Transparency

How Salesforce sees the HAIP Reporting Framework reducing AI governance fragmentation and making transparency a competitive advantage. The post HAIP is transforming transparency from a compliance burden to a competitive advantage appeared first on OECD.AI .

The social media platform rolls out new AI transparency tools and education initiatives for South African users.

Commission accepts X’s action plan to comply with Digital Services Act Anonymous (not verified) Thu, 07/16/2026 - 11:18 The European Commission has accepted X’s action plan to comply with transparency obligations and researchers’ access to data, under the Digital Services Act. The approved measures represent an important step in enabling researchers, civil society and the public in general to gain more transparency into X’s systems, in particular to monitor X’s systemic risks and to assess the p

As AI agents become more autonomous, strong identity, access, and auditing controls are critical to keeping them secure.

Australia's latest AI governance initiatives, heightened privacy enforcement and increasing regulatory cooperation signal a future in which AI, privacy, cybersecurity and digital accountability are ...

As conversational AI systems are designed for repeated use, a central question is how a series of interactions becomes a relationship. We present a longitudinal multimodal study of a memory-augmented conversational agent (24 participants x 10 sessions), in which participants rated five relational constructs -- familiarity, self-disclosure, perceived memory, conversational quality, and enjoyment -- after each session. Two complementary dynamics emerge. First, conversational quality strongly shape

arXiv:2607.13040v1 Announce Type: new Abstract: This paper examines where final authority should sit once capable AI systems are embedded in organizational workflows. It compares two governance models. The first, frontier-provider sovereignty, assigns privileged authority to the provider of the most capable models and is reflected in contemporary arguments for frontier-model testing, release gating, transparency duties, and compute-related controls. The second, action-centered deployer sovereign

arXiv:2605.16281v2 Announce Type: replace Abstract: Post-deployment accountability has become central to AI governance, yet little empirical evidence shows whether monitoring, incident reporting, and impact assessment obligations are visible when AI systems fail. This study analyzes real-world AI incidents from the AI Incident Database (2020--2026) and codes them against nine post-deployment provisions from the EU AI Act, the NIST AI Risk Management Framework, and the GDPR. The findings show sub

arXiv:2606.02528v2 Announce Type: replace-cross Abstract: Large language models now power robo-advisors and trading agents, yet whether they carry built-in biases toward specific assets is largely untested. We ask three questions: do LLMs systematically prefer certain financial instruments; can an internal representation with causal leverage over those preferences be identified; and does that representation affect downstream financial decisions? We develop a three-level audit protocol and apply

The increasing insecurity of traditional methods such as passwords and PINs has raised significant interest in behavioral biometrics. Keystroke Dynamics (KSD), which relies on the unique manner in which an individual types, is a promising candidate for continuous and unobtrusive authentication. This study presents a hybrid model for KSD that combines a Long Short-Term Memory (LSTM) network with an ensemble of Random Forest, XGBoost, and Multilayer Perceptron classifiers using a soft-voting strat

BackgroundStandard Retrieval-Augmented Generation (RAG) systems only use semantic similarity to retrieve information, and since this method is quite limiting, it may find clinically irrelevant evidence and produce outputs that are unsafe or hallucinated. This drawback is particularly important in respiratory care, where the diagnosis relies heavily on very accurate physiological indicators such as spirometry patterns and symptom profiles.MethodsWe propose MMCRAG-Resp., a clinically grounded, phy

Suspends next ⁠phase of cyber security certification program.

Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.

Background: Summary of findings (SoF) tables are widely used in systematic reviews and clinical practice guidelines to present evidence about health care interventions in a concise and transparent format. Although developed to improve accessibility and interpretation of evidence, previous studies have shown that users often experience difficulties understanding statistical information, certainty ratings, and the relationships between outcomes and treatment effects. Limited research has explored

Oura Rings, Garmin GPS fitness watches, Apple Watches, Whoop bands—every year, more and more tech devices are promising to monitor our health and fitness, guide us toward healthier living, and provide useful health metrics to take to our doctors. But few of these tools provide the sorts of privacy and security promises we demand from all technology, let alone tech that captures personal health data. It’s time they step up and start providing transparency reports and stronger encryption options.

The rapid development of Large Language Models (LLMs) and Artificial Intelligent (AI) powered autonomous agents has fundamentally changed the existing forms of software governance. In spite of the rigorous standards of transparency and account ability required according to the international frameworks such as the European Union's AI Act, there is a considerable gap between theory and reality. The present study discusses the inherent drawbacks of currently utilized platforms for LLM evaluation, m

Background: Large language models (LLMs) are increasingly embedded in conversational agents for cardiometabolic care. These systems could support self-management, but their behavior change content, delivery mechanisms, and implementation transparency are poorly understood. Objective: This scoping review mapped behavior change techniques (BCTs) used in LLM-driven conversational agents for cardiometabolic prevention and management, described how these techniques are delivered across static, rule-b

Elon Musk, the billionaire owner of X, wants to make the social network one of the most transparent major technology The post Elon Musk: “We will make the entire codebase of X open source, with no exceptions.” appeared first on The New Stack .

Elon Musk a promis, sur X, de publier l'intégralité du code source de la plateforme une fois une revue de sécurité achevée. Mais sa précédente promesse de transparence, plus limitée, montre déjà les limites de l'exercice.

Whistleblowers are a key safeguard against organizational wrongdoing, but the threat of retaliation deters reporting. Existing whistleblower-protection proposals lack formal privacy guarantees, and existing differential privacy mechanisms do not directly target the natural threat model -- one in which the audited organization itself observes auditor selection decisions and uses them to identify reporters. We formalize protection against a strong-adversary threat model as per-report $(0, δ)$-diff

The bill requires full price transparency, forces anyone advertising 50 or more tickets a year for resale to register with the District. Source

Attorney General nominee Todd Blanche's prosecutions of Comey and others reveal a pattern of prosecutorial sycophancy — charges brought to please Trump. The post To Audition for the Role of Attorney General, Blanche Is Prosecuting to Please appeared first on Just Security .

Background and Objective: Deep video models estimate left-ventricular ejection fraction (EF) from echocardiography with near-expert accuracy, and post-hoc attribution (Chefer relevance for transformers, Grad-CAM for CNNs) is increasingly used to certify that models "look at the right place." Yet whether these explanations are faithful both spatially and temporally is unaudited. Because EF is defined by the end-systolic (ES) and end-diastolic (ED) frames, a faithful explanation must localize the

Explainable Reinforcement Learning (XRL) seeks to make Reinforcement Learning (RL) policies more transparent and interpretable, a key requirement in safety-critical and human-centric scenarios. However, it is mostly based on user studies, thus targeting the needs of a specific audience and lacking shared evaluation metrics. On the other hand, logic-based approaches within eXplainable Artificial Intelligence (XAI) provide compact, human-readable abstractions of decision-making. However, the syste

The West African country advanced rules to force organizations to disclose cyberattacks, joining other nations in a shift to mandated transparency.

Digital video ad spend continues to climb, but buyers say bigger budgets bring tougher questions about inventory quality, supply chain transparency.

arXiv:2607.11918v1 Announce Type: cross Abstract: Dual submissions, in which identical or substantially similar papers are simultaneously submitted to one or more archival venues, without cross-citation or disclosure, are a growing problem for the AAAI Conference and other scientific publication venues. These submissions increase the burden on the peer-review system and pollute the scientific record. As part of the AAAI-26 review process, we (conference organizers) compared AAAI main-track submi

Coherent decision-making and internal accountability are critical to meeting this manic moment Anthony Albanese promises fast-track approvals for datacentres to shore up AI investment The University of Sydney was the natural setting for Anthony Albanese to lay out his vision for how Australia should confront the profound economic and social challenges posed by so-called artificial intelligence technology. His time around the jacaranda and sandstone in the early 80s was a seminal marker in the fu

Graph-based learning and explainable artificial intelligence (XAI) are increasingly used to improve both predictive performance and transparency in financial risk modelling. This paper presents a systematic literature review of AI and machine learning approaches for credit risk assessment and fraud detection, with specific attention to graph-based methods and explainable frameworks. Following a PRISMA-guided methodology, 149 studies published between 2015 and 2025 were analysed across multiple a

Turns out accountability was always something for other people. The post Amy Coney Barrett Then: ‘Read The Opinion!’ ACB Now: Inappropriate To Expect Supreme Court To Explain Decisions appeared first on Above the Law .

Patients with no other options are watching an agency turn on its own scientists — and the trust that took a century to build is draining out in two years.

Large language model (LLM) agents increasingly automate multi-step engineering and informatics workflows, yet they rarely ask how much effort a task actually requires. They often follow a maximum-context-first strategy--re-reading files and dependencies they have already seen--turning a one-line edit into a small code-base audit. We argue the missing capability is task-aware execution-scope estimation: judging a task's difficulty, the information it truly needs, and the shortest reliable path be

The persuasive power of data visualizations can go awry: for instance, in an explainable AI (XAI) context, visualizations can produce over-trust of predictive models. In this paper, we use a crowdsourced study to show that providing accurate (but superfluous or irrelevant) data in a model explanation can, in fact, result in unjustified trust and other positive beliefs about a model, even when the model is patently discriminatory and unfair. Our results suggest that XAI designers and developers n

Recommender-system research for Vietnamese remains limited by the absence of a public, well-documented hotel interaction resource. Building such a resource is challenging for three reasons: cross-platform hotel names must be reconciled before interactions are comparable; quality must be audited with reproducible metrics rather than ad hoc cleaning; and public release must preserve privacy while remaining benchmarkable under realistic cold-start conditions. We introduce ViHoRec, a quality-control

Publication date: June 2026 Source: Government Information Quarterly, Volume 43, Issue 2 Author(s): Shangrui Wang, Yuanmeng Zhang, Zhenming Huang, Zheng Liang

Publication date: June 2026 Source: Government Information Quarterly, Volume 43, Issue 2 Author(s): Shangrui Wang, Yuanmeng Zhang, Yiming Xiao, Zheng Liang

Publication date: June 2026 Source: Government Information Quarterly, Volume 43, Issue 2 Author(s): Jamil Civitarese, Gregory Michener, Octavio Amorim Neto

Publication date: June 2026 Source: Government Information Quarterly, Volume 43, Issue 2 Author(s): Hung-Yi Hsu