The Trump administration launches Tech Force initiative to recruit 1,000 early-career technologists for AI modernization across federal agencies over two years.

Big Tech has lost its way. At WIRED's Big Interview event, Techdirt editor Mike Masnick and Common Tools CEO Alex Komoroske announced a manifesto designed to help the industry get back on track. Alex Komoroske has always been at odds with Big Tech's darker side. Though he cut his product-management teeth at Google and Stripe, he was never comfortable with the industry's increasing prioritization of profits over people. Once during his time at Google, he extolled the societal benefits of a project only to be met with, "Oh Alex, you'd be a VP by now if you just stopped thinking through the implications of your actions."

Sahil Lavingia, previously a DOGE operative at the Department of Veterans Affairs, is now a career employee at the IRS. He said at WIRED's Big Interview event that he expects to work there 10 years. Sahil Lavingia, the former member of Elon Musk's so-called Department of Government Efficiency (DOGE) first identified by WIRED, has a new job in government at the Internal Revenue Service (IRS). Lavingia joined the IRS in November. In a conversation at WIRED's Big Interview event with former acting commissioner of the Social Security Administration (SSA) Leland Dudek and David Foote, outside counsel for the US Institute of Peace, Lavingia said, "I'm working at IRS for online accounts."

This year, we've seen a real-time experiment playing out across the technology industry, one in which AI's software engineering capabilities have been put to the test against human technologists. And although 2025 may have started with AI looking strong, the transition from vibe coding to what's being termed context engineering shows that while the work of human developers is evolving, they nevertheless remain absolutely critical. This is captured in the latest volume of the " Thoughtworks Technology Radar," a report on the technologies used by our teams on projects with clients. In it, we see the emergence of techniques and tooling designed to help teams better tackle the problem of managing context when working with LLMs and AI agents. Taken together, there's a clear signal of the direction of travel in software engineering and even AI more broadly. After years of the industry assuming progress in AI is all about scale and speed, we're starting to see that what matters is the ability to handle context effectively.

After 25 years at the Electronic Frontier Foundation, Cindy Cohn is stepping down as executive director. In a WIRED interview, she reflects on encryption, AI, and why she's not ready to quit the battle. After a quarter century defending digital rights, Cindy Cohn announced on Tuesday that she is stepping down as executive director of the Electronic Frontier Foundation. Cohn, who has led the San Francisco-based nonprofit since 2015, says she will leave the role later this year, concluding a chapter that helped define the modern fight over online freedom. Cohn first rose to prominence as lead counsel in, the 1990s case that overturned federal restrictions on publishing encryption code. As EFF's legal director and later executive director, she guided the group through legal challenges to government surveillance, reforms to computer crime laws, and efforts to hold corporations accountable for data collection. Over the past decade, EFF has expanded its influence, becoming a central force in shaping the debate over privacy, security, and digital freedom. In an interview with WIRED, Cohn reflected on EFF's foundational encryption victories, its unfinished battles against National Security Agency (NSA) surveillance, and the organization's work protecting independent security researchers.

Jesse Armstrong loves to pull fictional stories out of reality. His universally acclaimed TV show Succession, for instance, was inspired by real-life media dynasties like the Murdochs and the Hearsts. Mountainhead, which releases on HBO on May 31 at 8 p.m. ET, portrays four top tech executives who retreat to a Utah hideaway as the AI deepfake tools newly released by one of their companies wreak havoc across the world. As the believable deepfakes inflame hatred on social media and real-world violence, the comfortably-appointed quartet mulls a global governmental takeover, intergalactic conquest and immortality, before interpersonal conflict derails their plans. Armstrong tells TIME in a Zoom interview that he first became interested in writing a story about tech titans after reading books like Michael Lewis' Going Infinite (about Sam Bankman-Fried) and Ashlee Vance's Elon Musk: Tesla, SpaceX, and the Quest for a Fantastic Future, as well as journalistic profiles of Peter Thiel, Marc Andreessen, and others. He then built the story around the interplay between four character archetypes--the father, the dynamo, the usurper, and the hanger-on--and conducted extensive research so that his fictional executives reflected real ones.

Robin K. Hill Is Computer Science a Profession? We computer scientists--many of us--like to think of ourselves as professionals, as do doctors and lawyers, and police officers, and accountants. But there are definitions of "profession," with criteria and expectations, that we fail to meet. Are we ready, collectively, to confront the criteria? Do we want to be card-carrying members of a learned institution of service?

If you have tips about DOGE and its data collection, you can contact Ian and Charlie on Signal at @ibogost.47 and @cwarzel.92. If you were tasked with building a panopticon, your design might look a lot like the information stores of the U.S. federal government--a collection of large, complex agencies, each making use of enormous volumes of data provided by or collected from citizens. The federal government is a veritable cosmos of information, made up of constellations of databases: The IRS gathers comprehensive financial and employment information from every taxpayer; the Department of Labor maintains the National Farmworker Jobs Program (NFJP) system, which collects the personal information of many workers; the Department of Homeland Security amasses data about the movements of every person who travels by air commercially or crosses the nation's borders; the Drug Enforcement Administration tracks license plates scanned on American roads. More obscure agencies, such as the recently gutted Consumer Financial Protection Bureau, keep records of corporate trade secrets, credit reports, mortgage information, and other sensitive data, including lists of people who have fallen on financial hardship. A fragile combination of decades-old laws, norms, and jungly bureaucracy has so far prevented repositories such as these from assembling into a centralized American surveillance state. But that appears to be changing. Since Donald Trump's second inauguration, Elon Musk and the Department of Government Efficiency have systematically gained access to sensitive data across the federal government, and in ways that people in several agencies have described to us as both dangerous and disturbing.

At least dozens of workers for the Technology Transformation Services, housed within the General Services Administration, were fired Wednesday afternoon, sources tell WIRED. The sudden cuts seemingly targeted probationary and short-term staffers, including workers supplied by the Presidential Innovation Fellowship program, which brings skilled technologists from the private sector to work in government for a few years at a time. Around 50 of the 70 members of the US Digital Corps, an early-career two-year government fellowship, were terminated as well, sources say. Sources also tell WIRED that TTS management met with workers individually prior to the terminations, giving them one last chance to take the deferred resignation offered in the "Fork In the Road" email late last month. One TTS staffer called the meetings "coercive for sure."

The Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24) was held in San Jose, California from October 21-23, 2024. During the opening session of the conference, the best paper award winners were announced. Abstract: In response to rising concerns surrounding the safety, security, and trustworthiness of Generative AI (GenAI) models, practitioners and regulators alike have pointed to AI red-teaming as a key component of their strategies for identifying and mitigating these risks. However, despite AI red-teaming's central role in policy discussions and corporate messaging, significant questions remain about what precisely it means, what role it can play in regulation, and how it relates to conventional red-teaming practices as originally conceived in the field of cybersecurity. In this work, we identify recent cases of red-teaming activities in the AI industry and conduct an extensive survey of relevant research literature to characterize the scope, structure, and criteria for AI red-teaming practices.