Regulation

Last November, we published a blog post setting out our definitions of common AI terms. AI has continued to evolve rapidly since then. This update replaces that post and incorporates newer terminology, including “AI Agent,” “Agentic AI,” and “Harness.” AI governance is hard enough without the added difficulty of assessing risks absent a common understanding [...]

Opinion: Fathom CEO Andrew Freedman argues that the Supreme Court’s Slaughter ruling makes the case for independent verification for AI governance

Safety evaluations for language models increasingly depend on judgments about ambiguous natural-language behaviour: whether a model has followed an instruction, refused appropriately, complied with a policy, resisted an embedded command, or misreported progress in an agentic task. Existing benchmarks often compress these distinctions into pass/fail labels, obscuring whether failures arise from capability limits, policy ambiguity, instruction conflict, scaffold failure, or unstable evaluator judg

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

High-throughput RLHF systems often decouple rollout generation from policy optimization, leading to the use of stale rollouts during learner updates. In this work, we study the effect of such staleness in asynchronous GRPO. We make the behavior policy explicit in the GRPO surrogate objective and distinguish between the surrogate-gradient mapping used by the learner and the true total derivative of a distribution-dependent population objective. Under assumptions of local boundedness, distribution

Effective public health responses to many infectious diseases require sustained collective action. Communicable disease control in populations can only be achieved by high levels of public compliance with health directives. However, governing authorities have limited options if public compliance is insufficient and collective action is failing. Mechanisms to promote public compliance occur on a spectrum from providing public health advice, offering incentives so people cooperate more, to enactin

Accelerating materials discovery requires AI systems that can generate scientifically valid hypotheses through multi-step, domain-grounded reasoning. Standard large language models often produce fluent but weakly traceable responses to open-ended materials design problems, making it difficult to determine whether final answers are supported by coherent intermediate reasoning. We develop Graph-PRefLexOR, a family of graph-native reasoning models fine-tuned with Group Relative Policy Optimization

Recent advances in AI have heightened scholars' and policy makers' concern with social influence and behavioral contagion in online communities. We conduct a field experiment on Reddit to investigate the extent to which online users are susceptible to positive behavioral stimuli from other users and artificial agents. We let apparent human and bot accounts give symbolic awards to users with one of four rationales: praising the recipient's logical argument, emotional sensitivity, or moral integri

Ireland takes the reins of the Council’s policy negotiations at a moment of political possibility.

The Federal Trade Commission is seeking public comment on a proposed policy statement addressing concerns that AI companies may be manipulating the b View Press Release

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

Autonomous agents, whether LLM-driven software agents or robotic physical agents, face a common class of failure modes when operating without continuous human oversight: safety violations from unverified actions, behavioral instability from unconstrained loops, and continuity loss from unhandled error states. We develop \system{}, a discrete-time control system that combines five execution gears (\Gobs{}, \Gsug{}, \Gplan{}, \Gexec{}, \Gint{}) with utility-gated dispatch and event-driven fallback

Today, the New Jersey legislature passed the New Jersey Kids Code Act, which prohibits online companies from engaging in data and design practices that harm minors online. The bill now advances to the desk of Gov. Mikie Sherrill. EPIC applauds lawmakers’ passage of this crucial piece of legislation, which features several provisions from the model Age-Appropriate Design … Continued

Washington, D.C. — Today, the New Jersey legislature passed the New Jersey Kids Code ActNew Jersey Kids Code Act, which prohibits online companies from engaging in data and design practices that harm minors online. The bill now advances to the desk of Gov. Mikie Sherrill. EPIC applauds lawmakers’ passage of this crucial piece of legislation, which features … Continued

Chuyao is a Ph.D. candidate in Social Research Methods, supervised by Professor Patrick Sturgis and Dr Daniel De Kadt. His research examines how AI governance and generative AI shape political ...

This article presents a conceptual and integrative review of how multinational corporations articulate and operationalise the governance of artificial intelligence (AI). Drawing on three major bodies of scholarship—strategic governance, stakeholder engagement, and technology risk governance—the review synthesises existing research alongside publicly disclosed governance frameworks, policies, and oversight structures from eight global firms. The review identifies persistent tensions between innov

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

Amidst the general excitement about the opportunities afforded by artificial intelligence (AI), the tech industry must confront the uncomfortable reality that generative AI also facilitates child sexual exploitation and abuse (CSEA). This issue remains under-addressed in the literature. Aiming to deepen the understanding of online CSEA and the misuse of generative AI, we report empirical insights from semi-structured interviews with seven UK law enforcement practitioners. The topics covered rang

Learning deep reinforcement learning (DRL) policies directly in physical robots remains bottlenecked by slow wall-clock training times. We present preliminary research on Branched Euclidean Group Fractal Symmetries, a trajectory-level augmentation framework that super-scales group transformations to accelerate policy learning for manipulation. We model a Markov decision process (MDP) as a tree of state–action pairs; at each depth, affine transformations generate geometric structures, within whic

Emotional bonds between humans and AI companions are growing, and the question of whether a person may marry an AI system will soon move from speculative fiction into law. This chapter examines whether the autonomy-centered logic that has expanded marital choice among human beings can justify extending marital status to superintelligent companions. Following a scenario-envisioning exercise informed by anticipatory ethics, I argue that granting such status leads to socially unjust outcomes, even

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

Metacognition is a critical component of intelligence that describes the ability to monitor and regulate one's own cognitive processes. Yet LLMs exhibit systemic deficiencies in key metacognitive faculties: they hallucinate with high confidence, fail to recognize knowledge boundaries, and misrepresent their internal uncertainty--undermining trustworthiness and reliability. Since monitoring task performance and adapting behavior accordingly are central to metacognition, we posit that models capab

How to apply effective governance to harness the benefits of A.I. and mitigate its risks ...

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 International Conference on Machine Learning (ICML), held annually for over forty years, is among the most influential conferences in modern AI research. This year in Seoul, ICML is hosting its second workshop on Technical AI Governance Research (TAIGR), and several members of MIRI’s Technical Governance Team (TGT) will attend in July. This post summarizes […] The post Summary: TGT’s 2026 ICML Papers appeared first on Machine Intelligence Research Institute .

As large language models take on morally consequential roles in healthcare, legal, and hiring contexts, we need to examine whether their ethical behaviors are genuine or superficial. We show that current fairness evaluations substantially overestimate moral safety. Models appear fair when demographic identity is stated as an explicit label, yet become measurably less fair when the same identity must be inferred. We term this failure performative compliance, where a model is fair when the present

Call for Tenders: European Data Market Study 2027–2028 dumimar Tue, 06/30/2026 - 14:43   Opening: 29 June 2026   Closing: 12 August 2026 This call for tenders will fund the European Data Market Study 2027–2028, which will provide quantitative evidence on the EU data market and data economy at large. AdobeStock © Miha Creative The study will build on data collected since 2014 and support evidence-based policymaking by monitoring key trends, measuring progress towards EU digital policy o

Carolyn Geason-Beissel/MIT SMR | Getty Images Leaders at literally every Fortune 500 company will tell you that they are governing their AI — every single one of them. Now ask those same leaders who’s responsible for shutting down an AI model that’s causing harm. Most people can’t answer that question. That silence is the most […]

Since the Leveson Report was published in 2012, exposing a collapse in ethical standards across the press, most national newspapers have adopted a similar stance: objection to the very principle of accountability. They believe that while social media, broadcast media and every other industry should be regulated, they alone should be permitted to operate and […]

Large language models (LLM) trained on web-scale corpora generate output that may infringe copyright, yet existing technical safeguards focus narrowly on verbatim memorisation. EU copyright doctrine applies a broader standards: substantial similarity, which extends to stylistic choices, narrative structure, and creative elaboration. This mismatch between what current methods detect and what the law protects leaves a significant compliance gap. We introduce PSALM, an LLM-as-a-judge framework that

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Reducing compensation to symbolic amounts strips the regulation of its primary purpose: consumer protection and accountability.

Autonomous AI agents increasingly perform consequential actions on behalf of human principals, including financial transactions, external communications, and enterprise workflows. Existing agent infrastructure relies on identity federation and delegated authorization to authenticate workloads and control resource access, but it cannot determine whether an authorized action should be executed under the current behavioral and operational context. We present AgentBound, a runtime governance framewo