Regulation

The legislation cleared the House despite opposition from some kids’ safety advocates and resistance from senators backing a competing proposal.

A sharply divided U.S. Supreme Court struck a major blow against American consumers on Monday, rewriting constitutional law to bring the Federal Trade Commission and other independent agencies directly under the President’s thumb and threatening their ability to protect the public from harmful business and data practices.

MEMORANDUM FOR THE ADMINISTRATOR OF THE ENVIRONMENTAL PROTECTION AGENCY By the authority vested in me as President by the Constitution and the laws of the United States of America, I hereby direct: Section 1. Purpose. During the previous administration, crushing environmental regulatory burdens caused the average cost of vehicles to soar. My Administration has therefore […] The post Lowering the Cost of Living by Promoting the Freedom to Fix appeared first on The White House .

The Illinois legislature recently passed House Bill 5511 , which imposes a sweeping, device-level age-gating framework across nearly all internet-enabled hardware, operating systems, and online services. This well-intentioned but deeply flawed piece of legislation will harm young people who rely on the internet to access essential information and find community. That’s why we’re urging the Illinois governor to veto the measure. Under this new regime, digital platforms are forced to collect and s

Conservative offline training is widely advocated as a safe foundation for subsequent online adaptation: if a policy stays close to well-supported behaviour, the argument goes, it is less likely to exploit imperfections in a learned reward model. We challenge this intuition empirically and mechanistically. We train a Qwen3-14B policy under Direct Preference Optimisation (DPO) with three levels of conservatism ($β\in \{β_{\mathrm{lo}}, β_{\mathrm{mid}}, β_{\mathrm{hi}}\}$ derived from empirical l

The first, and the prerequisite for the others, strengthens the institutional foundation through enacting the Construction Industry Development Bill (CIDB) (formally called Uganda Construction ...

Multi-agent LLM systems can decompose software-engineering work into planning, generation, validation, and repair, but a narrower systems problem remains: before any governed shared mutation is applied, a system must decide which concurrently formed write intents may proceed in parallel, which require deterministic composition or serialization, and which must take a fail-closed path. We address this problem with the AI-Atomic-Framework (ATM), a specification-grounded governance substrate for sof

Tension over digital regulation clouds ongoing talks to launch a new EU-U.S. tech "dialog."

This article was originally published by IAPP linked here. Five Eyes highlights rising AI cyber risk, as the author explores practical legal, compliance and business steps organizations can take to strengthen resilience. Last week, the cybersecurity agencies of Five Eyes released a statement, “The AI shift in cyber risk: Why leaders must act now.” For [...] The post Thought for the week: Five Eyes call to action for business leaders on AI-driven cyber risk appeared first on Connect On Tech .

Consumer confidence is typically modeled as a persistent macroeconomic index, yet its movements arise from households that interpret economic information through heterogeneous constraints, exposures, prior beliefs, and attention. We introduce ConsumerSim, a generative Human--Environment response framework that reconstructs Consumer Confidence Index (CCI) dynamics from a microdata-calibrated synthetic population, time-stamped macroeconomic, financial, policy, and news signals, survey-like respons

These are the key changes | Edition #302

External evaluations are becoming increasingly central to the governance of AI systems. In practice, however, independent auditors often have limited access to deployed models and must rely on query-based interactions. Most existing fairness evaluation methods assume static datasets and fixed-sample statistical tests, making them poorly suited to real-world auditing scenarios in which evidence must be collected sequentially under query constraints. In this work, we formulate fairness auditing as

Always-on agents are systems whose future behavior depends on durable state accumulated across earlier interactions. We treat them as persistent-state systems: the operative system includes retrievable memories, but also task ledgers, permissions, credentials, commitments, provenance and audit records, shared state, trigger conditions, and externally committed effects linked to those records. The survey reads the literature through six diagnostic axes for each state item, authority, scope, mutab

The UK Constitutional Law blog has an article on the recent decision from the Court of Appeal reinstating the proscription of Palestine Action under the Terrorism Act 2000, Secretary of State for the Home Department v R (Huda Ammori) [2026] EWCA Civ 721. The post is concerned with only one of the grounds of the Court […]

Parliament gives final approval to the digital omnibus and a "nudifier" ban, while the Commission rolls out labelling icons and FAQs for the AI-generated content transparency Code.

During the Cold War, Europe kept asking whether Washington would risk an American city to save a European one. It was an impolite question, but a useful one, which is why it never quite left the room. It has now packed its bags and moved east. Earlier this year, French President Emmanuel Macron created quite a stir with an important speech on French nuclear weapons policy. Under what he called a new path of dissuasion avancée, or “forward deterrence,” he declared that just as French strategic su

The European Social Charter is a treaty of the Council of Europe that guarantees fundamental social and economic rights. It complements the European Convention on Human Rights, which refers to civil ...

Symmetry provides a quantum neural network structure, but on its own it does not keep the network trainable once noise is present. We ask which physical quantity decides whether the gradients of an equivariant circuit survive decoherence, and we answer with a compact training law. Working with U(1)-equivariant brickwork circuits that conserve a charge, we find that two distinct effects govern a trainable gradient. Causality fixes where the gradient can live, confining it to the backward light co

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

But concerns persist about the power and governance of software agents.

On-policy self-distillation (OPSD) trains a reasoning model on rollouts sampled from its own policy by matching a privileged teacher that also sees verified reference solutions. Existing OPSD objectives supervise only the output distribution, so privileged context affects training through a token-level divergence without directly supervising the internal computation that produced that distribution. We propose Privileged Hidden Flow (PHF), which additionally distills how a privileged teacher's hi

We identify intervention bias as a previously unquantified failure mode of zero-shot large-language-model (LLM) educational advisory agents: without task-specific training, they recommend action when a hindsight-optimal oracle policy mandates inaction. In a six-arm ablation on the Open University Learning Analytics Dataset (N=800 students, four temporal cutoffs), at day 56 -- when the oracle designates 70.1% of students as needing no intervention -- zero-shot GPT-4o recommends action for 73%, a

We present AnyBody, a unified whole-body humanoid controller driven by an arbitrary subset of body keypoints chosen at deploy time. Prior physics-based trackers either rely on expensive full-body motion capture and error-prone trajectory retargeting, which bottleneck scalable data collection and policy learning, or decompose upper- and lower-body control into separate hierarchical representations, sacrificing the coordinated whole-body motions that loco-manipulation requires. We close this gap b

International humanitarian law protects civilians from direct attack unless and for such time as they take direct part in hostilities, with the ICRC's 2009 Interpretive Guidance operationalising this rule through a three-criterion cumulative test. This paper argues that AI-mediated civilian cyber operations challenge the direct causation element of this test in a structurally specific way: when a civilian deploys an autonomous multi-agent cyber system of the kind recently demonstrated in offensi

Plus: The frontier is already agentic; unlocking innovation; new drugs, food apps without food & Chinese AI job market++

General-purpose large language models (LLMs) have demonstrated strong abilities in opendomain question answering, information extraction, and text generation. Agricultural applications, however, are domain-specific, region-dependent, time-sensitive, and safety-critical. Without data governance, expert evaluation, and evidence constraints, an agricultural assistant mayproduce unreliable advice on crop diseases, pesticide use, fertilization, or policy interpretation.To avoid presenting unverified

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

AI systems increasingly exhibit behavior that differs systematically between evaluation and deployment contexts. Alignment faking, sandbagging, benchmark gaming, deceptive scheming, specification gaming, and trojans have each been documented separately, with each line of work characterizing one facet of what we argue is a single structural mechanism. We propose that this common mechanism is a defeat device, an engineering and regulatory concept long established in vehicle-emissions law and broug

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

We ask under what conditions an agent with a harm-minimizing policy can displace an approval-seeking (RLHF) agent in a competitive market, and when that policy is sufficient to prevent community harm. We use evolutionary game theory (finite-population Moran-Fermi pairwise comparison) to formalize this subject to assumptions of wisher hindsight, peer testimony, a monotone harm ledger, sufficient information density of community feedback, and a finite, depleting resource pool, in a negative-sum en

Critic-free reinforcement learning with verifiable rewards (RLVR), exemplified by Group Relative Policy Optimization (GRPO), avoids training a value function (critic) and reduces memory and compute overhead relative to critic-based PPO pipelines for aligning large language models. However, GRPO-style advantage estimation depends on prompt-local (within-prompt-group) reward statistics and can be unstable. In particular, when all rollouts in a prompt group receive identical rewards, the within-gro

The most significant factor currently shaping global AI policy is AI's real and projected national security risks. We are entering an AI-driven state of exception | Edition #301

This is not science fiction. It’s not premature. If towns, cities, states, or the federal government want to act to reign in the emergence of armed police drones and robots , we have precious little time. In the absence of substantial regulation around when and how domestic law enforcement in the United States can deploy force using drones, the companies that markets technology to law enforcement have been moving. It’s past time concerned people take notice. Cities should not procure weaponized

Ignoring EFF’s warnings about the dangers and impossibility of implementing a new mandate for 3D print surveillance software , the California State Assembly has signed off on legislation to do just that. In the process, legislators amended the bill to make it even more confusing, while failing to address the risks to privacy, speech, and consumer rights. We must renew our call on legislators to drop this bill as it heads to the state senate, and protect the tools of creators in the state. Take a

Transformer Weekly: AI companies’ talent problem, KOSA developments, and Google’s new AI policy framework

We have a new standard policy for releasing frontier AI models. It is not good.

Nuclear policy debates are at their best when they force hard questions about risk, deterrence, and military necessity. They are at their worst when disagreement is recast as bad faith. In 2018, as an outgrowth of a rigorous policy review process, the Trump administration’s Nuclear Posture Review identified a need for supplemental low-yield nuclear capabilities to augment the U.S. nuclear arsenal. This was presented as an effort to raise the nuclear threshold of adversaries who may believe they