Regulation

Reinforcement Learning (RL) has emerged as a powerful paradigm for adaptive traffic signal control. However, in safety-critical infrastructure like traffic control, the opaque, black-box nature of deep RL models poses challenges for transportation agency acceptance, regulatory compliance, operational trust, troubleshooting, and fine-tuning. To bridge this gap between high-performance optimization and human-comprehensible interpretability, this effort introduces a novel, explainable entity centri

The American A.I. Sovereign Wealth Fund Act rests on a sweeping claim about the ownership of value created by artificial intelligence. Because AI models are trained on data generated by the public, the bill treats the resulting gains as a public resource subject to state control and redistribution. Sen. Bernie Sanders’ (I-Vt.) proposal would require ... The Fatal Conceit Gets a GPU Cluster: Bernie Sanders’ Plan to Socialize AI The post The Fatal Conceit Gets a GPU Cluster: Bernie Sanders’ Plan t

Frontier-AI governance today faces a problem structurally analogous to the one banking regulation faced pre-2008, and which post-2008 reforms (Basel III, Dodd-Frank) have since addressed. Two gaps recur: discovering a risk is not tantamount to acting on it, and individual-model review is unlike managing correlated build-up across the sector. Drawing on the Basel III framework and the U.S. financial-stability architecture, I propose a macro-prudential early warning and response system ("MEWRS") f

Enterprise artificial intelligence is moving from isolated experimentation toward operational dependency across copilots, retrieval-augmented generation systems, autonomous agents, and AI-enabled business workflows. As this transition accelerates, the primary enterprise challenge is no longer only model access or inference scale. It is governed intelligence operations: the ability to enforce authorization, preserve contextual lineage, control persistent memory, detect stale or conflicting knowle

Enterprise artificial intelligence is moving from experimentation into operational workflows. Early programs focused on model access and retrieval-augmented generation, but enterprises are now beginning to deploy agents that plan, retrieve, remember, call tools, update systems, and coordinate work across applications. This changes the evaluation problem. Leaders are no longer asking only whether an answer is accurate or fluent. They need to know who authorized an action, which policy applied, wh

These activities are directly based on the case law of the European Court of Human Rights, the recommendations and findings of the European Commission against Racism and Intolerance (ECRI), the ...

Agentic AI systems are increasingly used to edit, refine, and repair decision policies, but evaluating these edits is difficult when per-state expert action labels are unavailable. We study this problem in a hotel-pricing simulator where an agentic policy editor receives only region-level diagnostic feedback: summaries of how its price distribution differs from a benchmark policy across time, inventory, and market regions. The editor cannot observe benchmark actions, benchmark source code, rewar

Artificial intelligence (AI) technologies are increasingly adopted into everyday life, with most investment and development concentrated in the U.S. In response to rapid AI integration and scant federal guidelines, U.S. states have formed AI committees charged with studying AI-related societal trade-offs. We analyzed the 18 existing state-level AI committee reports to understand how policymakers discuss AI-related benefits and risks. We then compared the risks surfaced by policymakers to an esta

This is from a 2024 company presentation : Officers can also tap into data showing a car’s decals, bumper stickers, back and top racks—along with temporary and unique state tags. Flock calls it a “Vehicle Fingerprint” and it’s touted as a way for law enforcement officials to get more information “even when you don’t have full plate information,” the company’s presentation shows. The company gives police officers the ability to search that data as well, to “build stronger cases with less informat

Reinforcement Learning (RL) has substantially improved the reasoning ability of large language models (LLMs), but sparse outcome rewards still make token-level credit assignment difficult. Existing scalable RL methods typically assign trajectory-level rewards uniformly across tokens, while recent entropy-aware approaches either rely on coarse detached heuristics or directly optimize true entropy, which can introduce non-local gradient components misaligned with sampled-token policy updates. We p

We argue that AI systems used in conducting foreign policy tasks - broadly enacting 'statecraft' - should be a priority test case for technical AI governance research. In enacting foreign policy, we refer to the formulation and implementation of external objectives by political actors. Statecraft is a high-consequence deployment domain, with extreme downside risks and structural properties that standard evaluation practices handle poorly. These features include partial observability, unbounded a

Improved institutional safeguards and stricter regulations have pushed the burdens of protection and risk reduction on to Australian businesses.

CSET’s Jessica Ji shared her expert insight in an article published by CNBC. The article examines the House passage of the Kids Internet and Digital Safety (KIDS) Act, a bill aimed at strengthening protections for minors online through age verification, content restrictions, and parental oversight tools. The post A major online safety bill for kids just passed the House. Here’s what experts say parents need to know appeared first on Center for Security and Emerging Technology .

Expect more compressed patching cycles from Apple going forward, as attackers leverage artificial intelligence to reduce time to exploit.

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

The complexity of waste disposal regulations across European countries poses significant challenges for the residents and hinders the transition to a Circular Economy. In Germany, the proper sorting and disposal of household waste remains challenging across municipalities. Consequently, substantially reducing incorrectly disposed waste is vital for improving waste management and advancing the Circular Economy. AI-based waste sorting solutions can support residents through user-friendly tools, su

For roughly 90 years, Humphrey’s Executor had been the constitutional law equivalent of a load-bearing antique: an awkward, if still functioning, architectural kludge, much admired in certain circles, but increasingly hard to rationalize. Earlier this week, finally, the U.S. Supreme Court replaced it. In Trump v. Slaughter, the Court overruled that 1935 opinion. The president ... Much Ado About Removal: The Supreme Court, the FTC, and the End of Independent-ish Agencies The post Much Ado About R

The society and emerging risk-based regulatory frameworks for AI underscore the need for rigorous risk assessment to ensure safe and reliable AI systems. In response to this imperative, this paper presents an overview of AI risk assessment (identification and analysis) and management methodologies. It begins by reviewing the worldwide regulatory landscape that drives the need for systematic AI risk assessment. Then we characterize the spectrum of AI-related risks identified in the literature, fr

Columbia Global Freedom of Expression seeks to contribute to the development of an integrated and progressive jurisprudence and understanding on freedom of expression and information around the world. It maintains an extensive database of international case law. This is its newsletter dealing with recent developments in the field. Across Kenya, more than 350 anti-government protesters were arrested last […]

Autonomous AI agents increasingly depend on external knowledge stores, yet most retrieval pipelines provide relevance without durable guarantees of provenance, version identity, integrity, traceability, or point-in-time reconstruction. We formalize this as context governance and present ContextNest, an open specification and reference implementation for governed AI-consumable knowledge vaults. ContextNest does not replace Retrieval-Augmented Generation (RAG); it supplies the governance layer ben

What GAO Found In May 2025, GAO identified five priority recommendations for the Board of Governors of the Federal Reserve System. Since then, the Federal Reserve has not implemented any of these recommendations. GAO is highlighting the following three areas that warrant timely and focused attention: Strengthening bank supervision, Analyzing regulations, and Addressing blockchain technology risks. Addressing GAO's recommendations in these areas would help the Federal Reserve reduce the risk of i

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What GAO Found In May 2025, GAO identified nine priority recommendations for the Nuclear Regulatory Commission (NRC). Since then, NRC has not implemented any of these recommendations. In May 2026, GAO identified two additional priority recommendations, bringing the total to 11. GAO is highlighting the following three areas that warrant timely and focused attention: Addressing the security of radiological sources, Improving risk-informed decision-making, and Licensing advanced nuclear reactors. A

What GAO Found Under federal special education law, students with disabilities are to be educated alongside their peers without disabilities to the maximum extent appropriate. Nationally, the number of students with disabilities in the general education classroom (gen ed) for at least 40 percent of their day increased 25 percent from school year 2012–13 through school year 2023–24 (see figure). The largest increase came from students with disabilities in gen ed for at least 80 percent of their d

On Tuesday, the United States Department of Commerce removed restrictions on two of Anthropic’s new advanced AI models that have prompted security concerns: Mythos 5 and Fable 5. This is a major ...

New EU AI guidance sets practical expectations for labelling, deepfakes and AI-generated content transparency. In Brief Companies are increasingly using AI to create or modify content across marketing, communications and customer-facing channels. As EU transparency obligations under the AI Act move closer to application, this raises practical and operational questions around when AI-generated or AI-manipulated [...] The post New EU guidance on AI transparency: what should companies be doing from

Long-running adaptive intelligent agents face a structural tension between knowledge consolidation and information integrity. Memory consolidation is conventionally treated as an agent-changing operation: a model is fine-tuned, a prompt rewritten, a policy distilled, or a reflection appended to the context that governs future behaviour. In regulated autonomic deployment this is a liability because the agent operates under commitments and audit contracts that bind to a specific, cryptographically

Organizations increasingly make strategic decisions about AI systems whose behaviour, failure modes, and institutional effects cannot be fully known at design time. This technical report reframes strategic red teaming as a board-level governance discipline for testing the assumptions under which AI-enabled strategies are approved, funded, and supervised. The report proposes a six-component model for strategic red teaming in AI governance: an explicit assumption register, an adversarial mandate,

Companies are being too conservative in how they interpret FDA's AI guidance, but the agency can do more to help, too, Tala Fakhouri says.

Passed and signed with little warning, New Jersey's new law mandates unprecedented registration fees for data brokers and data collectors.

On-policy exploration is a crucial component for training robust Vision-Language Navigation agents, as it exposes the policy to a broader state distribution. However, such exploration inevitably leads to trajectories that deviate from expert demonstrations, resulting in a semantic mismatch between the executed visual stream and the original language instruction. In this work, we address this challenge by introducing Phi-Nav, a unified on-policy framework that leverages hindsight reasoning to ali

Open source software (OSS) is not homogeneous. A project's purpose, governance, and funding shape how its community forms, who contributes, and how the software is maintained, yet empirical research often samples OSS broadly and reports findings as if they held for open source as a whole. We argue that OSS comprises distinguishable sub-genres, and that the sub-genre a study samples bounds how far its findings generalize. Using a light, multi-source review that screens 3,925 unique papers, we syn

Public LLM leaderboards optimise for global average performance and do not capture the specific cognitive demands of financial-services work: a model that leads on MMLU-Pro may underperform on document-grounded compliance reasoning, and a coding leader may handle multi-turn customer interactions poorly. We present a meta-benchmarking framework that organises 452 publicly reported benchmarks into 41 O*NET Generalized Work Activities and aggregates those into 38 BIAN banking business domains spann

Big Data & Society, Volume 13, Issue 3, July-September 2026. The regulation of artificial intelligence (AI) is a prominent issue in both the European Union (EU) and the United States of America, but with distinct approaches to the governance of this rapidly evolving field. The EU has developed a comprehensive ...

This final rule removes duplicative and unnecessary sections from the Runaway and Homeless Youth Program regulations. These amendments will streamline the Runaway and Homeless Youth Program regulations to make them more accessible to the public.

The province has set out plans to assess the current state of the industry surrounding the naturally occurring but addictive and cancer-causing stimulant before proceeding with legislation.

Engineering management research has produced mature frameworks for software risk: ownership by feature, escalation by severity, and assurance by test coverage. These frameworks implicitly assume deterministic behavior, discrete and auditable change events, and clear component-to-owner mappings. Teams that build and operate agentic AI systems violate all three assumptions at once: outputs are probabilistic, systems take autonomous multi-step actions, and the risk surface mutates silently between