Large language models (LLMs) often generate content that contains factual errors when responding to fact-seeking prompts on open-ended topics. To benchmark a model's long-form factuality in open domains, we first use GPT-4 to generate LongFact, a prompt set comprising thousands of questions spanning 38 topics. We then propose that LLM agents can be used as automated evaluators for longform factuality through a method which we call Search-Augmented Factuality Evaluator (SAFE). SAFE utilizes an LLM to break down a long-form response into a set of individual facts and to evaluate the accuracy of each fact using a multi-step reasoning process comprising sending search queries to Google Search and determining whether a fact is supported by the search results. Furthermore, we propose extending F1 score as an aggregated metric for long-form factuality.

For each prediction task, we select features that have a causal influence on the target of prediction.

Exploring large corpora can generate useful discoveries but is time-consuming for humans. We formulate a new task, D5, that automatically discovers differences between two large corpora in a goal-driven way. The task input is a problem comprising a user-specified exploration goal ("comparing the side effects of drug A and drug B") and a corpus pair (collections of patients' self-reported reactions after taking each drug). The output is a goal-relevant description (discovery) of how these corpora differ (patients taking drug A "mention feelings of paranoia" more often).

On a Wednesday morning last month, I thought, just for a second, that AI was going to kill me. I had hailed a self-driving Waymo to bring me to a hacker house in Nob Hill, San Francisco. Just a few blocks from arrival, the car lurched toward the other lane--which was, thankfully, empty--and immediately jerked back. That sense of peril felt right for the moment. As I stepped into the cab, Federal Reserve Chair Jerome Powell was delivering a speech criticizing President Donald Trump's economic policies, and in particular the administration's sweeping on-again, off-again tariffs. A day earlier, the White House had claimed that Chinese goods would be subject to overall levies as high as 245 percent when accounting for preexisting tariffs, and the AI giant Nvidia's stock had plummeted after the company reported that it expected to take a quarterly hit of more than 5 billion for selling to China.

A United States Customs and Border Protection request for information this week revealed the agency's plans to find vendors that can supply face recognition technology for capturing data on everyone entering the US in a vehicle like a car or van, not just the people sitting in the front seat. And a CBP spokesperson later told WIRED that the agency also has plans to expand its real-time face recognition capabilities at the border to detect people exiting the US as well--a focus that may be tied to the Trump administration's push to get undocumented people to "self-deport" and leave the US. WIRED also shed light this week on a recent CBP memo that rescinded a number of internal policies designed to protect vulnerable people--including pregnant women, infants, the elderly, and people with serious medical conditions--while in the agency's custody. Signed by acting commissioner Pete Flores, the order eliminates four Biden-era policies. Meanwhile, as the ripple effects of "SignalGate" continue, the communication app TeleMessage suspended "all services" pending an investigation after former US national security adviser Mike Waltz inadvertently called attention to the app, which subsequently suffered data breaches in recent days.

United States Customs and Border Protection plans to log every person leaving the country by vehicle by taking photos at border crossings of every passenger and matching their faces to their passports, visas, or travel documents, WIRED has learned. The escalated documentation of travelers could be used to track how many people are self-deporting, or leave the US voluntarily, which the Trump administration is fervently encouraging to people in the country illegally. CBP exclusively tells WIRED, in response to an inquiry to the agency, that it plans to mirror the current program it's developing--photographing every person entering the US and match their faces with their travel documents--to the outbound lanes going to Canada and Mexico. The agency currently does not have a system that monitors people leaving the country by vehicle. "Although we are still working on how we would handle outbound vehicle lanes, we will ultimately expand to this area," CBP spokesperson Jessica Turner tells WIRED.

Just three months into the Trump administration's promised crackdown on immigration to the United States, Immigrations and Customs Enforcement now has a 30 million contract with Palantir to build a "near-real time" surveillance platform called ImmigrationOS that would track information about people self-deporting (electing to leave the US). Meanwhile, the Department of Homeland Security has been sending aggressive emails telling people with temporary legal status to leave the US. It is unclear who has actually been sent the messages, though, given that a number of people who are US-born citizens have reported receiving them. The US Cybersecurity and Infrastructure Security Agency briefly seemed poised this week to cancel funding for the critical software vulnerability tracking project known as the CVE Program. CISA eventually came through with the funding, but some members of the CVE Program's governing board are planning to make the project into an independent nonprofit.

The United States under President Donald Trump is ramping up use of surveillance systems and artificial intelligence (AI) to track and arrest immigrants, raising fears that risks to accuracy and privacy could put almost anyone in danger of getting caught up in the crackdown. The Department of Homeland Security (DHS) and other immigration control agencies are using a suite of AI tools -- such as facial recognition scanners in public areas and robotic dogs patrolling the southern border for human movement -- as part of the crackdown on alleged illegal immigration. Many of the AI tools that immigration agents are using have been in place for years and are a legacy of previous administrations, according to Saira Hussain, an attorney at the Electronic Frontier Foundation, a digital rights advocacy group.