Privacy

Personal agents are becoming persistent user-owned intermediaries: they remember preferences, filter platform-mediated information, use tools, and negotiate with services. Existing benchmarks evaluate tool use, web navigation, desktop control, personalization, recommendation, and evolving context, but rarely ask whether an agent preserves user sovereignty: advancing the user's current interests while respecting privacy, consent, evidence, user burden, and resistance to manipulative incentives. W

Anthropic accused of spying on users; engineer says “experiment” is over.

Congress is closer than ever to rewriting the rules for young people online. Just last week, the House of Representatives passed the KIDS Act, which includes a revised version of the Kids Online Safety Act (KOSA) and the Children’s Online Privacy Protection Act (COPPA) 2.0. Most of the public debate has centered on what these […] The post Should Have Known Is the Wrong Standard for Kids’ Safety Laws appeared first on Center for Democracy and Technology .

This article was originally published by IAPP linked here. The U.S. Supreme Court’s Slaughter decision may complicate the future of the EU-U.S. Data Privacy Framework, making preparedness and business continuity planning increasingly important. In Thursday’s World Cup match between Portugal and Croatia, Croatia held a 1-0 lead until the 68th minute. Then, things changed. Croatia’s [...] The post Thought for the week: What Slaughter and a World Cup penalty have in common appeared first on Connect

Big Data & Society, Volume 13, Issue 3, July-September 2026. This article examines AI-based video surveillance systems in public spaces. We investigate a case of AI-based camera technology designed to detect falls into the water and prevent drowning accidents at the harbor front of a large Scandinavian city. This ...

This article examines the institutional conditions under which artificial intelligence systems in U.S. welfare administration come to operate as instruments of support or as instruments of control. Rather than asking what welfare algorithms "really" are (tools of proactive assistance or infrastructures of surveillance) the article starts from the premise that support and control are co-present within the same system, while their relative balance shifts over time. This movement is conceptualized

A landmark case is forcing Brussels to decide whether opening Google's search data to rivals can boost competition without undermining Europeans’ privacy.

Federated learning (FL) enables multi-institutional collaboration in medical imaging while preserving patient privacy, yet its fairness landscape remains fragmented: existing methods predominantly address either collaboration fairness (equitable performance across institutions) or group fairness (equitable outcomes across demographic subgroups), but rarely both. In this systematic review, we adopt dual fairness —the joint satisfaction of both dimensions—as the analytical lens for organizing and

Visual object tracking is a fundamental problem in computer vision. Traditional tracking methods, which primarily rely on RGB imagery, often face difficulties in complex scenarios such as low resolution and background clutter. Hyperspectral imaging, which captures both spatial and spectral information across multiple narrow spectral bands, has emerged as a promising solution. However, hyperspectral tracking suffers from challenges including the complexity of spatial-spectral-temporal modeling, t

Detecting mental health disorders in a timely manner is an important societal challenge. NLP and machine learning (ML) methods used to assist with detection rely on data collected primarily from social media. However, such datasets often have sampling biases and inherent ethical and privacy issues. One avenue to overcome these limitations is non-social media data. We present the first comprehensive review of non-social media, free-text datasets for mental health research. We use the PRISMA metho

Decentralised federated learning, based on peer-to-peer communication, is increasingly proposed for on-device training of machine learning models, promising a privacy-preserving, communication-efficient training process with no risk of single-point failure. However, the role of structural and temporal inhomogeneities in such fully decentralised settings remains poorly understood. Here, we investigate their effects when model parameters are locally averaged during aggregation. We show that the de

Explainability is central to building trustworthy AI, yet explanation interfaces can inadvertently provide adversaries with an expanded privacy-related attack surfaces. Recent studies show that advanced membership-inference attacks succeed by exploiting confidence-drop trajectories, induced through attribution-guided perturbations, as discriminative features, rather than directly using confidence scores or explanation vectors. Existing defenses against membership inference fail to directly mitig

Leadership computing facilities steward large-scale scientific datasets that routinely require substantial transformation before serving as AI training data. However, no existing framework fully unifies automated transformation, readiness assessment, provenance tracking, and agent-native deployment. We present REDI, an open-source framework that addresses this gap through a unified five-stage pipeline (ingest, preprocess, transform, structure, and output) with per-stage instrumentation for repro

Scott’s foreword: Cynthia Dwork is Gordon McKay Professor of Computer Science at Harvard, and a pioneer in the fields of differential privacy and algorithmic fairness. On my recent travels to the SigmaWest science camp and then STOC, there was much talk about a recent Trump administration action that would ban not only differential privacy, but […]

New Jersey Governor Mikie Sherrill has signed A5328, banning the sale of sensitive data and creating a data broker registry in New Jersey. The ban on sale applies to all forms of sensitive data under the New Jersey Data Privacy Act and applies to all entities regardless of the number of consumers whose data the … Continued

X Corp. should not be able to escape privacy compliance because it changed its name. On May 15, X Corp. filed a petition before the Federal Trade Commission (FTC) to set aside or modify an order issued in 2022 requiring the company to report regularly to the FTC for its violations of user data. The order or “consent decree” is a result of misleading the platforms’ 140 million users by using private information given to secure accounts, like phone numbers and email addresses, for targeted adverti

FTC urged to reject Elon Musk’s bid to end X monitoring amid AI concerns.

Distributed machine learning enables collaborative model training without centralizing data, but it also exposes learning processes to privacy leakage and malicious manipulation. Existing defenses typically address these threats in isolation and are often tailored to specific learning paradigms or model architectures, limiting their applicability in realistic deployments. In particular, federated learning and decentralized learning exhibit distinct adversarial surfaces that are rarely addressed

Tencent today launched Just Dance: Party, a mobile rhythm game based on Ubisoft’s Just Dance franchise, across iOS, Android and HarmonyOS devices. The game uses a proprietary AI-powered skeletal tracking algorithm that enables full-body motion capture through a smartphone’s front-facing camera, eliminating the need for external accessories such as dance mats or motion controllers. Players […]

Yesterday, EPIC filed comments in response to the California Department of Justice’s proposed rules to implement the Protecting Our Kids from Social Media Addiction Act (SB 976). EPIC commended California for the proposed rules, which align strongly with the privacy- and speech-protective principles for age assurance implementation that EPIC urged the state to follow in a comment submitted last year. In this latest round of comments, EPIC recommended additional tweaks to further enhance privacy

Intrusion Detection Systems (IDSs) are essential for monitoring network traffic and identifying malicious activities in modern cyber-physical, Internet of Things (IoT), enterprise, and distributed network environments. However, developing reliable IDS models remains challenging because attack behaviors evolve over time, realistic datasets are difficult to obtain, traffic records may be incomplete, attack classes are often imbalanced, and privacy constraints limit centralized data collection. Rec

Last night, the New Jersey Legislature passed the Fair Price Protection Act, a law banning surveillance pricing for groceries.

Trump's power to fire regulators undermines independent oversight, European privacy groups argue.

Understanding case law evolution contributes to the comprehension of legal principles, the identification of trends in judicial reasoning, and testing consistency between judgments. Automation of the analysis has the potential to make it easier to keep up with relevant case law. While legal network analysis typically focuses on identifying precedents, it has largely overlooked tracking historical developments in judicial reasoning. This study applies Main Path Analysis (MPA) to legal citation ne

On Friday, June 26, EPIC filed an amicus brief alongside civil liberties and criminal defense organizations in New York v. Morris, an important case about cell phone privacy rights during criminal investigations. The brief was filed with the American Civil Liberties Union, the New York Civil Liberties Union, the Legal Aid Society, the Center for … Continued

Washington DC – Today, the Electronic Privacy Information Center (EPIC) announced the addition of four new members to its Advisory Board. Since its establishment, EPIC’s work has been informed by the expertise of leading scholars, experts, and advocates in the fields of privacy, technology policy, and digital rights. We are excited to see the expansion of … Continued

Visiting Scholar Alicia Solow-Niederman identifies "inter-regime doctrinal collapse," a source of legal strain by which the boundaries between information privacy law and copyright law become ...

The Internet of Things (IoT) is rapidly growing and expanding into various sectors, such as healthcare, transportation, smart homes, and more. Despite the benefits of using IoT devices, they present several challenges. Given the significant role these devices play in our lives, it is crucial to address issues related to their security and privacy. These devices are limited in resources, which complicates their security and the protection of the data that they manage. The paper aims to examine in

The World Cup is bringing visitors and AI-driven surveillance systems, but only one of those is certain to leave when the games are done.

If you’ve seen reports of a wildfire in your region and you’re looking for open source data, NASA’s fire-tracking tool is often the first place to start. It provides a heat signature and an approximate location. But detection is only the first step in understanding what’s happened. In this guide, we explore ways to analyse […] The post Burning Forests: Tools for Tracking and Reporting Wildfire Damage appeared first on bellingcat .

The Supreme Court ruled today that geofence searches violate a reasonable expectation of privacy under the Fourth Amendment.

The Supreme Court ruled today that geofence searches violate a reasonable expectation of privacy under the Fourth Amendment.

Does life feel Orwellian sometimes? One researcher has a solution for you: graphic tees that confuse the neural networks in surveillance cameras.

You have an expectation of privacy in location data that reveals your movements in the physical world, and even short-term surveillance of these movements is a search subject to the Fourth Amendment, the U.S. Supreme Court ruled today in Chatrie v. United States . The case involved geofence warrants, a form of dragnet surveillance police have used to vacuum up location data from electronic devices of people who happen to be in the vicinity of a crime. EFF had joined the American Civil Liberties

Human companionship is an essential capability for mobile robots operating in dynamic, human-centered environments. It enables robots to perform tasks such as guidance, assistance, surveillance, and service delivery across various domains, including healthcare, logistics, and public safety. The recent advances in artificial intelligence (AI), particularly in computer vision, deep learning, and sensor fusion, have significantly improved the reliability, adaptability, and contextual understanding

Software practitioners use online forums to navigate complex and often ambiguous legal privacy requirements, yet little is known about their professional backgrounds, what challenges they face, and how they use and assess the credibility of the advice received, or how they resolve ambiguities in posts. We report the findings of a survey of 223 Reddit users from regulatory-focused subreddits, complemented by a qualitative analysis of 2,248 posts and responses. Our results show that, despite holdi

Ovarian cancer is frequently diagnosed at an advanced stage, making preoperative contrast-enhanced computed tomography (CT) central to staging and surgical planning; yet the scarcity of annotated imaging data, compounded by privacy regulations, limits the development of generalizable computational models in this domain. Text-conditioned 3D CT synthesis has shown promise, but existing pipelines depend on paired radiology reports and have been evaluated only on chest CT. We propose OvESyn (Ovarian

The advance of these technologies is not occurring as an exception. They are established silently, without public debate, without transparency and without people knowing the fate of their data

Artificial intelligence reaches the land registry not as another tool but as a value chain that turns data into intelligence and intelligence into economic value. This paper argues that the decisive legal move is to place validity, a functional, second-order concept, at the centre of that chain. Rights, liability and supervision organise around it. It traces three impacts.Registry information becomes smart data, governed simultaneously by registry law, the GDPR, the European data acts and the AI

Smart medication systems increasingly automate medication recognition, reminders, and logging. However, automation in home medication routines should be carefully bounded, as users may have different capabilities, privacy expectations, and needs for control over decisions. We present a mixed-methods study of a Smart Medication Support system comparing three automation conditions: confirmation required, automatic logging with undo, and fully automatic support. Across 53 participants and interview