Christopher Marquis is a professor at the University of Cambridge and the author of The Profiteers. In 1930, in the depths of the Great Depression, John Maynard Keynes wrote a short essay called . It is often remembered for one striking prediction: by 2030, people in wealthy countries might only need to work about 15 hours a week. What Keynes imagined was a society advanced enough to solve what he called the "economic problem" of basic material provision. If technology kept improving, and societies kept growing richer, then fewer hours of human labor would be needed to produce the necessities and comforts of life.

An AI facial recognition tool that aims to detect adult migrants posing as children will be deployed at the UK's borders next year. A software company has been awarded a contract to develop and test the technology, which will estimate a person's age by analysing photographs of them taken at the border. The Home Office says the technology will make it easier to identify adult migrants attempting to game the system, after initial testing indicated promising performance and accuracy. But Human Rights Watch urged the government to scrap the scheme, describing it as unproven technology that will undermine the protections vulnerable children are entitled to. Unaccompanied child migrants are processed through the care system rather than the asylum system, which can make it easier to stay in the country.

PCWorld highlights that Windows 11's default firewall lacks proper outgoing connection monitoring, allowing programs to send data unchecked and potentially exposing users to malware communication. The article covers essential security tweaks including enabling DNS over HTTPS encryption, activating Microsoft Defender Network Protection, and disabling obsolete protocols like NetBIOS and LLMNR. Implementing these network hardening measures transforms Windows into a more controlled system that blocks unauthorized connections and protects against credential interception attacks. Windows' built-in network protection is like a front door that is locked from the outside, but through which any resident can carry valuables outside without being checked. By default, Microsoft allows almost any program to send data out without being checked -- this is known as a lack of egress filtering. If you want to know which apps are sending data back to their developers, or wish to prevent malware from contacting its command server -- the so-called command-and-control instance -- in the event of an attack, you need to tighten the reins. With the right filters and targeted protocol hardening, you can transform the open Windows data highway into a strictly controlled border crossing that checks every outgoing packet thoroughly.

PCWorld outlines five essential Windows Defender configuration changes to optimize security and performance on new Windows PCs. Key adjustments include disabling redundant system tray icons, turning off unnecessary "no threats found" notifications, and enabling Controlled Folder Access for ransomware protection. Strategic exclusions for trusted files and adjusting Core Isolation settings can improve performance while maintaining robust built-in antivirus protection. Windows Defender is a capable antivirus solution built into Windows itself. Unless you've installed a different antivirus program on your Windows 11 or Windows 10 PC, your PC is using it right now.

Roughly 500 labour groups across the United States have organised a widespread economic blackout calling for "no school, no work, no shopping" to mark May Day, also known as International Workers' Day. The events, organised as part of an initiative called May Day Strong, were inspired by economic boycotts following ramped-up immigration enforcement operations in Minneapolis, Minnesota, and the deaths of US citizens Renee Good and Alex Pretti in January. May Day Strong has a broad set of demands, including "tax the rich" and abolishing Immigration and Customs Enforcement (ICE) -- a call that comes as Republicans voted on Wednesday on a budgetary measure that would fund the agency under the Department of Homeland Security. It also calls for ending war and "expanding democracy", according to a statement from the group. While the tent is broad in nature, organisers stressed that it is a result of a wide set of challenges facing the US worker.

Deep Gradient Leakage (DGL) is a highly effective attack that recovers private training images from gradient vectors. This attack casts significant privacy challenges on distributed learning from clients with sensitive data, where clients are required to share gradients. Defending against such attacks requires but lacks an understanding of when and how privacy leakage happens, mostly because of the black-box nature of deep networks. In this paper, we propose a novel Inversion Influence Function (I2F) that establishes a closed-form connection between the recovered images and the private gradients by implicitly solving the DGL problem. Compared to directly solving DGL, I2F is scalable for analyzing deep networks, requiring only oracle access to gradients and Jacobian-vector products. We empirically demonstrate that I2F effectively approximated the DGL generally on different model architectures, datasets, modalities, attack implementations, and perturbation-based defenses. With this novel tool, we provide insights into effective gradient perturbation directions, the unfairness of privacy protection, and privacy-preferred model initialization.

Causal mediation analysis provides techniques for defining and estimating effects that may be endowed with mechanistic interpretations. With many scientific investigations seeking to address mechanistic questions, causal direct and indirect effects have garnered much attention. The natural direct and indirect effects, the most widely used among such causal mediation estimands, are limited in their practical utility due to stringent identification requirements. Accordingly, considerable effort has been invested in developing alternative direct and indirect effect decompositions with relaxed identification requirements. Such efforts often yield effect definitions with nuanced and challenging interpretations. By contrast, relatively limited attention has been paid to relaxing the identification assumptions of the natural direct and indirect effects. Motivated by a secondary aim of a recent non-randomized vaccine prospective cohort study (NCT05168813), we present a set of relaxed conditions under which the natural direct effect is identifiable in spite of unobserved baseline confounding of the exposure-mediator pathway; we use this result to investigate the effect mediated by putative immune correlates of protection. Relaxing the commonly used but restrictive cross-world counterfactual independence assumption, we discuss strategies for evaluating the natural direct effect in non-randomized settings that arise in the analysis of vaccine studies. We revisit prior studies of semi-parametric efficiency theory to demonstrate the construction of flexible, multiply robust estimators of the natural direct effect and discuss efficient estimation strategies that do not place restrictive modeling assumptions on nuisance functions.

Availability attacks provide a tool to prevent the unauthorized use of private data and commercial datasets by generating imperceptible noise and crafting unlearnable examples before release. Ideally, the obtained unlearnability can prevent algorithms from training usable models. When supervised learning (SL) algorithms have failed, a malicious data collector possibly resorts to contrastive learning (CL) algorithms to bypass the protection.Through evaluation, we have found that most existing methods are unable to achieve both supervised and contrastive unlearnability, which poses risks to data protection by availability attacks.Different from recent methods based on contrastive learning, we employ contrastive-like data augmentations in supervised learning frameworks to obtain attacks effective for both SL and CL.Our proposed AUE and AAP attacks achieve state-of-the-art worst-case unlearnability across SL and CL algorithms with less computation consumption, showcasing prospects in real-world applications. The code is available at https://github.com/EhanW/AUE-AAP.

"If you are interested in helping shape and deliver the next chapter of Palantir's work across DHS, please reach out," a Palantir executive wrote to employees about the massive purchasing agreement. The Department of Homeland Security struck a $1 billion purchasing agreement with Palantir last week, further reinforcing the software company's role in the federal agency that oversees the nation's immigration enforcement . According to contracting documents published last week, the blanket purchase agreement (BPA) awarded "is to provide Palantir commercial software licenses, maintenance, and implementation services department wide." The agreement simplifies how DHS buys software from Palantir, allowing DHS agencies like Customs and Border Protection (CBP) and Immigration and Customs Enforcement (ICE) to essentially skip the competitive bidding process for new purchases of up to $1 billion in products and services from the company. Palantir did not immediately respond to a request for comment.

From threat modeling to encrypted collaboration apps, we've collected experts' tips and tools for safely and effectively building a group--even while being targeted and tracked by the powerful. Rarely in modern US history have so many Americans opposed the actions of the federal government with so little hope for a top-down political solution. That's left millions of people seeking a bottom-up approach to resistance: grassroots organizing. Yet as Americans assemble their own movements to protect and support immigrants, push back against the Department of Homeland Security's dangerous incursions into cities, and protest for civil rights and policy changes, they face a federal government that possesses vast surveillance powers and sweeping cooperation from the Silicon Valley companies that hold Americans' data. That means political, social, and economic organizing presents a risky dilemma. How do you bring people of all ages, backgrounds, and technical abilities into a mass movement without exposing them to monitoring and targeting by a government--and in particular Immigration and Customs Enforcement and Customs and Border Protection, agencies with paramilitary ambitions, a tendency to break the law, and more funding than some countries' militaries. Organizing safely in an age of surveillance increasingly requires not only technical security know-how, but also a tricky balance between secrecy and openness, says Eva Galperin, the director of cybersecurity at the Electronic Frontier Foundation, a nonprofit focused on digital civil liberties.