Transparency

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

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:2607.26068v1 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

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 .

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 [...]

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

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

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.

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

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

Nasscom has urged the Supreme Court to define high-risk AI use and clarify that technical audits should not automatically require source code disclosure. The post What Nasscom wants changed in the Supreme Court’s draft AI rules appeared first on MEDIANAMA .

The young are searching for a new political grammar rooted in democracy and accountability.

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

Rules aimed only at downstream applications can make AI products less safe. Policymakers should hold both model makers and the companies building on them accountable.

Mit dieser neuen Regel will die EU für mehr Transparenz im Netz sorgen. Bilder, Videos und Texte, die mithilfe von KI erstellt wurden, müssen nun gekennzeichnet werden. Das ist ab Sonntag Pflicht, mit zwei wichtigen Ausnahmen.

Lernen in einer Übungsumgebung: Sicherheitsrisiken in der Windows-Active-Directory-Infrastruktur erkennen und beheben, um die IT vor Cyberangriffen zu schützen.

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

This week’s Future of TV Briefing looks at Comcast-owned FreeWheel enabling streaming ad sellers to directly pass show-level reporting to programmatic ad buyers.

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: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

In a new disclosure, OpenAI says its agent used exposed logins to gain access to at least four “publicly available services” in its unhinged quest to solve a test.

Hollanek and Nowaczyk-Basińska (2024) analyse the harms of AI-enabled re-creation services and offer four recommendations to providers. I accept their diagnosis but argue that their prescription shares a premise with the industry it seeks to reform: that a responsible provider remains present to carry it out. All four recommendations (retirement procedures, meaningful transparency, adult-only access, and mutual consent) are addressed to a continuing operator. Yet the paper’s own opening example,

The rise of virtual worlds, collectively known as the Metaverse, compels a re-examination of longstanding debates concerning personal freedom, moral responsibility, and legal accountability. These immersive digital environments differ from prior communication technologies not merely in degree but in the phenomenological quality they produce: a pervasive sense of presence that blurs the boundary between the virtual and the physical. This article examines the ethical and legal challenges that aris

The release of the Chinese AI model Kimi K3 was a flashpoint in the AI world, sharpening the debate over whether the most capable models should be closely held by individual companies, usually U.S. tech firms, or freely and transparently distributed in the tradition of open-source software. Not only did the high-performing Kimi K3 challenge the cherished Silicon Valley notion that Western AI labs still lead their Chinese counterparts in large language models (though likely by only a hair), but i

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 privacy (transparency) of the smart contracts managed by

Buoyed by the shift of sports programming to streaming, ad spend on digital video continues to climb, but that growth comes with greater scrutiny around transparency and business outcomes. Case in point: A major beverage company is conducting an independent audit of its digital media ads — including CTV and online video — that ran […]

Clinical diagnostic evaluation should not only assess whether models can provide correct diagnoses, but also reflect the realities of clinical practice, including progressive disclosure of multimodal information, dynamic updating of diagnostic hypotheses, and continuous refinement of clinical reasoning. However, existing evaluations of multimodal large language models (MLLMs) typically rely on single-turn or isolated tasks, making it difficult to fully capture the complexity of real-world clinic

Over the past decade, decision trees have been used to represent controllers (a.k.a. policies) in an explainable way, with dtControl2 as a current state-of-the-art tool. However, for systems that are large or have many corner cases, even such representations tend to be too complex and not human-comprehensible. Unfortunately, reducing the size of the decision tree is not straightforward, as missing just a single crucial case might result in an incorrect controller. We tackle this issue in the set

An independent review found the department was deficient in seven areas. The agency said many of the recommended actions are already underway. The post VA fails watchdog FISMA audit on IT security, but agency disagrees appeared first on FedScoop .

To alert the audit community to changes in professional standards, we periodically issue Professional Standards Updates (PSU). These updates highlight the effective dates of recently issued standards and guidance related to engagements conducted in accordance with Government Auditing Standards. PSUs contain summary information only, and those affected by a change should refer to the respective standard or guidance for details.

Large language models (LLMs) increasingly support biomedical research, yet their behavior under adversarial requests for dual-use knowledge remains insufficiently characterized. We introduce BioDisclose, a benchmark for measuring biomedical knowledge disclosure under adversarial elicitation. BioDisclose contains 480 prompts derived from 24 expert-authored scenarios across six biomedical risk domains and four elicitation families spanning academic, historical, role-playing, and decomposed prompti

As the Trump administration pursues an aggressive deregulatory agenda, concerns are mounting that artificial intelligence could make agency decisions harder to explain and defend.

F(AI)2R is FAIR research with AI in the loop, twice: an AI-assisted authoring pass and a machine-readable audit pass over every artefact. AI systems now draft, refactor, and verify research artefacts, yet their contributions are rarely recorded in a form a later human or machine can audit. Building on the original F(AI)2R experiment, we generalize its provenance model beyond scholarly writing into aiprov, a PROV-O extension covering any AI-in-the-loop artefact, and we package the method as an ex

Multi-agent frameworks built on large language models (LLMs) routinely entangle three logically distinct concerns: who is on the team (organization), how members align (coordination), and which algorithm fuses their work (collaboration protocol). IMACS (Intelligent Multi-Agent Collaboration System) separates the three into orthogonal, independently swappable layers. Classic organizational theory (Belbin roles, Mintzberg coordination, RACI accountability) becomes executable, validated configurati

Der KI-Cyberangriff von OpenAI hat Folgen: Der Hugging-Face-CEO fordert nun radikale Transparenz sowie eine Investition in die Absicherung seiner Plattform. ( KI , Cyberwar )

Eliciting explainable AI (XAI) requirements from stroke survivors presents a methodological challenge with direct implications for the design of trustworthy brain-computer interfaces for rehabilitation. How can patients and caregivers articulate preferences about algorithmic transparency when they lack conceptual frameworks for explainability, and when standard elicitation approaches are structurally inadequate for users with acquired communication disorders? We present a video-based scaffolding

arXiv:2607.22606v1 Announce Type: new Abstract: Health systems are rapidly deploying generative AI assistants that answer patient questions from institution-authored education materials, on the premise that grounding in local content yields consistent guidance. Whether it does depends on a question not previously measured at scale: do the underlying documents themselves agree? We use a structured-output large language model judge to audit 5,730,465 pairwise comparisons across 102 patient-educati

arXiv:2607.23207v1 Announce Type: new Abstract: The emerging infrastructure for AI-agent identity has converged, in industry practice and research proposals alike, on a single resolution of the tension between accountability and privacy: make every agent identifiable. We document a national system in China -- built as national infrastructure and scheduled for public launch in Q3 2026 -- that occupies a different and underexplored point in the same design space: an agent is associated with a veri

arXiv:2607.23519v1 Announce Type: new Abstract: Political audits of large language models (LLMs) usually reduce each to one point on a political compass. But that resting point barely matters in deployment: a model must land somewhere, and what counts is how far, and in which directions, its answers can be steered. That steering runs through the system prompt: the personalization layer a platform sets, or one induced from a user's history, not necessarily written by hand. We run a dispersion-fir

arXiv:2607.24035v1 Announce Type: new Abstract: Explainable AI (XAI) is used to assess whether artificial intelligence models rely on meaningful patterns, yet explanations that appear plausible for individual predictions may systematically misrepresent model behavior. This is particularly problematic in medicine, where models may rely on irrelevant signal characteristics rather than disease-specific patterns without being recognizable. We address this challenge using electrocardiogram (ECG) data