Regulation

The bureau is wary of adversaries getting their hands on tools that can uncover system vulnerabilities and enhance other capabilities. The post FBI sees Anthropic’s Mythos as a law enforcement challenge appeared first on FedScoop .

It's a grand tradition of chaos, and we want to hear all about it. The post The Bar Exam Is Here, Which Means Something Is About To Go Horribly Wrong appeared first on Above the Law .

This paper investigates how multi-agent systems (MAS)-based on large language models (LLMs) can support actuarial risk modelling, with a particular focus on uncertainty quantification. Actuarial workflows represent a high-stakes decision-support setting where unreliable outputs may lead to incorrect risk assessment, unfair pricing, and regulatory non-compliance. To address uncertainty introduced by the probabilistic nature of LLMs and dependencies between agents, a multi-agent framework is propo

Biglaw keeps waiting while other firms keep writing checks. The post Cha-Ching: Another Firm Joins The Bonus Party appeared first on Above the Law .

False testimonials are prohibited under Australian consumer law, writes policy professional Kat George, but they are also very hard to police Read more Australian customer service questions While looking at the website for NannyLane Australia, which bills itself as “the Uber for Nannies”, I noticed some glowing testimonials apparently written by happy parents who’d used their services. But a simple reverse Google image search of “James & Emily T” from Sydney led me to a stock image of a couple,

Clio Work went live in Canada on July 23, enabled by more than 470,000 Canadian cases drawn from Jurisage. The post Bringing Home The Bacon: Clio Launches ‘Clio Work’ AI In Its Home Country Of Canada appeared first on Above the Law .

Rising expenditure from OpenAI, Anthropic, Google and Microsoft reflects growing battle over federal policy Von Michael Taffe ( Wirtschaft , KI )

* Corporate pardons were never a thing. Trump has issued nine. [ The New Republic ] * Freshfields losing European partners worried about U.S. growth. [ Bloomberg Law News ] * Comey seeks to 86 the 8647 suit. [ NPR ] * Trump heading to the Supreme Court with his effort to use Post Office to block voting by mail in Democratic states. [ Reuters ] * "Abruptly changes" is never an encouraging description of a law school dean switch. [ Penn Live ] * Blanche confirmation vote held over again as holdout

Public services face growing pressure to adopt artificial intelligence (AI) to close the gap between rising demand and falling resources. That pressure has intensified with general-purpose AI (GPAI): AI built on large language models that can be directed by prompt alone to perform an effectively unbounded range of tasks. We argue that the properties that make these models attractive - their generality, accessibility, and low deployment cost - undermine the conditions under which AI safety has hi

From the boardroom to the C-suite, AI governance should be on the front burner.

From the boardroom to the C-suite, AI governance should be on the front burner.

Today's links Discernment: How can you fact-check AI when you're asking it to teach you something you don't understand? Hey look at this: Delights to delectate. Object permanence: How to help with computers; Batman equation; Fuck and the law; NC's racist voting law; Pregancy app is full of spyware; Stiglitz v Apple's "tax fraud"; Accelerometer fingerprinting; Sacklers v bankruptcy; Boss-politics antitrust. Upcoming appearances: Edinburgh, Sydney, Melbourne, Brighton, London, South Bend. Recent a

Exponant and Syskit are helping organisations gain greater visibility, stronger governance and simplified Microsoft 365 management.

NewMod law firm Crosby is to provide ‘professional liability insurance for [their] agents, so that they can do autonomous legal work’, in what is an ...

Supply chain decision-making is rapidly transforming with the rise of agentic AI - highly autonomous systems that can operate on complex, long-horizon tasks. Yet the adoption of agentic systems outpaces their governance: existing taxonomies of autonomy only offer discrete classifications, rely on subjective judgement, and cannot track autonomy across a system's life cycle, leaving enterprises unable to assess the risks of increasingly autonomous supply chain agents. This paper proposes the Agent

Language-model agents are increasingly deployed under standing instructions: a system prompt, a policy file, or a skills document is placed in context, and the agent is trusted to let it govern every action that follows. Existing benchmarks rarely test this deployment pattern directly; they measure whether an agent can complete a task, not whether a long, binding policy document actually constrains its behavior over an extended tool-use horizon. We present HANDBOOK.md, a benchmark of 65 agentic

The intersection of artificial intelligence adoption, cybersecurity governance, and public sector institutional constraints has not been examined as a unified analytical problem in the existing literature. Studies address AI cybersecurity risks generically, public sector governance independently, and framework adequacy separately. Existing studies have not integrated these three streams to explain specifically how AI adoption causes cybersecurity governance failure in government organizations, n

Tool-using agents expose structured calls but commonly attach free-form rationales. Such rationales are neither authorization nor reliable introspection. We present Explanation-Bound Tool Execution (EBTE), a claim-carrying mediation layer that converts decision-relevant rationale content into typed action claims and checks them against server-held intent, policy, payload, tool, risk, provenance, and freshness facts. EBTE cannot widen baseline authority: conflicts deny, incomplete or uncertain cl

How Will New Student Visa Rules Impact Athletics? Johanna Alonso Tue, 07/28/2026 - 03:00 AM NCAA policy allows athletes to compete for five seasons, but new federal rules limit international students to just four years in the U.S., cutting off collegiate play for some. Byline(s) Johanna Alonso

Sovereign cloud is about preserving control, reducing vendor dependency and ensuring critical systems can adapt when regulation or risks change.

Activation steering controls language models by adding vectors or features to hidden states at inference time, but the upstream source of these steering signals is often treated as a secondary detail. We study this source choice as activation source selection: the combination of source context and activation readout policy used to collect the hidden states from which a steering signal is built. Holding the downstream intervention fixed, we show across three instruction-tuned models and four stee

Zendaya stunned the red carpet at the “Spider-Man: Brand New Day” Los Angeles premiere in a black satin Ashi Studio corset with a sweeping architectural train, putting an exclamation point on a press tour that the young star used as her personal runway. “It’s kind of an abstract way to present the spider,” Law Roach, […]

arXiv:2607.22604v1 Announce Type: new Abstract: In the age of Artificial Intelligence (AI), Large Language Models, Generative AI and larger frontier AI models, data centres create a significant environmental burden on electricity grids and fresh water resources. Requiring data centre operators and Big Tech under the recast Energy Efficiency Directive (recast EED) to quantify, report and disclose the facility-level energy and water impacts seems to be a step into the right direction towards more

arXiv:2607.22619v1 Announce Type: new Abstract: Several international agreements have been proposed to regulate frontier AI development in response to catastrophic risks. However, there is no structured way to evaluate whether these proposals are enforceable, to assess where they might fail in practice, or to determine which combination of policies is most effective. We propose a taxonomy based on the principle that wherever sufficient capacity exists to violate an agreement, it must be under a

arXiv:2607.23336v1 Announce Type: new Abstract: The built environment is on the cusp of populating itself with autonomous artificial agents. AI systems that advise, control and coordinate are being deployed across retrofit, operation and mobility faster than their collective behaviour is studied. The dominant framing treats each agent as a tool operating on a passive building, governance reduced to single-agent safety, which is inadequate. A building, a street, or a city is more accurately model

arXiv:2607.24391v1 Announce Type: new Abstract: AI systems already govern. They rank speech and allocate attention, filter applicants and triage claims. The dominant frame for AI governance, alignment, asks whether such systems pursue the right objectives safely. It cannot answer a prior question: by what right are those objectives set and enforced? This Article argues that legitimacy is an autonomous regulatory objective, distinct from alignment and not secured by it. Legitimacy here is sociolo

arXiv:2607.22953v1 Announce Type: cross Abstract: Modern AI systems bring societal risks such as mass surveillance, extreme concentrations of power, and loss of user autonomy---calling into question a model where third-parties collect and control massive amounts of user data. Users require a sovereign system to securely own, govern, and disclose their context while remaining compliant across regulated domains with strict provenance, interpretability, and policy adherence. Perspective-aware AI ap

arXiv:2607.23438v1 Announce Type: cross Abstract: As AI systems increasingly exhibit agentic behavior, discussions of autonomy often conflate what systems are technically capable of doing with what they should be permitted to do in practice. This paper introduces a governance framework that explicitly separates Allowed Autonomy Levels (AAL), which define the degree of autonomy an AI agent is authorized to exercise given risk, oversight, and accountability considerations, from Autonomous Capabili

arXiv:2607.23888v1 Announce Type: cross Abstract: In the United States, artificial intelligence (AI) is rapidly deployed amid limited federal regulation. With courts become a recurring forum in which AI-related practices are scrutinized, it is important to empirically understand the AI litigation landscape to date. We address this gap through a systematic review of 559 U.S. federal court opinions in which AI plays a role in the parties' contentions, taxonomizing (1) common topics of dispute, (2)

arXiv:2607.24275v1 Announce Type: cross Abstract: Ethical governance of AI-driven systems is often expressed through high-level principles and static documentation, creating a gap between regulatory requirements and system-level verification. This challenge is particularly acute in digital phenotyping, where continuous behavioural data raises concerns around consent, privacy, and fairness. In this paper, we propose a computational ethical framework for AI-driven digital phenotyping system in whi

arXiv:2504.02636v3 Announce Type: replace Abstract: As generative AI (GAI) becomes increasingly embedded in higher education, universities worldwide are developing policies to govern its ethical, pedagogical, and institutional use. However, these policies vary across national and institutional contexts. We undertake a cross-nationalanalysis of GAI guidelines issued by leading universities in the United States, Japan, and China, identifying key policy orientations and proposing a structured frame

arXiv:2603.20248v2 Announce Type: replace Abstract: AI systems are increasingly entrenched in public governance, yet scholarship lacks formal tools to determine when deviations of public trust in algorithmic institutions dissipate and when they grow into collapse. Stability refers here to asymptotic recovery from finite state perturbations under fixed structural parameters. We address this gap by developing a mathematical framework for institutional trust stability that couples a Friedkin-Johnse

arXiv:2507.21134v2 Announce Type: replace-cross Abstract: As large language models (LLMs) are increasingly deployed in high-risk domains such as law, finance, and medicine, systematically evaluating their domain-specific safety and compliance becomes critical. While prior work has largely focused on improving LLM performance in these domains, it has often neglected the evaluation of domain-specific safety risks. To bridge this gap, we first define domain-specific safety principles for LLMs based

A federal judge on Monday halted a prediction market ban in Minnesota days before it was set to roll out. District Judge Katherine Menendez wrote that the Trump administration, Kalshi and Polymarket are “likely to succeed on the merits” in the case arguing that the state ban is pre-empted by federal law. “Specifically, it appears...

ANA is issuing final interpretive rules, general statements of policy, and rules of agency organization, procedure, or practice relating to the following Fiscal Year (FY) 2026 Notices of Funding Opportunity (NOFOs): Economic Advancement Grants for Local Empowerment (EAGLE), AI3 Action Institute--Artificial Intelligence for American Indians (AI3 Action Institute), and the National Center for Native Training and Technical Assistance (NCNTTA).

Research on preference optimization often varies the training objective while holding the data fixed. We instead ask whether a small, high-confidence set of on-policy responses can provide a reliable learning signal. Our method, DMAPO (Data-centric Multi-evaluator Agreement for Preference Optimization), generates candidate responses from the target policy, evaluates helpfulness, factuality, and conciseness with rubric-specialized evaluators, applies a process-critic correction, and retains only

Worried about the bar exam this week? Well, it could be worse! Just ask the class of 2014. The post A Bar Exam Disaster For The Ages appeared first on Above the Law .

Beware of gifts-bearing Greeks. The post A Jaunt Through ‘The Odyssey’ appeared first on Above the Law .

Seldom used words, like "axolotl," a type of salamander, are inserted in Code Four's output, ensuring that law enforcement officers carefully review AI-generated content before submitting it into evidence.