent outputs of large language models may allow linguistic plausibility to substitute for epistemic evaluation, producing the condition they call *Epistemia*: the experience of possessing knowledge without undertaking the practices through which judgment would ordinarily be warranted. This article accepts that diagnosis but challenges its explanatory framework, which compares an embodied, socially situated human knower with an isolated generative mod

Inequality in real-world societies are associated with psychological distress and behavioral consequences. However, less is known about whether similar dynamics emerge when inequality exists within virtual environments or make-belief worlds. As online games increasingly constitute meaningful social spaces, it becomes critical to examine how players perceive and react to structural and resource differences online to optimize their experiences. This study studies perceptions of inequality in the o

Statistical analysis on sensitive datasets like medical records and financial transactions is essential for decision-making, but raises significant privacy concerns. While existing secure Two-Party Computation (2PC) makes extensive efforts in designing the common secure primitives (e.g., addition and multiplication) or machine learning-related functions, few pay attention to the statistical functions. In this paper, we propose SafeStats, a secure toolkit tailored for 2PC secure statistical analy

Eliciting explainable AI (XAI) requirements from stroke survivors presents a methodological challenge with direct implications for the design of trustworthy brain-computer interfaces for rehabilitation. How can patients and caregivers articulate preferences about algorithmic transparency when they lack conceptual frameworks for explainability, and when standard elicitation approaches are structurally inadequate for users with acquired communication disorders? We present a video-based scaffolding

Supply chain decision-making is rapidly transforming with the rise of agentic AI - highly autonomous systems that can operate on complex, long-horizon tasks. Yet the adoption of agentic systems outpaces their governance: existing taxonomies of autonomy only offer discrete classifications, rely on subjective judgement, and cannot track autonomy across a system's life cycle, leaving enterprises unable to assess the risks of increasingly autonomous supply chain agents. This paper proposes the Agent

India is a vast nation of over 1.4 billion people, varied by hundreds of diverse and locally specific traditions and cultures and 22 officially recognized languages. Large language models (LLMs) are now being deployed on a massive scale throughout the mainland as well as in remote villages. However, the common benchmarks - MMLU, BIG-Bench, and TruthfulQA are almost exclusively English- and Western-centric. They do not identify those safety, fairness, and accuracy failures unique to the Indian co

Multi-agent systems improve capability through task decomposition and role specialization, but these same mechanisms introduce an important safety blind spot: a harmful objective can be fragmented into locally plausible subtasks, allowing malicious intent to evade detection by any single agent. This is a growing social-impact challenge: systems handling sensitive information or consequential tools can turn routine delegation into unauthorized disclosure or unsafe action. We argue that this failu

Auto-bidding systems optimize bids to maximize value under efficiency constraints such as Cost-Per-Action (CPA). Existing methods treat each day as an independent episode. However, many advertisers produce value so sparsely that per-day efficiency ratios become statistically unreliable, undermining advertiser retention. Platforms therefore evaluate window-level efficiency over sliding windows of $W{=}7$ days, ensuring fair evaluation and long-term advertising effectiveness. This creates cross-ep