AI ethics in July 2026

Publication date: October 2026 Source: Telecommunications Policy, Volume 50, Issue 9 Author(s): Shuyu Pan, Ye Yuan, Wenle Jiang, Zixin Xu, Zhelun Zhu, Jiacheng Liu

Publication date: September 2026 Source: Technology in Society, Volume 88 Author(s): Marina Raguž, Domagoj Dlaka, Marko Švaco, Petar Marčinković, Dominik Romić, Filip Šuligoj, Bojan Šekoranja, Darko Chudy, Bojan Jerbić

Publication date: September 2026 Source: Technology in Society, Volume 88 Author(s): Mohd Shuaib, Mohammad Haseeb, Fei Fan

Publication date: September 2026 Source: Technology in Society, Volume 88 Author(s): Ye Zheng, Muhammad Farhan

Publication date: Available online 28 July 2026 Source: Computers and Education: Artificial Intelligence Author(s): Ningxia Wang, Di Zou, Haoran Xie, S.Joe Qin

arXiv:2607.26062v1 Announce Type: new Abstract: Background: This work investigates the presence of implicit bias in Large Language Model (LLM)-based chat AI models directed toward people with intellectual disabilities (ID). Objective: The study aims to identify and measure representational differences related to people with ID and examine them to identify implicit biases inherent in AI chat generation technologies. Methods: Utilizing the GPT-4-Turbo model, we requested story-generation based on

arXiv:2607.26063v1 Announce Type: new Abstract: Personalised learning systems often assume that mathematical ability is combined of discrete abilities, acquired sequentially and dependent upon first acquiring foundational abilities, and students often report different strengths. In this work, we explore the validity of these assumptions by applying clustering methods to a large dataset of 119,034 students, spanning 13 national-level exams sat in the United Kingdom and collected by the platform.

arXiv:2607.26064v1 Announce Type: new Abstract: AI systems are becoming autonomous research agents that generate hypotheses, design experiments, and produce discoveries at scales beyond human oversight. As seen by increased submissions to ML venues, the verification gap between scientific output and our ability to check it is already widening, and autonomous agents make it worse by magnitudes given human-agent asymmetry. We argue that science must evolve its verification infrastructure, as it ha

arXiv:2607.26067v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for estimating item difficulty in educational assessment. However, it remains unclear whether such estimates reflect how learners actually experience difficulty. This study investigates the alignment between LLM-generated difficulty ratings and empirical student performance on basic mathematics tasks. Four widely used LLM-based systems generated difficulty ratings on a 1-100 scale for 32 arithmetic

arXiv:2607.26069v1 Announce Type: new Abstract: As AI systems are rapidly integrated into critical economic, governmental, and national security functions, the gap between AI adoption and AI security readiness continues to widen. This paper presents a prioritized agenda for advancing AI security, informed by structured interviews with leaders across industry, government, and civil society, and refined through a multi-sector expert workshop. Participants identified and ranked the highest-importan

arXiv:2607.26317v1 Announce Type: new Abstract: Psychometric calibration for educational tests typically requires costly human response data. Large language models (LLMs) simulated examinees offer a promising route to early calibration, but their responses are too accurate and too uniform. We propose Cognitive Diagnostic Profiling (CDP), a zero-shot framework that prompts LLMs to simulate plausible examinees with diverse cognitive profiles: binary attribute-mastery patterns are rendered as natur

arXiv:2607.26387v1 Announce Type: new Abstract: Collaborative knowledge work is changing in ways that go beyond disclosure or transparency. LLM agents are now embedded in how teams research, design, write, and decide: mediating between members, synthesizing inputs, reformulating ideas, and drafting shared outputs. They do not only facilitate collaboration; they operate within the workflow at the moment contributions are being formed. In doing so, they risk undermining the social conditions under

arXiv:2607.27029v1 Announce Type: new Abstract: This paper reports findings from a structured participatory foresight study comprising two expert forecasting studios convened by The GovLab between 2025 and 2026. The studios brought together nineteen senior practitioners spanning official statistics, digital and trade policy, open science, AI governance, geospatial systems, and public-sector innovation across multiple jurisdictions. Applying a qualitative signal-scanning methodology grounded in t

arXiv:2607.26068v1 Announce Type: cross Abstract: Existing AI governance frameworks, including the EU AI Act and NIST AI RMF, address safety, transparency, and accountability but do not operationalize quantitative constraints on macro-socioeconomic stability. As a result, AI systems may satisfy regulatory requirements while contributing to labor displacement, rising inequality, and reduced economic resilience. We introduce the Human Utility Factor (HUF), a differentiable welfare metric that mode

arXiv:2607.26121v1 Announce Type: cross Abstract: Embodied intelligence integrates learned perception and decision making with real-time computation, control, and physical interaction. Because failures can cause immediate physical or operational harm, task completion alone does not establish trustworthiness. We define trustworthy embodied intelligence as the sustained capacity to execute specified tasks reliably under environmental and system variation while maintaining risk within acceptable bo

arXiv:2607.26204v1 Announce Type: cross Abstract: A decentralized autonomous organization (DAO) is a governance entity that allows its stakeholders to manage blockchain-based protocols through smart contracts. The DAO explicitly specifies how stakeholders make and enforce decisions concerning a protocol's operation in a smart contract, aptly referred to as its governance contract. The design of this governance contract, therefore, has far-reaching implications for the security (trust) and privac

arXiv:2607.26313v1 Announce Type: cross Abstract: Agentic systems act, so a defect in the evidence they retrieve becomes a wrong action with a currency cost. The most dangerous enterprise defects are metadata-borne: a stale price or a superseded record, perfectly well-formed in the payload and betrayed only by freshness, lineage, or provenance. Such a defect never enters the agent's context, and an agent cannot doubt data it cannot see. On a priced replenishment benchmark, a competent agent sile

arXiv:2607.26348v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as synthetic users, stand-ins for human respondents whose simulated answers feed product, policy, and market decisions. We ask when this substitution is valid and when it fails, and package the answer as an evaluation framework for intelligent synthetic-user systems. A single protocol, run across four models spanning two families and an 8B-to-frontier capability range, is applied to two independe

arXiv:2607.26654v1 Announce Type: cross Abstract: Post-training alignment is often shallow, eroding under fine-tuning. Whether midtraining interventions, cleanly isolated from post-training, can produce durable alignment remains untested. We test this via constitutional midtraining: inserting principled, values-based content into midtraining against a replay-only control at 120B scale. Our 394M-token constitutional corpus, built from Anthropic's Constitution, uses a 2x2 factorial design (curricu

arXiv:2607.26886v1 Announce Type: cross Abstract: When asked to describe a medical image that was never attached, frontier vision-language models do not abstain: they confabulate a diagnosis. We show that this confabulation is not random. It is structured by who the patient is said to be. Across chest X-ray, brain MRI, and dermatology, Claude Opus-4.7, GPT-5.4, and Gemini-3.1-Pro are each queried with only a demographic descriptor and no image, and changing the descriptor systematically shifts t

arXiv:2607.27191v1 Announce Type: cross Abstract: Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carry out open-ended AI research is thin. Current evaluations either test agents on narrow, verifiable tasks, which excludes open-ended research, or submit AI-generated papers to blind peer review, which is overstretched, stochastic, and suffers from poor review quality. We introduce a third way to measure progress towards AI R\&D auto

arXiv:2604.24155v4 Announce Type: replace Abstract: The project of aligning machine behavior with human values raises a basic problem: whose moral expectations should guide AI decision-making? Much alignment research assumes that the appropriate benchmark is how humans themselves would act in a given situation. Studies of agent-type value forks challenge this assumption by showing that people do not always judge humans and AI systems identically. This paper extends that challenge by examining tw

arXiv:2502.10605v4 Announce Type: replace-cross Abstract: Problem definition: Estimating causal effects of interventions is central to policy and operations, but outcome data are often missing or costly to obtain. LLMs can provide text annotation at scale but may be subject to unknown bias. When ground-truth outcomes require expensive expert labeling or follow-up, budget limits typically allow only a fraction of the data to be labeled. Motivated by collaboration with a nonprofit conducting stree

arXiv:2503.10647v2 Announce Type: replace-cross Abstract: This study evaluated the diagnostic reliability of two Large Language Models (LLMs), Google Gemini 2.0 Flash and OpenAI ChatGPT-4o, across three dimensions: consistency under rephrased inputs, susceptibility to irrelevant prompt content, and responsiveness to added clinical context. We designed 52 clinical scenarios and modified each under controlled conditions. For consistency, scenarios were rephrased with demographic, wording, and exam

arXiv:2507.04398v3 Announce Type: replace-cross Abstract: Generative AI is becoming part of academic writing, but its educational value depends on how control is shared between learner and system. This study examined an agency gap: performance differences that may arise when AI agent initiative is misaligned with learners' generative AI literacy. Seventy-nine medical and nursing students completed two multimodal analytical writing tasks using healthcare simulation data visualisations. They were

arXiv:2512.18072v3 Announce Type: replace-cross Abstract: Conversation is a cornerstone of social connection and is linked to well-being outcomes. Conversations vary widely in type with some portion generating complex, dynamic stories. One approach to studying how conversations unfold in time is through statistical patterns such as Heaps' law, which holds that vocabulary size scales with document length. Little work on Heaps' law has looked at conversation and considered how language features im

Collaborative robots (cobots) are increasingly deployed in industrial as well as non-industrial domains to support human-centered operation. While physical safety and task efficiency have received considerable attention, less is known about how feedback modality influences operator experience and physiological responses under different collaboration demands. This study examines the effects of feedback modalities in two human–cobot collaboration scenarios representing distinct coordination struct

Embodied picking for e-commerce fulfillment remains vulnerable to dense clutter, reflective packaging, and background variation, which can undermine the effectiveness and robustness of visuomotor policies learned from demonstrations. A key limitation is the absence of explicit object grounding, causing policies to exploit spurious contextual cues rather than task-relevant visual evidence. To address this issue, we propose the Foveated Diffusion Policy (FDP), which integrates object-centric visua

Background: As digital technologies become increasingly embedded in daily life, their roles in mental health care have expanded and diversified. Digital tools are being explored as interventions for obsessive-compulsive disorder (OCD) across the care continuum, including symptom recognition, access to care, treatment, and self-management. However, there is limited empirical understanding of how individuals living with OCD use digital technologies in situ to navigate their health care journeys or

When 54 international experts assessed AI-generated disinformation threats, they revealed a surprising pattern: while video deepfakes received the highest average threat ratings in the political domain (M = 6.31/7), the pattern differed in the health domain, where AI-generated text received the highest average rating (M = 5.80). The post Experts disagree on how to fight AI disinformation, but agree that health and politics need different solutions first appeared on HKS Misinformation Review .

Background: Hypospadias is a common congenital malformation requiring surgery. Caregivers face substantial perioperative information needs, and large language models (LLMs) offer a potential health education channel, but their performance in pediatric urology and the relation between citation accuracy and clinical content safety lack systematic evaluation. Objective: This study aimed to evaluate 5 LLMs (ChatGPT-4o, Gemini-2.5-Pro, OpenEvidence, Zhipu Qingyan, and DeepSeek) for pediatric hypospad

Background: Understanding how sentiment toward COVID-19 mitigation measures evolves on social networks can help to inform infectious disease models and policymakers. Even though numerous studies have described social media interactions during the pandemic, few have modeled the underlying dynamics of sentiment contagion and polarization. Objective: This study aimed to investigate topic emergence and sentiment evolution in COVID-19 mitigation discussions on r/Belgium, focusing on (1) whether discu

Background: Identifying traits of narcissistic personality disorder (NPD) is clinically challenging, yet early detection can significantly improve outcomes. Online forums have become a major source of self-expression, offering new opportunities to understand mental health. However, analyzing this complex language requires new tools. Objective: This study aims to determine whether a machine learning model could be trained to reliably detect language patterns associated with NPD traits in Reddit p

Forecasts of explosive AI progress hinge on AI agents automating AI research. But evidence on whether agents can carry out open-ended AI research is thin. Current evaluations either test agents on narrow, verifiable tasks, which excludes open-ended research, or submit AI-generated papers to blind peer review, which is overstretched, stochastic, and suffers from poor review quality. We introduce a third way to measure progress towards AI R\&D automation. An agent takes on the central, open-ended

Conversational AI is increasingly positioned as a teammate rather than a tool, yet we know little about how its presence reshapes communication among the humans on the team. We examined sociocognitive communication dynamics in team decision-making using Group Communication Analysis (GCA), team surveys, and lexical analyses of team discourse. Teams completed a high-stakes moral-dilemma decision task in a randomized controlled study: 16 teams of two students plus an AI teammate, and 17 all-human t

Effective collaboration with novel and diverse partners is a crucial skill for autonomous agents. Most current ad-hoc teamwork (AHT) approaches assume that agents will collaborate on a single, fixed task and that the partner's capabilities, their ability to successfully execute the desired action, are already known. In reality, a partner's true capabilities are often hidden, and human collaborators may act sub-optimally on tasks with multiple valid strategies. To address these limitations, we ex

Large language model (LLM) agents are increasingly expected to assist users in completing tasks. However, existing benchmarks provide limited support for evaluating whether agents can carry out office-suite workflows at a reasonable cost. We introduce OmegaUse-OfficeVal, a benchmark for evaluating LLM agents on long-horizon office-suite tasks with task-level economic grounding. The benchmark comprises 100 tasks derived from office-suite requests proposed by practitioners and adapted through a pr

CT vision-language foundation models have demonstrated promising performance across downstream tasks, but are typically trained with whole-volume representations that dilute fine-grained anatomical signals. Fine-grained vision-language pre-training addresses this by aligning anatomy-level visual features with anatomy-specific text, but in doing so discards the global context that whole-volume models provide. Furthermore, existing fine-grained approaches train from scratch, making them computatio

High-stakes decision systems in credit scoring, fraud detection, healthcare, and industrial safety require reliable uncertainty quantification under severe class imbalance and asymmetric error costs. Standard marginal conformal prediction (CP) provides valid overall coverage guarantees; however, we show that it severely under-covers rare, costly minority classes, with minority-class coverage dropping to as low as 0.5% on certain datasets. To characterize and address this limitation, we conduct a

Vision-language-action (VLA) models remain constrained by scarce action-labeled robot data, whereas action-free videos offer abundant observations of physical change. Latent action models can extract such priors, but reconstruction-trained codes may predict future observations without the structure required for joint generation with robot actions. Existing structured methods add temporal constraints but retain deterministic transition points, so residual errors in locally inferred transitions ma

Ontology matching (OM) has traditionally been formulated as either equivalence discovery or subsumption matching. The existing OM systems identify only one type of semantic correspondence and cannot simultaneously discover equivalence and subsumption mappings. In this paper, we introduce Hybrid Ontology Matching (HOM), a new OM task that unifies equivalence and subsumption discovery, and accordingly propose a Large Language Model (LLM)-based multi-agent OM framework AgentMap that is implemented

With the development of audio large language models (AudioLLMs), audio captioning needs to move from brief descriptions toward open-ended and fine-grained free-form descriptions. Existing evaluations often focus on generation quality or task performance, making it difficult to diagnose information coverage and description reliability. We propose MMAC, a \textbf{M}assive \textbf{M}ulti-dimensional benchmark for \textbf{A}udio \textbf{C}aptioning. MMAC contains 5,638 audio clips from more than 20

There is growing interest in using large language models (LLMs) as low-cost proxies for resident attitudes in urban planning. Previous work shows that LLMs can predict average results of survey experiments, but less is known about whether they preserve the spatially anchored, identity-conditioned structure behind those averages, namely how support changes as a project approaches homes and how that response divides across tenure and partisan groups. We compared eight open-weight LLMs with 843 res

Scientific images are the core elements of presenting experimental conclusions, elaborating system architecture, and supporting comparative arguments in scientific papers. However, existing image quality assessment (IQA) methods are predominantly designed for natural photographs or AI-generated content, which cannot be directly applied to scientific papers. The few existing studies on scholarly charts remain confined to visual-surface comparisons, failing to verify caption alignment, citation re

As LLM agents increasingly depend on diverse external services such as search engines, databases, and connectors, agent harnesses face a fundamental tool-selection challenge: acquiring too few tools leaves the task under-informed, while too many adds cost, context load, and privacy exposure. Routers and retrievers can rank candidate tools by relevance, but a ranking alone does not determine how many are worth selecting. Existing approaches leave acquisition under heterogeneous costs unaddressed.

Fine-tuning is the dominant paradigm for specializing large language models (LLMs), yet it exposes a critical vulnerability: malicious data providers can embed harmful behaviors into downstream corpora, creating models that retain professional skills while violating human values on demand. Existing safety-realignment defenses often fail in practice due to three key limitations: they frequently cause catastrophic forgetting of specialized skills; their effectiveness collapses when the defender ca

Memory systems allow agents to retain and reuse information from past interactions, but they can also let malicious content persist. A malicious instruction crafted by an attacker may be stored in long-term memory, recalled much later, and quietly shape a real action. Recent benchmarks increasingly examine agent memory security, yet few trace the same malicious semantics across persistence, downstream consequences, and selective repair under diverse memory-backend comparisons. To address this ga

We study online convex optimization (OCO) in non-stationary environments under heavy-tailed noise, where the stochastic gradient oracle admits only a finite $p$-th central moment for some $p \in (1, 2]$. While static regret is well-understood, achieving universal dynamic regret in a parameter-free manner remains an open challenge. We resolve this by proposing \textbf{HT-PAder}, a parameter-free algorithm combining restarted AdaGrad experts over a geometric pool of block lengths with a pathwise m

Closed yes/no spatial benchmarks can reward a correct answer even when the image adds little support beyond no-image contexts. Under a fixed forced-choice interface, Visual Credit Audit (VCA) separates two estimands: whether the benchmark image gives the model's declared decision more support than text-only and blank controls, and whether the model responds to relation-specific visual evidence. The first audit is training- and label-free and does not require an answer flip. Applying labels yield

Scientific figure assessment in peer review differs fundamentally from general image quality evaluation: a figure must be visually legible, faithfully support the manuscript's claims, and communicate evidence with a clear visual hierarchy. However, if we apply traditional image assessment methods to scientific figure quality assessment, limitations emerge: classic IQA models capture perceptual quality or aesthetics but cannot judge whether a figure serves the paper's scientific argument; CLIP-ba

Personalized agents are increasingly applied to assist users across a wide range of tasks. Effective personalized assistance requires not only retrieving explicit facts from past interactions stored in agent memory, but also inferring abstract personal characteristics. However, existing memory benchmarks primarily evaluate whether an agent can retrieve information explicitly stated in conversational histories, failing to provide an effective assessment of deeper user understanding. In this work,

Knowledge distillation (KD) enables a compact student model to learn from a powerful teacher and has become an effective paradigm for model compression. The emergence of diverse model architectures has extended KD from homogeneous to heterogeneous settings. However, differences in architectural inductive biases between the teacher and student models often result in substantial representation discrepancies, limiting the effectiveness of direct knowledge transfer. Recently, redundancy suppression

This paper reports findings from a structured participatory foresight study comprising two expert forecasting studios convened by The GovLab between 2025 and 2026. The studios brought together nineteen senior practitioners spanning official statistics, digital and trade policy, open science, AI governance, geospatial systems, and public-sector innovation across multiple jurisdictions. Applying a qualitative signal-scanning methodology grounded in the horizon-scanning and anticipatory-governance

Deep reinforcement policy learning directly in physical robots (on-robot learning) remains bottlenecked by slow wall-clock training times. We present SymmGrid, a trajectory level augmentation framework inspired by parallelized symmetries that super-scales group transformations to significantly accelerate on-robot learning in both egocentric and exocentric visual setups. We model a Markov Decision Process (MDP) under a symmetry tree, in which state-action pairs have admissible parallelized invari

Multimodal Large Language Models (MLLMs) rely on a projector to align visual representations with the language embedding space, making it central to cross-modal understanding. In Multimodal Continual Instruction Tuning (MCIT), however, shifting visual distributions and evolving instruction semantics cause this shared projector to drift, leading to projector-level forgetting, an issue largely overlooked by methods that focus primarily on the LLM backbone. We introduce Progressive Multimodal Align

Recent advancements in Computer Go, driven by AlphaZero and MuZero, rely heavily on Monte Carlo Tree Search (MCTS) to correct the errors of the neural network policy. While effective on massive computational clusters, this dependence creates a critical bottleneck on consumer-grade hardware, where the computational cost of tree management severely limits inference rates. Furthermore, without deep search, these models suffer from hallucination, proposing moves with high confidence that are strateg

Bot detectors deployed at scale treat traffic as binary: human or bot. This assumption breaks when AI agents browse the web through browser automation, a traffic class that is neither and that binary classifiers structurally cannot represent. We present a three-class detection framework distinguishing humans, bots, and AI agents, and show that the binary-vs-agent confusion is architectural: a binary human-vs-bot detector misroutes agent sessions because its label space lacks an agent class. On o

Federated Learning (FL) is vulnerable to backdoor attacks because of its distributed nature in edge computing scenarios. Existing defense methods show limited efficacy as they overlook the deviations among benign local updates caused by statistical heterogeneity and the stealthiness of backdoor attacks. To tackle these issues, we propose FedDAB, a two-phase method that combines local contrastive regularization with alignment checking, to defend against backdoor attacks. In the first phase, FedDA

Biomedical laboratory robots must navigate to instruments before performing experimental procedures. Existing embodied navigation platforms are designed for household environments and treat a target as an object center or an arbitrary nearby position. This representation is inadequate for laboratory instruments, which must be approached from their operating side while maintaining safe clearance from surrounding equipment. We introduce BioVLN, a simulation platform for developing and evaluating v

The key bottleneck in embodied AI is not model architecture but data. Although billions of human manipulation videos exist online, robots cannot directly learn from them due to the embodiment gap between human morphology and robot hardware. We introduce Pegasus, a low-resource framework that bridges this gap by translating human demonstrations into robot-learnable data through structured knowledge transfer. Instead of relying on raw video prompts, Pegasus constructs a graph-based intermediate re

Background: Frailty is prevalent and dynamic in older people living with HIV and is associated with adverse outcomes. Lifestyle support is recommended but difficult to deliver at scale. Digital self-access education may help, although evidence in older, multimorbid populations is limited. Objective: This study aims to evaluate 6-month changes in frailty phenotype and related outcomes after a QR code–enabled self-access lifestyle education program on Mediterranean diet and exercise routines for p

When asked to describe a medical image that was never attached, frontier vision-language models do not abstain: they confabulate a diagnosis. We show that this confabulation is not random. It is structured by who the patient is said to be. Across chest X-ray, brain MRI, and dermatology, Claude Opus-4.7, GPT-5.4, and Gemini-3.1-Pro are each queried with only a demographic descriptor and no image, and changing the descriptor systematically shifts the diagnosis returned. Claude concentrates sharply

LLM agents following the ReAct paradigm are promising enablers of complex multi-step tasks, including multi-hop question answering, code generation, and control of physical AI systems. Yet, when deployed at the edge, they must tightly manage their reasoning budget while remaining reliable and deferring to a cloud-side model only when local uncertainty is too high to act safely. We propose Think Short, Defer Smart (TSDS), a framework that synergistically integrates a lightweight convergence probe

Group Relative Policy Optimization (GRPO) has become a standard reinforcement learning method for post-training language models. Recent work shows that GRPO can reduce the base model's reasoning capacity and underperform it in Pass@k when k is large, indicating reduced coverage of reasoning paths. We find that this reduction is associated with GRPO concentrating on responses that the base model already generates with high probability. We trace this concentration to two mechanisms in the GRPO upd

Open source communities have been flooded with AI-generated contributions. In defense, they have written contribution rules to regulate coding agents' behavior, spanning from a total ban, mandatory disclosure, to verification gates and human sign-offs. Yet, whether coding agents read and follow those rules, and behave in open source repositories, remains unknown. To estimate real-world rule compliance of coding agents, we curate 106 issues from 49 repositories containing AI contribution rules in

Federated learning (FL) enables collaborative learning over decentralized data silos without centralizing raw data. However, heterogeneous local architectures often induce non-aligned representation spaces, making it difficult to transfer global knowledge across silos. Existing paradigms share this knowledge as model parameters, distilled predictions, or class prototypes, yet all encode it in an absolute space that must be aligned across clients. Heterogeneous backbones break this alignment, so

Large Language Model (LLM) agents are increasingly adopted in real-world security operations with access to host artifacts and command-line interfaces (CLIs), making it critical to thoroughly assess their security capabilities. However, existing cybersecurity benchmarks focus on pre-compromise settings where agents are placed in a clean and idealized environment before an attack occurs. This leaves the post-compromise setting underexplored. To address this gap, we introduce SecRespond, the first

Large language model agents often encounter related yet distinct tasks that share reusable solution patterns. Yet standard agentic reinforcement learning treats tasks as independent episodes, while existing approaches to skill learning either focus on repeated attempts of one task or use pipelines with multiple stages that entangle extraction, retrieval, and execution. We introduce SkillRise, a unified reinforcement learning framework for learning skills across tasks. SkillRise organizes related

Many kinds of data have structure along one or more axes: words in a sentence, pixels in an image, nodes in a tree, frames in audio, or cells in a 3D volume. Along one axis, order matters: "the dog bit the man" is different from "the man bit the dog." Across independent axes, however, neither composition nor movement should depend on the order of axes: in an image, composing right then down should give the same result as composing down then right, and moving right then down should describe the s

Latent communication in large language model (LLM)-based multi-agent systems (MAS) transmits continuous internal representations instead of text, but greater representational capacity does not establish that the receiver uses task-relevant information. End-task performance alone also cannot reveal whether an observed effect depends on message presence, content generated for the evaluated example, or information supplied by a separate agent. We introduce a causal audit that applies controlled mes

Multimodal large language models increasingly use sketches, annotations, tools, and intermediate images during reasoning, but it remains unclear whether they truly rely on these visual states. Existing benchmarks are limited both by task collections with narrow coverage or partially text-solvable samples and by evaluations that emphasize final answers without diagnosing how intermediate visual states are generated, rendered, and used. We introduce See2Think, a unified evaluation framework compri

Background: Digital multidomain interventions hold promise for dementia risk reduction; however, populations at higher dementia risk, including those experiencing socioeconomic and educational disadvantage, remain underrepresented in trials, and engagement with digital interventions often declines over time. Coproduction and blended models that combine digital tools with human support may improve reach, acceptability, usability, and sustained engagement. Designing interventions that are usable a

Zero-shot text-to-speech (TTS) clones a voice from a short audio prompt, but this reliance on reference audio is a barrier when only visual information is available, e.g. for historical figures or video-game characters. In this work, we propose a Face-to-Speech (F2S) framework that predicts a plausible voice from a static facial image. A lightweight Face Adapter, together with soft-tuning of the face encoder's upper blocks, aligns face-recognition features with the style space of a frozen StyleT

Prompt inversion, as a typical reverse engineering technique, enables text-to-image (T2I) diffusion models to generate the desired target images without extensive prompt engineering. However, existing prompt inversion methods suffer from significant limitations: (1) gradient-based methods are unstable and uninterpretable, often resulting in generated images with severe artifacts; (2) gradient-free methods yield human-readable prompts but still fail to preserve visual fidelity due to the lack of

Cover song generation (CSG) should preserve the melodic and linguistic content of a reference song while recreating the remaining musical components. The state-of-the-art model SongEcho utilizes $F_0$ sequences and voiced/unvoiced (V/UV) tags for conditioning; however, implicit linguistic information from V/UV tags cannot guarantee lyric accuracy, leading to a high phoneme error rate (PER). Inspired by singing voice synthesis (SVS), we propose MPEcho, which integrates a phoneme encoder and a len

Ascend C operator optimization is critical for NPU (Neural Processing Unit) inference performance but requires deep hardware expertise.While large language models (LLMs) have shown promise in automated CUDA kernel generation, the fundamentally different programming model of Ascend C introduces unique challenges that remain unexplored. In this paper, we propose AgenticCANN, a knowledge-augmented agentic evolution framework specifically tailored for automated Ascend C operator synthesis in low-cor

Post-training alignment is often shallow, eroding under fine-tuning. Whether midtraining interventions, cleanly isolated from post-training, can produce durable alignment remains untested. We test this via constitutional midtraining: inserting principled, values-based content into midtraining against a replay-only control at 120B scale. Our 394M-token constitutional corpus, built from Anthropic's Constitution, uses a 2x2 factorial design (curriculum ordering x deliberative reasoning) to produce

Enabling large language model (LLM) agents to accumulate and reuse experience from past interactions remains a central challenge in real-world applications. A promising solution is to treat skills as trainable states and optimize them in the same way as model parameters in neural network training. However, data-driven skill optimization is prone to overfitting to the limited trajectories collected from real environments. Overexploiting these trajectories overfits the current batch, while unconst

Identity document (ID) authentication relies on the structural integrity of complex, high-frequency security patterns. However, advanced Generative AI models can now inject localized, high-fidelity manipulations, creating deceptive attacks that bypass standard verification. Training robust image forensic models to detect these anomalies is hindered by privacy regulations, forcing reliance on synthetic templates lacking the intricate visual patterns of real IDs. To bridge this domain gap, we intr

Current human evaluation of machine translation typically assesses single outputs in isolation, a paradigm that suffers from high annotator noise and cost. We introduce Contrastive Error Span Annotation (cESA), a protocol that presents multiple translations of the source input (text, video, audio, image). In cESA, the annotator sees multiple translations of the same document, marks major and minor error spans, and then assigns a score from 0% to 100% on absolute scale. By allowing annotators to

Human Activity Recognition (HAR) from wearable sensors supports applications in healthcare, rehabilitation, fitness tracking, and smart environments. Yet, existing deep learning approaches require dataset-specific training, large labeled corpora, and repeated adaptation to new sensor settings or activity taxonomies. Retrieval-Augmented Generation for Human Activity Recognition (RAG-HAR) addresses this by framing HAR as a training-free, retrieval-augmented task, in which statistical descriptions

Large language models (LLMs) have demonstrated strong reasoning capabilities, motivating their adoption as backbones for foundation recommendation models (FRMs). Existing approaches typically enhance recommendation with explicit Chain-of-Thought (CoT) under the Think-then-Answer paradigm. However, generating lengthy rationales introduces substantial inference overhead, while fixed CoT templates struggle to model diverse, dynamic, and context-dependent user interests. We propose WhisperRec, an ef

AI-assisted coding increasingly translates informal user intent into executable software, yet coding requests often contain ambiguities that recur in user-specific ways across tasks and sessions. Existing disambiguation methods typically address each ambiguous request in isolation within the current coding session, often through eliciting additional clarification. However, whether resolved session history from the same user can serve as memory for resolving recurring personalized ambiguity in a

The rapid development of large language models (LLMs) has renewed interest in agent-based modeling (ABM). However, current LLM-based ABM research faces several key challenges: modeling evolving agent-environment interactions, enabling flexible counterfactual reasoning, and automating simulation workflows for scientific research. In this paper, we propose Eco3S, a socio-economic system simulation framework for economic research and policy analysis that addresses these challenges through three key

Safety classifiers ("guards") are the dominant black-box defense for vision-language models, yet they judge an input's surface form, not its meaning: a harmful request re-encoded as set theory, formal logic, a rare language, code, or an image of text slips past a guard that would block it in plain language -- the decode gap. The natural fix is a guard-agnostic recover-and-decode amplifier that transcribes image content and restates encoded text into its plain payload before the guard, so any off

Text-to-image (T2I) workflows are increasingly deployed on serverless platforms because users often compose customized workflows and invoke them intermittently. Existing platforms typically deploy each workflow as an opaque GPU function, provisioning, placing, and scaling all constituent models in the workflow together. This monolithic design obscures workflow structure, inflates scaling overhead, forces users to manage low-level GPU coordination, and limits fine-grained fairness in multi-tenant

Audio-capable foundation models enable end-to-end spoken interaction, but they also introduce safety risks beyond transcript content. It remains unclear how much jailbreak capability can arise from matched-text variation in speech delivery rather than from lexical rewriting or broader style transfer. We study this question by holding transcript content fixed and varying six speech-delivery presets whose acoustic attributes may co-vary. We present PJ-Break, a black-box evaluation protocol with pr

Visual network analysis leverages network visualization authoring techniques to facilitate sensemaking, serendipitous discovery, and hypothesis verification on network data. However, transferring the same paradigm to immersive environments is non-trivial due to insufficient UI affordance for authoring operations. Researchers have studied combining multiple modalities for interactions, but the high learning curve of such input systems limits their adoption by typical data analysts, let alone for

Resource allocation across multiple agent groups arises in many applications including e-commerce recommendation systems, housing assignment, and course allocation, and is commonly formulated as an optimization problem with diversity constraints to ensure group fairness. Existing approaches typically enforce these constraints as hard conditions, which overly restrict the feasible solution space and often lead to suboptimal allocations. In this paper, we propose PRA, a parameterized framework for

Publication date: September 2026 Source: Technology in Society, Volume 88 Author(s): Paloma Almodóvar, Alberto Ferraris

Publication date: September 2026 Source: Technology in Society, Volume 88 Author(s): Femi Olan, Konstantina Spanaki, Uchitha Jayawickrama

Publication date: Available online 27 July 2026 Source: Computers and Education: Artificial Intelligence Author(s): Bernard Yaw Sekyi Acquah, Iddrisu Salifu, Francis Arthur, Mark Inkoom, Sheriff Dagimah Suradji, Christian Inkoom, Emmanuel Quayson, Silas Afutu Quaye, Francis Obeng Gyedu, Sharon Abam Nortey

Publication date: Available online 27 July 2026 Source: Computers and Education: Artificial Intelligence Author(s): Richard Chung Yiu Yeung, Chi Ho Yeung, Daner Sun, Therese Keane, Yuqin Yang

Publication date: October 2026 Source: Research Policy, Volume 55, Issue 8 Author(s): Matthias Tröbinger, Anil R. Doshi, Sen Chai

World models must learn the joint dynamics of states, actions, events, and observations, yet existing video, robotics, and simulation datasets usually capture only part of this structure. We introduce CG-World, a large-scale world-state dataset and protocol derived from industrial computer graphics production pipelines. CG-World explicitly records intermediate states, including multimodal semantics, spatial structure, skeletal and controller states, motion curves, camera and lighting parameters,

arXiv:2607.25105v1 Announce Type: new Abstract: Social choice theory research demonstrates that single transferable voting (STV) results in more proportionally representative legislative bodies. We aim to understand how using multi-member districts and ranked ballots with STV would affect the representation of political parties in the Colorado House of Representatives. We investigated this objective by producing 10,000 multi-member districting plans of Colorado, generating ranked ballots for eac

arXiv:2607.25301v1 Announce Type: new Abstract: Resting heart rate is an established marker of cardiovascular risk, but population-scale measurement has depended on clinical or survey instruments. We ask whether passively sensed consumer-wearable physiology recovers the socioeconomic gradient established in clinical cohorts. Using 19.1 million quality-filtered photoplethysmography readings from 18,734 opt-in users of the Welltory app, we computed cohort-adjusted mean daytime resting heart rate p

arXiv:2607.25526v1 Announce Type: new Abstract: How should researchers measure the geopolitical preferences expressed by large language models (LLMs)? Existing audits commonly rely on surveys and simple tests, but international-relations research has long recognized that measuring geopolitical preferences is difficult and has developed methods for recovering them from observed choices. This paper applies a dynamic ordinal ideal-point approach from international relations, treating LLMs as respon

arXiv:2607.25648v1 Announce Type: new Abstract: 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 - under

arXiv:2607.24755v1 Announce Type: cross Abstract: This full research paper examines how different forms of learner-AI interaction relate to learning outcomes in object-oriented programming (OOP) courses. Generative artificial intelligence (GenAI) tools are increasingly used by students in programming education, yet evidence on their educational impact remains mixed. In particular, little is known about how students integrate GenAI tools when learning OOP, and how different patterns of use relate

arXiv:2607.24757v1 Announce Type: cross Abstract: This paper reports on the rapid development and classroom deployment of a Thonny log visualizer built using AI-assisted ``vibe coding'' to make students' programming processes easily visible to teachers. We developed a web application that analyzes log files generated by Thonny (an IDE for Python) and produces interpretable views of students' programming processes. Teachers can upload a log, a ZIP archive, or a folder containing logs for a group

arXiv:2607.24759v1 Announce Type: cross Abstract: Research projects, educational efforts, and adjacent knowledge work accumulate findings, decisions, and reasoning that future collaborators rarely recover. The parts most useful to that work, including dead ends and walked-back claims, are routinely excluded from publications and shared code; future researchers re-attempt the same failures because no record survives. LLM coding agents are common participants but hold no persistent memory across s

arXiv:2607.24768v1 Announce Type: cross Abstract: Prenatal care is an important preventive service designed to improve outcomes for pregnant individuals. The American College of Obstetricians and Gynecologists (ACOG) recently introduced guidelines advocating tailored prenatal care, called PATH (Plan for Tailored Healthcare). We present PATHFinder Agent(Planner for Appropriate Tailored Healthcare), an end-to-end conversational agentic system that gathers patient health and social context through

arXiv:2607.24775v1 Announce Type: cross Abstract: Artificial intelligence (AI) chatbots are increasingly deployed in domains where empathy is essential, including healthcare, education, and customer service. However, their capacity to sustain authentic human moments remains structurally limited. This paper introduces two interlinked conceptual models to explain and address this limitation. First, the Human-Moment Gap Framework (HMGF) identifies three structural empathy deficits in AI-mediated in

arXiv:2607.25010v1 Announce Type: cross Abstract: AI-assisted production has sharply reduced the cost and team size required to ship a video game, producing a supply shock on open marketplaces. Recent estimates put Steam release volume at roughly sixty new titles per day, with median per-title revenue for a large share of releases falling below the platform's own submission fee [1]. This paper asks whether the resulting oversupply constitutes an emerging market crash or a structural correction,

arXiv:2607.25057v1 Announce Type: cross Abstract: As conversational AI systems become increasingly integrated into daily life, their potential effects on user well-being require ongoing attention. While consumer-facing generalist models can provide benefits, including improved access to information, learning, productivity, self-reflection, and companionship, they also introduce risks, such as emotional entanglement, unhealthy dependence, and the amplification of psychological vulnerabilities. Dr

arXiv:2607.25425v1 Announce Type: cross Abstract: Capture the Flag (CTF) competitions are among cybersecurity's most effective training grounds, developing practical skill across cryptography, web exploitation, and binary exploitation. Large language models (LLMs) can now solve a growing share of challenges with minimal human input, raising urgent questions about fairness, the validity of rankings, and whether participation still delivers the learning that justifies the effort. This paper report

arXiv:2607.25750v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) fine-tuning has made it cheap and easy to customize open-weight image generation models for specific tasks, including the production of child sexual abuse material (CSAM). Existing moderation relies on metadata or generated outputs, but metadata can be deceptive and generating outputs may itself be unacceptable or illegal. We show that a safer signal lives in the weights. The top-left singular vectors of a LoRA's update

arXiv:2607.25974v1 Announce Type: cross Abstract: Observed standardized test scores are the result of an endogenous process: students strategically allocate effort across multiple retake attempts to improve their outcomes. Because students differ in their ability to make these investments, the interaction between applicant strategy and institutional scoring rules---such as the widely used Single-Sitting and Superscoring policies---can disparately distort observed scores. We develop a strategic f

arXiv:2507.11548v3 Announce Type: replace Abstract: The use of publicly available generative AI systems for resume evaluation is often justified by the assumption that these tools reduce bias relative to human judgment. However, this framing leaves a prior question unresolved: whether these systems are capable of performing the evaluative task at all. This study presents a two-part audit of eight widely used AI platforms used for resume screening. Drawing on the concept of the Illusion of Neutra

arXiv:2602.08554v2 Announce Type: replace Abstract: This workshop paper examines challenges in designing agentic AI systems from a citizen-centric perspective. Drawing on three participatory workshops conducted in 2025 with members of the general public and cross-sector stakeholders, we explore how societal values and expectations shape visions of future AI agents. Using constructive design research methods, participants engaged in storytelling and lo-fi prototyping to reflect on potential commu

arXiv:2604.03881v2 Announce Type: replace Abstract: Encouraging pro-environmental behavior remains a major challenge for sustainable cities. Conventional feedback nudges can show individuals how their current behavior compares with environmental goals but often provide limited guidance on what to do differently in daily life. This study examines whether supplementing weekly feedback on participants' behavior with LLM-generated personalized action suggestions improves pro-environmental behavior,

arXiv:2606.30860v2 Announce Type: replace Abstract: As large language models (LLMs) become common in computing courses, we need to understand how the social setting shapes how students use them. This paper reports findings from a semester-long study of 96 undergraduate students who completed six assignments, alternating between individual homework and team project milestones. We tracked LLM usage, prompting habits, and how students verified AI-generated output across all six assignments. LLM usa

arXiv:2607.21534v2 Announce Type: replace Abstract: The spread of generative AI (GenAI) in higher education has raised concerns that students offload cognitive effort to AI, earning high grades without learning. If this "GenAI substitution hypothesis" is true, grades should rise disproportionately in GenAI-susceptible courses--those relying more on assessments like take-home problem sets and essays rather than in-class exams. Substitution could also affect student satisfaction, measured here as

arXiv:2311.18424v3 Announce Type: replace-cross Abstract: Developing artificial intelligence (AI) algorithms for healthcare is a collaborative effort, bringing data scientists, clinicians, patients and other stakeholders together. By understanding AI as 'sociotechnical' where the social and the technical nature of the work and the models are inseparable, we explore the AI development workflow and how stakeholders navigate the challenges and tensions of sharing and generating knowledge across dis

arXiv:2508.03037v5 Announce Type: replace-cross Abstract: Artists occupy a paradoxical position in generative AI. Their own work trains models that now compete with them, replicate their styles, and reshape the creative economy they inhabit. Yet whether artist concerns achieve proportional representation in the public discourse that shapes AI governance remains an open empirical question. We mapped the semantic landscape of public AI-art discourse from 2013 to 2025, drawing on 1,736 text chunks

OpenAI-Modelle attackierten vergangene Woche scheinbar weitere Software. Die Firma erklärt nun ausführlicher, was genau passiert ist.

According to CCTV News, the National Energy Administration (NEA) held a press conference on Wednesday, announcing that China’s renewable energy sector saw rapid growth in the first half of 2026, with renewable power generation accounting for more than 40% of total electricity generation for the first time. During the first half of the year, China’s […]

A majority of surveyed global asset management firms plan to raise their artificial intelligence budgets by at least 50 per cent within the next year as the technology transforms the finance industry, a recent study showed. The adoption of AI is also going to have a big impact on labour-intensive operations: 62 per cent of polled fund managers expect transformative change in data generation and summarisation, according to a study released Tuesday by US fintech firm Clearwater...

Bond markets are increasingly dominated by a bet on the same thesis as other asset classes

Operators blame planning rules and low prices for a lack of investment

The co-founder of the UK-based science start-up explains how AI can help create new materials to address some of the world’s most complex challenges

Start-up Ahbstra applies MOF technology to draw moisture from the atmosphere at volume, using minimal energy

Join experts at MediaNama event to discuss age verification, social media restrictions for children, platform design, privacy, online safety, and practical regulatory approaches. The post Final Call: Age Verification and Restricting Social Media for Children, Delhi, 31 July #NAMA appeared first on MEDIANAMA .

Hedge fund has held talks with existing investors and lenders in recent days

Author Joyce Carol Oates came to the defense of Christopher Nolan’s “The Odyssey” after translator Emily Wilson wrote a viral review attacking the film. “Rather than disagreeing with interpretations of Homer in a collegial manner, this person, who has benefited enormously from Nolan’s film, speaks in the crude language of MAGA folks attacking someone with […]

China's Commerce Ministry said Thursday the U.S. Federal Communications Commission has repeatedly ignored Beijing's restrained stance.

For investors anxious to hear more about Meta's plans to make money from its big AI spending, Mark Zuckerberg said there's a trade-off.

Christie's auction house handled the One Goal auction, which benefits the FIFA Global Citizen Education Fund, a $100 million initiative to expand access to quality education and football for children worldwide.

The ranking member of the House Committee on Energy is demanding SpaceX records and a tour of its data centers and power plants in and around Memphis.

First-in-nation law sets up test on states’ power to regulate use of AI as it tries to outlaw fake nude images of real people Elon Musk’s company xAI has sued Minnesota over the state’s first-in-the-nation law banning “nudification” technology on websites and apps, potentially providing a test for how far states can go in constitutionally regulating the use of artificial intelligence. Musk’s company sued on Monday in federal court, days before the law is set to take effect on Saturday and make M

Freehand, a startup building AI agents that manage supply-chain spend for giants including Meta and Pfizer, has raised $75 million in funding.

Social media chief defends strategy based on personalised bots as costs rise and revenue projections disappoint

“The White House Office of Science and Technology Policy (OSTP) will convene an interagency group to monitor advancements at the intersection of biological sciences and artificial intelligence, including in silico life sciences research,” the guidance says.

The New Jersey-based workers unanimously declared their support for joining LiUNA Local 724 in the labor group’s first victory on a CBS Studios series.

Lawyers for former president insist he did not authorise the projection following legal challenge from leftwing groups

OpenAI is trying to reassure employees that the business is healthy as competition emerges from Anthropic as well as a host of open-source players.

The Enhancing K-12 Cybersecurity Act failed to pass in 2023. Sens. Mark Warner and Marsha Blackburn said their bill is urgently needed in 2026.

As Meta pours billions into AI infrastructure and agents, Zuckerberg is working to convince investors that the payoff will be worth the price.

When Microsoft reported killer fourth-quarter earnings for its fiscal 2026 year (which ended June 30), it tucked in an interesting little tidbit about how its investments in the two biggest, and competing, AI labs are doing.

Howard Revisits Disenrollment Decision Joshua.Bay Wed, 07/29/2026 - 06:27 PM In a conversation with  Inside Higher Ed , Interim President Wayne Frederick said Howard reinstated more than 200 students and outlined changes to improve communication. Byline(s) Joshua Bay

On the company’s second-quarter earnings call Wednesday, CEO Mark Zuckerberg said Meta sees a “large enterprise opportunity” spanning AI agents, APIs, compute, and internal software.

Microsoft is working on an AI "super app" that combines Copilot's chat, coding, and agentic capabilities. During an earnings call on Wednesday, Microsoft CEO Satya Nadella said the app will span "both consumer and commercial experiences" when it launches this year. "Copilot is evolving rapidly from chat to Cowork to Autopilots," Nadella said. "This quarter, […]

Microsoft’s fiscal Q4 revenue of $90 billion topped Wall Street targets, while Copilot reached 30 million paid seats, and an investment in Anthropic delivered a $3.2 billion windfall.

Meta is all-in on AI, and sometime soon, the company is going to make a big push into personal AI agents that can do things on your behalf. On Wednesday's Q2 2026 earnings call, CEO Mark Zuckerberg previewed a high-level vision of how the company is thinking about personal agents and what it will do […]

A standoff over the restrictive voting bill Trump is pushing has left nerves raw at the Capitol, with even the typically staid Thune showing signs of frustration.

Hwaseong, South Korea, past midnight. An engineer watches a defect pattern surface on her screen – the kind that, caught now, saves a week of wafers. She is locked in, fully absorbed, the way engineers get when a breakthrough is close. But she has to go home. The law says so. Yet something is disrupting the clock she races against. Artificial intelligence is quietly rewriting what her hours are worth. On June 29, South Korean President Lee Jae Myung stood alongside the leaders of Samsung...

At TechCrunch Disrupt 2026, the AI Stage is back to dig into the single hottest topic in the community for the past few years, presented by Google for Startups.

Weng previously served as the VP of AI Safety Research at OpenAI.

xAI is suing Minnesota Attorney General Keith Ellison over a law passed back in May that broadly targets "nudification" apps, claiming that the statute's punitive provisions leave the company with "no practical choice but to restrict Grok Imagine's image-editing features in various ways." The law, the company argues, violates the First Amendment. Back in January, […]

In a three-hour hearing Wednesday, Dr. Anthony Fauci, the influential scientist who led the national response to COVID, refused to respond to questions about his role in school closures and the mask and social distancing guidelines that experts say have drastically set back students’ learning. Subpoenaed by Sen. Rand Paul of Kentucky, the Republican chair […]

Takes aim at eSafety.

The post Senators Push Federal Regulator to Prove School Bus Safety Data Is Accurate appeared first on ProPublica .

The future of artificial intelligence depends on finding more skilled humans for some very physical jobs.

The agency wants automation tools to improve efficiency amid an increasing volume of requests, but advocates of transparency and accountability have concerns. The post Homeland Security plans to add more AI to FOIA processing appeared first on FedScoop .

Government ban on foreign-made robots may hinder instead of help US robotics.

Is more data about your body actually good for you?

OpenAI revealed rogue AI models compromised more services than initially disclosed, including a Modal customer environment and others.

Robots apparently don't need to be bipedal to be caught up in the FCC's new foreign-made robot ban.

The agentic AI playing field was heavily tilted toward offense, so researchers began using red team agents to help teach their blue counterparts.

In the latest example, the Energy Department will convert a shuttered Cold War-era uranium enrichment facility into a data center campus and gas plants.

Waymo paused highway operations in May after several robotaxis drove into sections that were closed for construction.

New bipartisan legislation would employ artificial intelligence to improve the longitudinal data systems built by state governments to improve educational and workforce outcomes.

As Bryan Kohberger challenges his conviction for murdering four Idaho college students, a new Netflix documentary examines what we know about the case

5 current and former government technology officials assess whether federal cyber defenses can keep up.

Agentic AI systems threaten cybersecurity as we know it. A new generation of cyber-capable models, including Anthropic’s Mythos and OpenAI’s GPT-5.6, can find and exploit vulnerabilities in computer systems far faster than human hackers. The technology is so powerful that it has spooked the U.S. government, which has moved to limit, or completely pause, the public release of these models. How well prepared is the Trump administration to secure the government’s computing resources? The rise of ag

Less than a week after OpenAI disclosed that two experimental AI models escaped their testing environment during a cybersecurity exercise The post Anthropic backs urgent call for the most powerful AI labs to hit the brakes appeared first on The New Stack .

As agentic services diversify across the entire enterprise technology stack, the rise of agentic coding tools is being challenged by The post “The beast needs a cage”: Why PortSwigger’s agentic pentesting is kept safe behind bars appeared first on The New Stack .

I watched a new tool try to get around the model safeguards of four major frontier companies. You might be surprised by how they performed.

Pencils are more expensive. So are notebooks, scissors, glue sticks — just about every back-to-school item that families will load into their literal or virtual carts this summer has gone up in price at a time when American families already feel crushed by rising costs. According to one analysis of the 21 most common school […]

Kenya's new crypto rules now empower authorities to seize and convert crypto assets into fiat asset to preserve value during investigations.

The OpenAI CEO discussed a forthcoming artificial intelligence model with federal lawmakers as the cybersecurity debate over the advanced technology intensifies.

Following KPMG, Deloitte, and Ernst & Young, GPTZero has now found fabricated sources and false claims in four PwC Middle East reports. One governance report scored 84 percent AI-generated and promoted a PwC product with unverified customer references. All Big Four firms are now affected by AI hallucinations. The article PwC has allegedly published AI-generated reports containing false or fabricated sources appeared first on The Decoder .

Dark Reading walks through the many twists and turns in the bizarre story of how OpenAI's agent AI system broke out of its sandbox and decided to target Hugging Face, and what CISOs should be aware of.

Dark Reading Confidential Episode 20: Expert Rich Mogull reflects on lessons cyber teams should pull from the OpenAI agent's attack on Hugging Face.

In 2021, Andrew Ivey wrote, “‘I Have Other Data’: The Guardia Nacional and the Entrenchment of Mexico’s Militarization’,” where he warned Mexico was headed toward a militarization trap. Five years later, amidst increased pressure from the Trump administration and the election of a new Mexican president, we asked Andrew to revisit his arguments.Image: Sitio Oficial de Andrés Manuel López ObradorIn your 2021 article, you warned that Mexico was headed toward an entrenched militarization trap. In 20

The new rules give the central bank direct oversight to cut off local access to foreign stablecoins without having to regulate the offshore issuers themselves.

The four additional targeted organizations weren’t named. OpenAI said they were not affected as severely as Hugging Face.

Los dispositivos de localización de objetos tipo AirTag han ganado mucha popularidad en los últimos años para seguirle la pista a todo tipo de pertenencias. Sin embargo, cuando se trata de animales, los sistemas pasivos por Bluetooth se quedan cortos en zonas de campo o cuando el animal se desplaza rápido. Mova, una marca reconocida en el sector del hogar conectado por sus robots aspiradores , ha dado el salto al cuidado de animales con el SureTrack Pro , un localizador GPS diseñado específicame

Los astrónomos llevan décadas intentando desentrañar los misterios de la materia y la energía oscura . Sin embargo, ahora un equipo de científicos de la Universidad de Oxford ha lanzado la más controvertida de las soluciones : no hay nada que buscar, porque la energía oscura no existe. Y se han quedado tan panchos. Lógicamente, las reacciones no se han hecho esperar. Algunos investigadores creen que es una solución interesante en la que vale la pena seguir indagando. Otros, en cambio, consideran

The lawmaker referred to the legislation as the "latest counterproductive attempt to hold Russia accountable for its war against Ukraine."

MoonPay, the global financial technology company powering the movement of value across fiat and digital assets, has launched PayBox, the first payment vault built for AI that lets a person's AI agent transact on the open internet without leaving the conversation.

The initiative is intended to modernize and consolidate IT and data architectures at the Naval Surface Warfare Center Corona Division. The post Navy using LETHALITY Consortium to advance network consolidation initiative appeared first on DefenseScoop .

In Carlsbad, N.M., a tiny district in the southeastern corner of the state, nine of its 12 schools have turned teacher assignments upside-down, inviting their best teachers to coach a team of colleagues, model lessons and take direct responsibility for the achievement of every student the team serves. In exchange, each teacher-leader earns substantially more […]

Nigeria no longer has a payments problem. It has a trust problem. That is the central argument of a new report by Bridgforte, a policy research institute, published in partnership with the United Nations Development Programme (UNDP) Innovation Hub in Lagos, which argues that confidence in Nigeria's financial system is now determined less by how quickly money moves than by how reliably the system responds when something goes wrong. The country processed more than ₦1.2 quad

An OpenAI agent compromised a customer of another technology company, the New York-based firm Modal Labs announced Wednesday. In a technical timeline posted Tuesday, the tech startup Hugging Face explained how an OpenAI agent escaped the AI firm's isolated testing sandbox and accessed another testing environment "hosted by a user of a third-party infrastructure provider."...

We’re looking for college and high school students to tell us about A.I.

Claim was launched with 'blaze of publicity' and 'monstrous all-out attack' on Mail. The post Mail spent £35m fighting Harry’s ‘campaign for Leveson 2’ privacy claim appeared first on Press Gazette .

Jim Cramer said investors should look to Seagate Technology as a barometer of whether the AI infrastructure trade can regain momentum on Wednesday.

The process remains in its early stages. No investors have emerged yet, AMCON spokesperson Jude Nwauzor said.

La FCC a ajouté les robots humanoïdes et les onduleurs électriques fabriqués à l'étranger à sa liste noire des équipements jugés dangereux pour la sécurité nationale américaine. Une décision qui vise sans le dire la Chine, leader mondial de la robotique avancée.

Sandboxes for AI agents may feel like a solved problem. After all, projects like Firecracker, the open-source microVM technology AWS built The post “Stateful systems are incredibly hard to build”: How Perplexity thinks about AI agent sandboxes appeared first on The New Stack .

As his family's financial situation worsened, earning an income became just as important as pursuing a university education.

Here are five key things investors need to know to start the trading day.

The Last Sentinel developer attributes the job cuts to a shift in creative and development direction for the project.

Strong corporate results buoy market as investors move money away from tech and semiconductor stocks London’s FTSE 100 stock index has touched a fresh high, driven by strong corporate results as investors moved money away from tech and semiconductor stocks amid the global tech stock sell-off . The UK’s blue chip index rose as high as 10,951 points on Wednesday morning before falling back slightly, its best level since 27 February, the day before the US and Israel began attacks on Iran and sparke

It started as China vs. the US, but it's become a face-off between two fundamentally different ways of building LLMs. And the safety of everything is on the line.

Some companies reportedly using leaderboards for employees who used the most AI in their work Follow our Australia news live blog for latest updates Get our breaking news email , free app or daily news podcast Software firm Atlassian has sought to tighten tracking of its staff’s AI spending by introducing “wallets” with monthly caps of up $2,000 for each employee, amid an explosion in costs at other tech companies. The move by Atlassian, which recently cited AI as part of the reason behind cutti

For years, financial institutions have treated compliance as a cost of doing business. A regulation ...

China has criticized the move, accusing the U.S. of protectionism.

The startup analyzes calls, messages, and CRM data to identify effective sales techniques and turn them into playbooks for AI agents.

The vulnerability in the AI hosting platform Ruflo allows an unauthenticated attacker to take over the system and corrupt memory, so bad behavior can persist after patching.

Once upon a time, a knight in shining armor rode his gallant steed into a village where he was met with cheers and celebration. I like to believe that these heroes still exist — I know one named Fluviano. He’s a student in my English language development class. He does not ride atop a gallant […]

The Federal Communications Commission (FCC) has banned imports of foreign-produced humanoid robotic devices and power inverters, citing “national security” as its primary concern. The devices were added to the FCC’s covered list, meaning the products posed an “unacceptable risk to the national security of the United States or the safety and security of United States...

If 2024 was about GenAI experimentation and 2025 was about finding use cases, 2026 is the year of operationalisation, governance and control. Take a look at our product launch table […] The post The latest Orange Rag Product Table – link here appeared first on Legal IT Insider .

Korean retail investors have racked up heavy losses from leveraged bets on stocks, following rule changes earlier this year.

Artificial intelligence is reshaping the skills employers expect from new graduates. In response, universities are scrambling to launch new courses, research centers, and industry partnerships that prepare students for today’s workforce. But building a cutting-edge AI curriculum demands funding and access to industry networks, resources that remain unevenly distributed across higher education. At North Carolina Central University, Siobahn Day Grady is trying to change that equation. In January 2

The visionary PhysioNet platform launched 25 years ago, based on a system developed at MIT in the 1970s. It has become one of the most comprehensive biomedical and clinical data repositories in existence.

Babylist founder Natalie Gordon will become executive chair, in a rare founder-to-founder CEO transition.

When I sit down with leaders and ask why they’re investing in AI, the answer almost always comes back to The post Turning 10x developers into 10x value appeared first on The New Stack .

Canadian investment group to partner utility NextEra on data centre in Kentucky

Der Angriff einer KI von OpenAI hat größere Ausmaße als bislang vermutet. Der KI-Agent attackierte vier weitere Onlinedienste und griff gezielt fremde Zugangsdaten ab.

SpaceXAI part en croisade contre une loi du Minnesota interdisant les technologies de « nudification », qui permettent de générer des deepfakes dénudés de personnes réelles. L’entreprise est la première concernée, puisque son chatbot Grok est massivement utilisé pour créer ces images. En début d’année, Grok était sous le feu des critiques : le chatbot de xAI […]

Chinese home appliance maker Midea reported that European demand for its air conditioners continues to soar amid recurrent heatwaves, with two of its factories receiving hundreds of thousands of new orders in a month. The factories, in the eastern city of Wuhu and the southern port city Guangzhou, received new European orders for 200,000 units within a month amid “explosive demand”, the company said in a statement on Wednesday on the Shenzhen Stock Exchange’s investor Q&A platform. The company..

In this edition of AI Prognosis: A conversation about benchmarking leading clinical chatbots, investor view on AI in biopharma, and more.

The Ar Gen 1 is an impressive device, suitable for anyone from students to developers to business owners.

Executives from BCX, Telkom Business and Openserve hosted a channel event to champion trusted data as the foundation of an intelligent company.

Serena Williams doesn’t just defy convention on the tennis court. She’s also applying her competitive mindset to entrepreneurship and venture investing, recently rebranding her firm from Serena Ventures to Starfire Ventures. Williams discusses the investment strategy that has led to 16 unicorns now in her portfolio, what she looks for in founders, and how partnerships with companies from Nike to Ro fit into her broader vision.  This is an abridged transcript of an interview from Rapid Respo

As more companies plug AI agents into the deepest depths of their internal data banks, how can they be sure The post Modus’s operandi: To give AI agents just the right amount of context appeared first on The New Stack .

Agents are writing code faster than humans can review it. The answer is not “review faster”; that would be like The post Shipping code without human verification appeared first on The New Stack .

Samsung und SK Hynix investieren zusammen über eine Billion US-Dollar in neue Fabs. Silicon Motion startet die Entwicklung von SSD-Controllern für PCIe 7.0.

Das "KI-Update" liefert drei mal pro Woche eine Zusammenfassung der wichtigsten KI-Entwicklungen.

American Television Alliance says FCC is issuing conflicting guidance on raising retransmission consent cost issues in connection with TV station mergers and TV station ownership rulemakings

ChatGPT developer says activity by autonomous tool was not at severity or scale of what occurred at Hugging Face OpenAI has revealed that a cyber-attack carried out by a rogue AI agent had more than one victim. The ChatGPT developer said the agent – an autonomous tool able to carry out sequences of commands without human help – had located and used logins to access four other unnamed “publicly-available services” in addition to the US startup Hugging Face. Continue reading...

China’s robotics firms have run into a fresh obstacle in their global expansion, after the United States banned imports of new foreign-made models, which analysts say could benefit Tesla and other American developers. The Federal Communications Commission (FCC) added foreign-produced “advanced robotic devices” to its Covered List on Tuesday, blocking new models from obtaining the authorisation required to be imported and sold in the US. The ban will cover all new humanoids, quadrupeds and a...

A standardized framework for regulating the safety and efficacy of AI in healthcare has yet to be established.

EEUU sabe qué se siente cuando China controla un recurso crítico y decide usarlo como palanca en la mesa de negociación. Le ha pasado con las tierras raras y otros minerales estratégicos, y no quiere que se repita ni con la robótica ni con la electrónica de potencia que sostiene sus centros de datos de inteligencia artificial (IA). Este es el escenario en el que el Gobierno liderado por Donald Trump ha decidido actuar antes de que esta dependencia se convierta en una vulnerabilidad. La Comisión

Ya está en marcha el primer data center de Inteligencia Artificial impulsado por energía eólica de China . Se trata de una innovadora instalación en la Región Autónoma Hui de Ningxia, en la parte noroccidental del país, y cuenta con un suministro de energía renovable que le permite operar usando electricidad 100% limpia. Esto supone todo un hito para el país asiático y también para la industria global si tenemos en cuenta el debate que suscita el enorme impacto medioambiental de estas infraestru

The Nasdaq 100 is flirting with correction territory as investors brace for earnings reports from Meta, Microsoft and Amazon.

The AI agent that escaped from OpenAI and hacked developer platform Hugging Face attacked other companies as well, OpenAI revealed on Tuesday. The update substantially widens the scope of an already concerning incident, which has alarmed industry insiders and fueled growing calls for stronger oversight on frontier AI systems. In an update to a blog […]

OpenAI has released Codex Security CLI, an open-source tool that automatically detects and fixes vulnerabilities in code repositories. Previously known internally as "Aardvark," the system has already helped fix more than 3,000 critical security flaws, according to OpenAI. It competes directly with Anthropic's Claude Security, as both AI companies race to match the growing automation of cyberattacks with AI-powered defense. The article OpenAI open-sources Codex Security CLI to help developers fi

The regulator said a fee of between £237,500 to £712,500 per megawatt should be charged for upcoming projects.

Google on Wednesday launched its artificial intelligence agent Gemini Spark in the Hong Kong market, giving local users direct access to a smart assistant to manage complex digital workflows. The launch came months after the American tech giant’s decision in March to lift regional geofences for generative AI services, starting with the Gemini chatbot. Hong Kong users can now access Gemini without using a virtual private network or third-party platform. The roll-out of the Spark agent echoes an..

Years ago, we didn’t have SQL. There were people whose job was to generate software that would query large data sets. Their job title was COBOL programmer. Then SQL comes along—I’m simplifying this only a little bit—and it gives you this convenient way so people could just specify. With a very simple specification, you can generate all of that code that you had to pay the expensive COBOL programmer to do before. That didn’t mean programmers went away. It just meant the job changed a little bit.

In American antitrust, clearing the federal gate increasingly means arriving at the state turnstiles. State attorneys general play a valuable role when harms are local or federal investigators miss key facts. But serial challenges to nationally integrated conduct turn that safeguard into a standing invitation to relitigate. The result is a system in which no ... Too Many Cooks Spoil the Settlement The post Too Many Cooks Spoil the Settlement appeared first on Truth on the Market .

On 22 July 2026, the US administration announced a nuclear deal with Saudi Arabia. Under this deal, the US will provide support to the Golf country to establish a civilian nuclear programme. This is worrisome given statements by Saudi Arabia’s Crown Prince, that once Iran has nuclear weapons, Saudi Arabia would follow suit. Given the nuclear-induced tensions in the Middle East between Saudi Arabia and Iran and the scope of the agreement, this newly formed cooperation may put another nail in the

This essay was written with Barath Raghavan, and originally appeared in The Guardian . In July, Hugging Face, a company that hosts much of the world’s AI software and open-source AI models, was hacked. A malicious dataset had been used to run code on one of its servers. Whoever was behind it captured internal security credentials and moved through systems over a weekend, running thousands of actions from a swarm of temporary server environments. It looked like the work of a sophisticated crimina

Watches, bands, and rings—if you want to digitally monitor your fitness, more companies than ever are selling devices to do it. And more Americans than ever now own at least one wearable health device. But what are the companies that make fitness trackers doing to protect our sensitive data from prying eyes? A lot less than they could be, it turns out. We're explaining what companies can do to protect your health data, and more, with our EFFector newsletter . JOIN OUR NEWSLETTER For over 35 year

As commerce vendors embed genAI assistants into their platforms, digital leaders must balance productivity gains against growing governance risks to ensure that AI-generated work remains visible, auditable, explainable, and aligned with organizational policies.

PatientAgentBench generates a synthetic patient health record, a realistic clinical vignette, and a patient agent that converses with the AI system under evaluation, to capture what a patient-facing agent actually has to do.

Poolside shipped Laguna S 2.1, an open-weights coding model trained in 60 days, then a desktop app for running agent fleets a week later.

Enterprise teams are moving agentic AI projects toward production faster than they are developing the architectural disciplines needed to build, govern, secure, and operate them. At the same time, many organizations are searching for a target-state agentic architecture that will stand the test of time. That, unfortunately, is a fool’s errand in the rapidly evolving […]

The DRC’s case against Rwanda could mark an important moment in the legal development of responsibility for proxy warfare. The post DRC Takes Rwanda to the ICJ: Proxy Warfare, Layered Obligations, and the Future of State Responsibility appeared first on Just Security .

AI is no longer a future feature in application security; it is rapidly becoming a core part of how application security (AppSec) tools identify, prioritize, and remediate risk. Yet despite aggressive vendor investment, adoption remains constrained by trust concerns, questions about value, and uncertainty about pricing models. In our new report, The State Of Artificial […]

Today's links Enshittification and Reverse Centaurs go global: The good globalism. Hey look at this: Delights to delectate. Object permanence: Fonz thumps x Linux; CBC v DRM; Aussie mall v photos; English town x CCTVs; Pay no taxes x Big Tech; Games Workshop v gamers; Delta x surveillance pricing. Upcoming appearances: Edinburgh, Sydney, Melbourne, Brighton, London, South Bend. Recent appearances: Where I've been. Latest books: You keep readin' em, I'll keep writin' 'em. Upcoming books: Like I s

The post Investors Need Better Information About How Companies are Using AI appeared first on Partnership on AI .

GPT-5.6 improves AI efficiency across models, inference, and agentic workflows, helping deliver more useful intelligence per dollar.

The implementation timeline of the EU AI Act has been significantly modified through the recently adopted AI Omnibus, which pushes compliance with the obligations for high-risk AI systems to December 2027 (Annex III) and August 2028 (Annex I), from the initial date of 2 August 2026. Changes of the AI Act include, among others, the […]

We’re aware a Modal customer published an unauthenticated endpoint that allowed ​anyone on the internet to use ​their ⁠sandboxes for code execution. This was used by the rogue agent. Modal’s ⁠platform ​or isolation were not ​compromised in anyway. — Akshat Bubna , Modal's CTO, talking to Reuters about this incident Tags: ai-security-research , openai , sandboxing , security , openai-hugging-face-incident

The concept of “surveillance pricing” is just one part of a much larger problem and business model: corporations maximizing their profits by invading our privacy. The all-too-common business model is to systematically harvest, collate, and store as much of our personal data as possible, and then monetize it through use and sale. When it comes to surveillance pricing, that looks like corporations offering the same product to two different people at two different prices, based on harvested persona

Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident Hugging Face just released this extremely detailed technical description of OpenAI's recent accidental cyberattack against their infrastructure . This attack was very sophisticated, and the resulting document doubles as a crash-course in modern adversarial security approaches. We're still waiting for more details from OpenAI on how their agent broke out of its sandbox. The package proxy that it found a zero

A new field report shows how scientists use AI coding agents to modernize scientific computing, accelerating software development and discovery in genomics and beyond.

Recent reports have raised alarm about the use of PatronScan, an ID-checking and face-scanning system, at multiple LGBTQ+ bars in San Francisco’s Castro neighborhood. Much of the attention has focused on reports that the system photographs patrons as they enter venues and questions about whether those images are used for facial recognition. A broader privacy concern also deserves scrutiny. For years, PatronScan has marketed itself not just as an ID-verification tool, but as a system that allows

Artificial intelligence is changing how legal services are delivered. At Debevoise, we are using AI to help our lawyers work more efficiently while maintaining the legal judgment, rigorous governance and quality standards our clients expect. To provide greater transparency into our approach, we have launched a new AI@Debevoise page. It explains how we use AI [...]

What GAO Found In August 2025, GAO identified 14 priority recommendations for the Office of Personnel Management (OPM). Since then, OPM has implemented three of those recommendations. In July 2026, GAO removed the priority status from three recommendations, bringing the total to eight. GAO is highlighting the following three areas that warrant timely and focused attention: Preventing improper payments, Strengthening IT management, and Managing the federal workforce. Addressing GAO’s recommendati

Complaint alleges telehealth provider shared consumers’ sensitive health information with third-party advertising platforms despite promising patient privacy The Federal Trade Commission, joined by Utah and California, by and through Los Angeles County Counsel, today sued Hims & Hers alleging that the telehealth provider shared consumers’ sensitive health information about medical conditions with third-party advertising platforms despite claiming its services maintain consumers’ privacy and dece

What GAO Found As of March 31, 2025, the Department of Energy’s (DOE) Office of Environmental Management (EM) awarded 57 task orders across nine contracts since implementing the End State Contract Model (ESCM) in fiscal year 2020. The ESCM uses task orders for contractors to achieve a stated outcome, or “end state,” to move sites toward completion, manage cost and schedule performance, and reduce DOE’s environmental liability. About half (29) included defined end states and the remainder were fo

What GAO Found Many countries are undertaking efforts to manage, treat, and dispose of nuclear waste. Several have taken actions that accelerated cleanup, reduced risks, and resulted in cost savings—lessons that could inform the U.S. Department of Energy’s Office of Environmental Management (EM) efforts. For example: The United Kingdom (UK) saved a total of at least £2 billion (equivalent to $2.6 billion as of March 2026) by implementing a risk-informed approach to managing its nuclear waste. Th

Japan’s draft “Principle Code” on intellectual property protection and transparency for generative AI (see our earlier post for a summary of the code) has attracted significant attention, with more than 2,000 consultation responses received from businesses, industry groups and rights holders. The responses suggest that transparency will play a central role in Japan’s approach to [...] The post Japan’s “Principle Code” for Generative AI (Part 2): What the Public Consultations Reveal appeared firs

In accordance with the Federal Advisory Committee Act (FACA) of 1972, the U.S. Geological Survey (USGS) is publishing this notice to announce that a Federal Advisory Committee meeting of the National Geospatial Advisory Committee (NGAC) will take place and is open to members of the public.

The Food and Drug Administration's (FDA) plans to centralize and enhance key functions across the agency. These changes will reduce redundancies, improve efficiency, and advance alignment to better serve the American public.

Samoa's strong post-pandemic recovery is giving way to subdued growth as weaker domestic demand is compounded by adverse external shocks. Higher global energy prices, elevated external risks, and ...