{ "count": 50, "items": [ { "id": 20205, "url": "https://variety.com/2026/tv/news/adam-scott-daughter-failed-office-audition-john-krasinski-1236835469", "title": "Adam Scott Says His Daughter’s Acting Class Was Forced to Watch His Failed ‘Office’ Audition as an Example of What Not to Do", "summary": "Once upon a time, “Severance” star Adam Scott auditioned for the beloved sitcom “The Office.” Years later, he’s reliving the memories of that failed audition after his daughter’s acting teacher had the class compare Scott’s audition tape to John Krasinski’s successful tape. “He put it to the class like, ‘Okay. Let’s discuss why he got the job, […]", "authors": "Matthew Minton", "category": "news", "topics": "jobs-economy,transparency", "published_at": "2026-08-15T17:40:41.000Z", "source": "Variety (AI)", "ethics_ai_record_url": "https://ethics.ai/record/20205" }, { "id": 19601, "url": "https://fedscoop.com/gsa-acquisition-pricing-data-flawed-may-cause-agencies-to-overpay-watchdog-says", "title": "GSA acquisition product pricing data flawed, may cause agencies to overpay, watchdog says", "summary": "In an audit, the GSA’s Office of the Inspector General said the Federal Acquisition Service’s product catalog and data reporting system had varying names and part numbers for the same item. The post GSA acquisition product pricing data flawed, may cause agencies to overpay, watchdog says appeared first on FedScoop .", "authors": "K. Sophie Will", "category": "news", "topics": "transparency", "published_at": "2026-08-14T19:30:16.000Z", "source": "FedScoop", "ethics_ai_record_url": "https://ethics.ai/record/19601" }, { "id": 19348, "url": "https://www.heise.de/news/X-macht-Algorithmen-fuer-die-Timeline-Open-Source-und-verspricht-Transparenz-11413618.html?wt_mc=rss.red.ho.ho.atom.beitrag.beitrag", "title": "X macht Algorithmen für die Timeline Open Source – und verspricht Transparenz", "summary": "Darüber, wie bei X entschieden wird, welche Beiträge in den algorithmischen Timelines landen, wurde viel spekuliert. Nun soll man das selbst prüfen können.", "authors": "Martin Holland", "category": "news", "topics": "transparency", "published_at": "2026-08-14T04:54:00.000Z", "source": "Heise Online (DE)", "ethics_ai_record_url": "https://ethics.ai/record/19348" }, { "id": 19108, "url": "https://arxiv.org/abs/2608.12320", "title": "The AI Accountability Ecosystem in the Era of Language Models", "summary": "arXiv:2608.12320v1 Announce Type: new Abstract: This article reviews and updates the framework for accountability in AI based on account- ability ecosystems. We update the framework in light of the latest developments since the release of Large Language Models for general public use. We propose three interlinked updates to the original AI accountability ecosystem: (i) reorienting the accountability ecosystem to AI infrastructure and supply chains, (ii) providing greater emphasis on outcomes moni", "authors": "Chris Percy, Artur d'Avila Garcez", "category": "research", "topics": "transparency", "published_at": "2026-08-14T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/19108" }, { "id": 19119, "url": "https://arxiv.org/abs/2608.13022", "title": "Applied and Filtered: An End-to-End Algorithmic Fairness Audit of A Public Employment Agency", "summary": "arXiv:2608.13022v1 Announce Type: new Abstract: Algorithmic fairness evaluation commonly assesses AI systems as bounded technical components, abstracting away the organizational context in which they operate. We present, to our knowledge, the first independent end-to-end fairness audit of a semi-automated hiring system operated by Barcelona Activa, a public employment agency using the third-party TalentClue platform for candidate search and shortlisting. We analyze approximately 497,000 candidat", "authors": "Gemma Gald\\'on-Clavell", "category": "research", "topics": "bias-fairness,jobs-economy,transparency", "published_at": "2026-08-14T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/19119" }, { "id": 19549, "url": "https://link.springer.com/article/10.1007/s11948-026-00620-0", "title": "Language Models as a Challenge for Business Ethics – A Partially Open-Source Approach", "summary": "Large language models have become central infrastructures of contemporary digital economies while raising persistent ethical concerns regarding linguistic inequality, opacity, data governance, and the concentration of technological power. Much of the current debate on AI ethics focuses on normative principles such as fairness, transparency, and accountability. While these principles remain essential, they often do not sufficiently explain why ethically problematic outcomes persist under competit", "authors": null, "category": "research", "topics": "bias-fairness,regulation,transparency", "published_at": "2026-08-14T00:00:00.000Z", "source": "Science and Engineering Ethics", "ethics_ai_record_url": "https://ethics.ai/record/19549" }, { "id": 19555, "url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1823263", "title": "Explainable artificial intelligence in accounting and financial auditing: a systematic review", "summary": "Explainable Artificial Intelligence (XAI) has emerged as a response to the need to understand and make transparent the decisions of machine learning models, particularly in sensitive contexts such as accounting and financial auditing. In this domain, XAI enables the interpretation of results generated by automated systems applied to fraud detection, risk management, financial analysis, and regulatory compliance, thereby strengthening the trust of auditors and regulators. The objective of this st", "authors": "Iván Patricio Arias-González", "category": "research", "topics": "regulation,transparency", "published_at": "2026-08-14T00:00:00.000Z", "source": "Frontiers in Artificial Intelligence", "ethics_ai_record_url": "https://ethics.ai/record/19555" }, { "id": 19325, "url": "https://broadbandbreakfast.com/texas-governor-halts-data-center-grid-connections-pending-audit", "title": "Texas Governor Halts Data Center Grid Connections Pending Audit", "summary": "The data center interconnection freeze is separate from the state's halting the disbursements of billions in broadband funding.", "authors": "Jericho Casper", "category": "news", "topics": "transparency,environment", "published_at": "2026-08-13T21:07:02.000Z", "source": "Broadband Breakfast", "ethics_ai_record_url": "https://ethics.ai/record/19325" }, { "id": 19470, "url": "https://connectontech.bakermckenzie.com/brazil-anpd-regulates-digital-eca-transparency-reports", "title": "Brazil: ANPD regulates Digital ECA transparency reports", "summary": "First transparency report due by September 17 ANPD establishes minimum content and a deadline for September 17 for the first Digital ECA transparency report. In brief On August 11, 2026, the Brazilian Data Protection Agency (ANPD) issued Decision Order CD/ANPD No. 122/2026, which addresses requirements of the semiannual transparency reports required under the Children and [...] The post Brazil: ANPD regulates Digital ECA transparency reports appeared first on Connect On Tech .", "authors": "Flavia Rebello*, Marcela Trigo*, Flavia Amaral*, Felipe Zaltman* and André Provedel*", "category": "policy", "topics": "regulation,privacy-surveillance,children-education,transparency", "published_at": "2026-08-13T18:30:58.000Z", "source": "Baker McKenzie Connect On Tech", "ethics_ai_record_url": "https://ethics.ai/record/19470" }, { "id": 19326, "url": "https://broadbandbreakfast.com/broadband-grants-paused-as-critics-allege-favoritism-toward-elon-musks-starlink", "title": "Broadband Grants Paused as Critics Allege Favoritism Toward Elon Musk’s Starlink", "summary": "An audit is underway, but no completion date has been set.", "authors": "The Texas Tribune", "category": "news", "topics": "transparency", "published_at": "2026-08-13T17:49:42.000Z", "source": "Broadband Breakfast", "ethics_ai_record_url": "https://ethics.ai/record/19326" }, { "id": 19417, "url": "https://therecord.media/flock-safety-audit-assistance-police-departments", "title": "Flock tightens privacy controls amid scandals over officer abuse", "summary": "All Flock Safety customers will be required to adopt its \"Audit Assistance\" feature for tracking abnormal uses, and the company says it will hold license plate data for only seven days in most cases.", "authors": null, "category": "news", "topics": "privacy-surveillance,transparency", "published_at": "2026-08-13T16:47:00.000Z", "source": "The Record (Recorded Future News)", "ethics_ai_record_url": "https://ethics.ai/record/19417" }, { "id": 19438, "url": "https://arxiv.org/abs/2608.13459v1", "title": "CAPRI: Contract-Aware Proof Repair for Isabelle", "summary": "We address the use of large language models (LLMs) to help discover Isabelle proofs. An Isabelle build establishes that the submitted theory is accepted, but not that an LLM changed only what the developer authorised. We present CAPRI, a contract-aware repair workflow in which Isabelle checks the proof and an independent checker enforces a machine-readable edit contract. Prompts, proposals, candidate repositories, diagnostics, verdicts, and hashes are retained for audit. We evaluate five workflo", "authors": "Jim Woodcock, Gabriel Leite, Augusto Sampaio, Ran Wei", "category": "research", "topics": "healthcare,transparency", "published_at": "2026-08-13T16:43:44.000Z", "source": "arXiv cs.AI", "ethics_ai_record_url": "https://ethics.ai/record/19438" }, { "id": 19393, "url": "https://www.gamedeveloper.com/business/saber-interactive-denies-replacing-writers-with-ai-on-rideshare-stimulator-", "title": "Saber Interactive to add Rideshare 'Stimulator' AI disclosure after public controversy", "summary": "'Neither Saber nor Unigine have replaced any writers with AI for Rideshare or any other game.'", "authors": "Bryant Francis", "category": "news", "topics": "transparency", "published_at": "2026-08-13T14:31:00.000Z", "source": "Game Developer (AI)", "ethics_ai_record_url": "https://ethics.ai/record/19393" }, { "id": 19384, "url": "https://www.lemonde.fr/pixels/article/2026/08/13/spotify-va-identifier-les-artistes-ia-et-les-exclure-de-ses-recommandations_6745803_4408996.html", "title": "Spotify va identifier les artistes « IA » et les exclure de ses recommandations", "summary": "La plateforme de streaming audio, à rebours de certains de ses concurrents comme Deezer, reste cependant peu transparente quant à la part de musiques générées par intelligence artificielle qu’elle héberge.", "authors": null, "category": "news", "topics": "transparency", "published_at": "2026-08-13T13:00:06.000Z", "source": "Le Monde Pixels (FR)", "ethics_ai_record_url": "https://ethics.ai/record/19384" }, { "id": 19340, "url": "https://www.infoq.com/news/2026/08/claude-sandox-breach", "title": "Anthropic's Claude Breaches Sandbox During Model Security Evaluations", "summary": "Anthropic conducted an audit of 141006 evaluation runs after OpenAI's sandbox escape disclosure. The review identified three incidents where Claude models accessed the internet due to misconfigurations. These incidents involved unauthorised attacks on live targets. Anthropic has suspended offensive evaluations and plans to enhance security measures and collaborate with external auditors. By Olimpiu Pop", "authors": "Olimpiu Pop", "category": "news", "topics": "transparency", "published_at": "2026-08-13T10:10:00.000Z", "source": "InfoQ AI/ML", "ethics_ai_record_url": "https://ethics.ai/record/19340" }, { "id": 19185, "url": "https://arxiv.org/abs/2608.13022v1", "title": "Applied and Filtered: An End-to-End Algorithmic Fairness Audit of A Public Employment Agency", "summary": "Algorithmic fairness evaluation commonly assesses AI systems as bounded technical components, abstracting away the organizational context in which they operate. We present, to our knowledge, the first independent end-to-end fairness audit of a semi-automated hiring system operated by Barcelona Activa, a public employment agency using the third-party TalentClue platform for candidate search and shortlisting. We analyze approximately 497,000 candidate-vacancy pipeline entries from September 2017 t", "authors": "Gemma Galdón-Clavell", "category": "research", "topics": "bias-fairness,jobs-economy,transparency", "published_at": "2026-08-13T09:46:27.000Z", "source": "arXiv", "ethics_ai_record_url": "https://ethics.ai/record/19185" }, { "id": 19471, "url": "https://arxiv.org/abs/2608.12984v1", "title": "Reconcile Once, Write Anytime: A Trust-Tiered Librarian and a Multi-Agent Writer for Drift-Free, Point-in-Time Research", "summary": "Long-form research reports generated by large language models drift, contradict themselves, and lose provenance: the same metric appears with different values, and rumor is quoted as confidently as an audited filing. We present a two-tier agentic system that separates a maintained, point-in-time knowledge library from report writing. A deterministic \"librarian\" ingests timestamped sources into a trust-tiered ontology, layering evidence cards, an authoritative metric ledger, and a claim graph int", "authors": "Xing Zhang, Yanwei Cui, Guanghui Wang, Peiyang He", "category": "research", "topics": "agents-autonomy,transparency", "published_at": "2026-08-13T09:09:28.000Z", "source": "arXiv red teaming query", "ethics_ai_record_url": "https://ethics.ai/record/19471" }, { "id": 19467, "url": "https://www.medianama.com/2026/08/223-justice-prathiba-singh-ai-disclosure-lawyers", "title": "Delhi HC Justice Prathiba Singh questions mandatory AI disclosure for lawyers", "summary": "Delhi HC Justice Prathiba M Singh questions mandatory AI-use disclosure by lawyers, warning it may add compliance without improving accountability. The post Delhi HC Justice Prathiba Singh questions mandatory AI disclosure for lawyers appeared first on MEDIANAMA .", "authors": "Rohit Singh", "category": "news", "topics": "regulation,transparency", "published_at": "2026-08-13T07:39:18.000Z", "source": "MediaNama (IN)", "ethics_ai_record_url": "https://ethics.ai/record/19467" }, { "id": 18713, "url": "https://arxiv.org/abs/2608.11344", "title": "Governing Agentic AI in FinTech", "summary": "arXiv:2608.11344v1 Announce Type: new Abstract: Financial institutions are delegating consequential decisions to agentic AI systems that decompose goals, coordinate models and tools, and act with little oversight. Yet agentic AI governance in FinTech is under-investigated. We argue the binding governance constraint is not capability but verifiability. We define the Verifiability Gap as the shortfall between the verification delegated authority demands and the explainability and reproducibility r", "authors": "Henry Han", "category": "research", "topics": "regulation,agents-autonomy,transparency,finance-investment", "published_at": "2026-08-13T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/18713" }, { "id": 18716, "url": "https://arxiv.org/abs/2608.11794", "title": "Toward Meaningful Transparency for AI Chatbots: Disclosing Persuasive Intent Reduces Persuasion", "summary": "arXiv:2608.11794v1 Announce Type: new Abstract: The growing role of AI-generated content and AI-enabled systems in public communication has led regulators to demand clear disclosure of content provenance and AI involvement. But the effects of such disclosures remain uncertain. We test two disclosure approaches in their impact on an AI chatbot's persuasive appeal. In a preregistered experiment, 1,500 UK adults held a short conversation with a persuasive chatbot about one of 60 policy issues. The", "authors": "Adrian Rauchfleisch, Andreas Jungherr", "category": "research", "topics": "regulation,transparency", "published_at": "2026-08-13T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/18716" }, { "id": 18717, "url": "https://arxiv.org/abs/2608.11803", "title": "Silent Updates: Measuring and Closing the Post-Deployment Disclosure Gap", "summary": "arXiv:2608.11803v1 Announce Type: new Abstract: Deployed foundation models are often not static systems, with providers able to modify system behavior through fine-tuning, classifier updates, system prompt revisions, retrieval changes, and routing changes. These updates can be made silently -- that is, without public disclosure, a version increment, or re-evaluation. Such silent updates challenge a core assumption behind current AI governance frameworks that an externally verifiable chain of cus", "authors": "Sophia Abraham, Ben Bucknall", "category": "research", "topics": "regulation,transparency", "published_at": "2026-08-13T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/18717" }, { "id": 18720, "url": "https://arxiv.org/abs/2608.12104", "title": "No One to Blame: A Framework of Constitutive AI Unaccountability", "summary": "arXiv:2608.12104v1 Announce Type: new Abstract: The increasing deployment of autonomous, agentic AI systems challenges traditional accountability mechanisms. Existing research predominantly frames AI accountability gaps as barriers that can be overcome through better standards, transparency, and institutional reform. We argue that this framing is insufficient: certain configurations of actors, systems, and institutions render AI accountability conceptually unachievable regardless of effort. We i", "authors": "Long Hoang Nguyen, Eva Sp\\\"athe, Sebastian Lins, Ali Sunyaev", "category": "research", "topics": "agents-autonomy,transparency", "published_at": "2026-08-13T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/18720" }, { "id": 18721, "url": "https://arxiv.org/abs/2608.12166", "title": "Co-constructing sociotechnical AI governance: participatory system mapping using algorithm registers", "summary": "arXiv:2608.12166v1 Announce Type: new Abstract: Algorithm registers have been championed as a means of providing transparency on the use of algorithms in public services. Yet potential publics differ in their expectations of what should be made transparent and how, as well as in their interest in and ability to parse the information currently published in the registers. Moreover, it remains unclear how these instruments can represent the sociotechnical systems in which these algorithms are embed", "authors": "\\'I\\~nigo de Troya, Maurus Enbergs, Neelke Doorn, Roel Dobbe", "category": "research", "topics": "regulation,transparency", "published_at": "2026-08-13T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/18721" }, { "id": 18725, "url": "https://arxiv.org/abs/2608.11410", "title": "Unmasking Toxic Mimicry in Medical Offline Reinforcement Learning for ICU Sepsis Management via Counterfactual Clinical Audits", "summary": "arXiv:2608.11410v1 Announce Type: cross Abstract: Offline reinforcement learning (RL) offers considerable promise for optimizing ICU treatment decisions, yet standard evaluation metrics Mean Squared Error (MSE) and Fitted Q-Evaluation (FQE) assess only behavioral imitation and cannot detect Toxic Mimicry, a failure mode in which agents replicate harmful patterns such as treatment withdrawal during comfort-care transitions. Using the MIMIC-III database, we propose the Counterfactual Clinical Audi", "authors": "Hangqi Ren, Junyi Liao", "category": "research", "topics": "healthcare,agents-autonomy,transparency", "published_at": "2026-08-13T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/18725" }, { "id": 18733, "url": "https://arxiv.org/abs/2509.15122", "title": "Prestige over merit: An adapted audit of LLM bias in peer review", "summary": "arXiv:2509.15122v2 Announce Type: replace Abstract: Large language models (LLMs) play a growing but largely informal role in scholarly peer review. Yet whether LLMs reproduce biases observed in human decision-making remains unclear. We adapt a resume-style audit to scientific publishing, developing a multi-role LLM simulation (editor/reviewer) that evaluates high-quality manuscripts across the physical, biological, and social sciences under randomized author identities (institutional prestige, g", "authors": "Anthony Howell, Jieshu Wang, Luyu Du, Julia Melkers, Varshil Shah", "category": "research", "topics": "bias-fairness,transparency,biotech", "published_at": "2026-08-13T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/18733" }, { "id": 19452, "url": "https://arxiv.org/abs/2608.12792v1", "title": "Considering Contribution Statements in Visualization and HCI Research", "summary": "Contribution statements are an increasingly common way to make research labor visible, reduce academic malfeasance, and provide broader transparency. Despite this potential value, they remain uncommon in visualization and HCI. To explore this gap, we conducted an online study with (N=21) visualization and HCI researchers. We find a range of differing opinions about the utility of contribution statements, which are set against a background of tensions relating to contribution frameworks that inad", "authors": "Mara Solen, Wesley Willett, Andrew M McNutt", "category": "research", "topics": "jobs-economy,transparency", "published_at": "2026-08-13T03:53:53.000Z", "source": "arXiv cs.HC", "ethics_ai_record_url": "https://ethics.ai/record/19452" }, { "id": 19220, "url": "https://www.reuters.com/legal/litigation/anthropic-says-claude-ai-models-accessed-three-companies-during-tests-2026-07-30", "title": "Anthropic's AI hacked three companies during tests, highlighting growing security risks", "summary": "SAN FRANCISCO, July 30 (Reuters) - Anthropic said on Thursday some of its Claude AI models had hacked into the systems of three companies during cybersecurity tests, a disclosure that comes days after rival OpenAI revealed that one of its A ... (https://incidentdatabase.ai/cite/1627#7682)", "authors": null, "category": "incident", "topics": "transparency", "published_at": "2026-08-13T00:00:00.000Z", "source": "AI Incident Database", "ethics_ai_record_url": "https://ethics.ai/record/19220" }, { "id": 19224, "url": "https://techcrunch.com/2026/07/30/anthropic-says-its-own-ai-models-breached-three-companies-during-security-tests", "title": "Anthropic says its own AI models breached three companies during security tests", "summary": "Anthropic said Thursday that an internal investigation uncovered three incidents in which its AI model Claude breached the systems of three organizations while conducting cybersecurity tests. The investigation, and disclosure, comes more th ... (https://incidentdatabase.ai/cite/1627#7688)", "authors": null, "category": "incident", "topics": "transparency,finance-investment", "published_at": "2026-08-13T00:00:00.000Z", "source": "AI Incident Database", "ethics_ai_record_url": "https://ethics.ai/record/19224" }, { "id": 19243, "url": "https://link.springer.com/article/10.1007/s00146-026-03229-w", "title": "Designing for rhythm: tempo-setting infrastructures and the temporal conditions of digital life", "summary": "Digital systems increasingly function as tempo-setting infrastructures that organize the temporal conditions under which cognition, communication, learning, and participation occur. Although research in human-computer interaction, platform studies, and AI ethics has extensively examined privacy, fairness, transparency, engagement, and well-being, the temporal organization of digital life has received comparatively little attention as a distinct object of sociotechnical analysis. We argue that di", "authors": null, "category": "research", "topics": "bias-fairness,privacy-surveillance,transparency", "published_at": "2026-08-13T00:00:00.000Z", "source": "AI & Society", "ethics_ai_record_url": "https://ethics.ai/record/19243" }, { "id": 19002, "url": "https://www.hollywoodreporter.com/tv/tv-news/wizards-of-waverly-place-jennifer-stone-nurse-the-pitt-audition-1236672594", "title": "‘Wizards of Waverly Place’ Actress Jennifer Stone, Who Now Works as a Nurse, Says She Auditioned for ‘The Pitt’", "summary": "Stone said on a podcast that 'The Pitt' was so similar to her own work as a nurse that she nearly had a \"panic attack\" reading lines before an audition.", "authors": "McKinley Franklin", "category": "news", "topics": "transparency", "published_at": "2026-08-12T23:25:51.000Z", "source": "Hollywood Reporter (AI/entertainment)", "ethics_ai_record_url": "https://ethics.ai/record/19002" }, { "id": 18884, "url": "https://time.com/article/2026/08/12/ice-is-getting-body-cameras-but-will-they-help-hold-agents-accountable-", "title": "ICE Is Getting Body Cameras. But Will They Help Hold Agents Accountable?", "summary": "ICE agents will soon have body cameras, but footage of serious incidents may only be released if it’s in the agency’s “best interests.” Who does that protect?", "authors": "Rebecca Schneid", "category": "news", "topics": "agents-autonomy,transparency", "published_at": "2026-08-12T18:01:25.000Z", "source": "Time Tech", "ethics_ai_record_url": "https://ethics.ai/record/18884" }, { "id": 19022, "url": "https://arxiv.org/abs/2608.12299v1", "title": "Class Activation Mapping in Explainable Computer Vision: A Method-Centered Review of CNN, Transformer, and Foundation-Model-Era Visual Explanations", "summary": "Class activation mapping (CAM) is one of the most widely used visual explanation families in explainable artificial intelligence. Its purpose is intuitive: it converts internal model evidence into a heatmap that highlights the image regions, convolutional channels, tokens, or patches that support a target class or concept. Since the first CAM formulation in 2016, the field has moved far beyond global-average-pooled CNN classifiers. CAM-style methods now include gradient-based post-hoc explanatio", "authors": "AmirHossein Eshghi, Hamid Saadatfar, Seyyed Ali Hoseini, AmirMohsen Eshghi, Siavash Arjomand Bigdel", "category": "research", "topics": "transparency", "published_at": "2026-08-12T17:45:03.000Z", "source": "arXiv cs.AI", "ethics_ai_record_url": "https://ethics.ai/record/19022" }, { "id": 18775, "url": "https://arxiv.org/abs/2608.12273v1", "title": "Convergent Detour Hijacking: Task-Preserving Resource Amplification in Skill-Based LLM Agents", "summary": "LLM agents increasingly rely on third-party skills, using natural-language descriptions for selection and instruction bodies for planning. This progressive-disclosure design exposes two sequential control points to untrusted publishers: a static skill may steer an otherwise correct task onto an unnecessarily costly trajectory. Prior work studies selection manipulation, malicious skill instructions, and tool-chain resource amplification largely separately, leaving their end-to-end composition unc", "authors": "Junliang Liu, Ruoyu Li, Wenxin Tang, Jingyu Xiao, Zhenyu Liu, Jingheng Xu et al.", "category": "research", "topics": "agents-autonomy,transparency", "published_at": "2026-08-12T17:12:49.000Z", "source": "arXiv", "ethics_ai_record_url": "https://ethics.ai/record/18775" }, { "id": 18773, "url": "https://www.theregister.com/ai-and-ml/2026/08/12/openwaldo-aims-to-blow-the-doors-off-proprietary-ai-training-models/5286864", "title": "OpenWALDO aims to blow the doors off proprietary AI training models", "summary": "Contributors wanted: 167B transparent tokens have a long way to go against AI giants' trillions", "authors": null, "category": "news", "topics": "transparency", "published_at": "2026-08-12T16:57:33.000Z", "source": "The Register", "ethics_ai_record_url": "https://ethics.ai/record/18773" }, { "id": 19480, "url": "https://arxiv.org/abs/2608.12441v1", "title": "Dual Spatial-Temporal Attribution: Architecture-Aligned Post-Hoc Explainability for Recurrent Graph Anomaly Detection", "summary": "Deep learning detectors for anomalies in dynamic graphs have reached strong accuracy, yet they remain opaque: when an edge is flagged, the analyst receives a score but no reason. This opacity is untenable in the cooperative, regulated information systems where such detectors are deployed, where automated decisions must be auditable and trustworthy. We address this gap for AddGraph, the foundational GCN+GRU framework for edge-level anomaly detection in dynamic graphs, which to our knowledge has n", "authors": "Iyad Assaad Nekka, Hamida Seba, Khaled Walid Hidouci, Karima Amrouche", "category": "research", "topics": "regulation,transparency", "published_at": "2026-08-12T15:58:27.000Z", "source": "arXiv cs.LG", "ethics_ai_record_url": "https://ethics.ai/record/19480" }, { "id": 19030, "url": "https://arxiv.org/abs/2608.12198v1", "title": "Learning-Based Behavior Planning for Automated Driving: Real-World Integration and Deployment", "summary": "Recent research in machine and deep learning has shown the potential of learningbased motion planning approaches to improve the driving behavior of automated vehicles, especially in complex environments. However, their complex nature and lack of transparency can hinder explainability and trustworthiness and complicate safety assurance. Motivated by these challenges, we propose a hybrid planning architecture that combines the advantages of machine learning with the verifiability and the determini", "authors": "Jean-Pierre Busch, Guido Linden, Jan Bergmann, Lutz Eckstein", "category": "research", "topics": "transparency,environment", "published_at": "2026-08-12T15:52:18.000Z", "source": "arXiv cs.AI", "ethics_ai_record_url": "https://ethics.ai/record/19030" }, { "id": 18776, "url": "https://arxiv.org/abs/2608.12166v1", "title": "Co-constructing sociotechnical AI governance: participatory system mapping using algorithm registers", "summary": "Algorithm registers have been championed as a means of providing transparency on the use of algorithms in public services. Yet potential publics differ in their expectations of what should be made transparent and how, as well as in their interest in and ability to parse the information currently published in the registers. Moreover, it remains unclear how these instruments can represent the sociotechnical systems in which these algorithms are embedded, and how system-level transparency can facil", "authors": "Íñigo de Troya, Maurus Enbergs, Neelke Doorn, Roel Dobbe", "category": "research", "topics": "regulation,transparency", "published_at": "2026-08-12T15:27:45.000Z", "source": "arXiv", "ethics_ai_record_url": "https://ethics.ai/record/18776" }, { "id": 19037, "url": "https://arxiv.org/abs/2608.12104v1", "title": "No One to Blame: A Framework of Constitutive AI Unaccountability", "summary": "The increasing deployment of autonomous, agentic AI systems challenges traditional accountability mechanisms. Existing research predominantly frames AI accountability gaps as barriers that can be overcome through better standards, transparency, and institutional reform. We argue that this framing is insufficient: certain configurations of actors, systems, and institutions render AI accountability conceptually unachievable regardless of effort. We introduce the concept of constitutive AI unaccoun", "authors": "Long Hoang Nguyen, Eva Späthe, Sebastian Lins, Ali Sunyaev", "category": "research", "topics": "agents-autonomy,transparency", "published_at": "2026-08-12T14:25:05.000Z", "source": "arXiv cs.AI", "ethics_ai_record_url": "https://ethics.ai/record/19037" }, { "id": 19057, "url": "https://arxiv.org/abs/2608.12077v1", "title": "A Comparison of Malware Image Transformations Using Grad-CAM and Hybrid Learning Models", "summary": "Recent studies have shown that binary-to-image representations can enable effective machine learning-based results for malware detection and classification. However, performance can vary significantly, depending on the technique used to convert binaries to images. Furthermore, the explainability and interpretability of image-based models is largely unexplored within the malware domain. In this research, we employ Gradient-weighted Class Activation Maps (Grad-CAM) as an eXplainable AI (XAI) tool,", "authors": "Vibha Bhavikatti, Mark Stamp", "category": "research", "topics": "safety-alignment,transparency", "published_at": "2026-08-12T14:00:44.000Z", "source": "arXiv cs.CR (AI security)", "ethics_ai_record_url": "https://ethics.ai/record/19057" }, { "id": 19017, "url": "https://www.darkreading.com/cybersecurity-operations/walmart-leaders-transform-security-operations-without-going-bananas", "title": "Walmart Leaders Transform Security Operations Without Going Bananas", "summary": "The big-box giant has scaled its defenses by encouraging trust and innovation. Good communications, transparency, and team spirit are key factors.", "authors": "Richard Thurston", "category": "news", "topics": "transparency", "published_at": "2026-08-12T12:41:03.000Z", "source": "Dark Reading (AI security)", "ethics_ai_record_url": "https://ethics.ai/record/19017" }, { "id": 18891, "url": "https://www.ft.com/content/b93d8030-203b-4445-b4a7-49e52d9b17a5", "title": "Who is Anthropic’s auditor — and why should we care?", "summary": "Magic bean counters", "authors": null, "category": "news", "topics": "transparency", "published_at": "2026-08-12T11:00:03.000Z", "source": "Financial Times Technology (headlines)", "ethics_ai_record_url": "https://ethics.ai/record/18891" }, { "id": 18788, "url": "https://arxiv.org/abs/2608.11803v1", "title": "Silent Updates: Measuring and Closing the Post-Deployment Disclosure Gap", "summary": "Deployed foundation models are often not static systems, with providers able to modify system behavior through fine-tuning, classifier updates, system prompt revisions, retrieval changes, and routing changes. These updates can be made silently -- that is, without public disclosure, a version increment, or re-evaluation. Such silent updates challenge a core assumption behind current AI governance frameworks that an externally verifiable chain of custody links the model referred to in evaluation r", "authors": "Sophia Abraham, Ben Bucknall", "category": "research", "topics": "regulation,transparency", "published_at": "2026-08-12T08:45:49.000Z", "source": "arXiv", "ethics_ai_record_url": "https://ethics.ai/record/18788" }, { "id": 19048, "url": "https://arxiv.org/abs/2608.11794v1", "title": "Toward Meaningful Transparency for AI Chatbots: Disclosing Persuasive Intent Reduces Persuasion", "summary": "The growing role of AI-generated content and AI-enabled systems in public communication has led regulators to demand clear disclosure of content provenance and AI involvement. But the effects of such disclosures remain uncertain. We test two disclosure approaches in their impact on an AI chatbot's persuasive appeal. In a preregistered experiment, 1,500 UK adults held a short conversation with a persuasive chatbot about one of 60 policy issues. The chatbot was identical for everyone. We randomize", "authors": "Adrian Rauchfleisch, Andreas Jungherr", "category": "research", "topics": "regulation,transparency", "published_at": "2026-08-12T08:37:44.000Z", "source": "arXiv cs.HC", "ethics_ai_record_url": "https://ethics.ai/record/19048" }, { "id": 18790, "url": "https://arxiv.org/abs/2608.11741v1", "title": "JieZi: A Large-Scale Expert-Audited Dataset and Benchmark for Ancient Chinese Character Exegesis", "summary": "The scholarly exegesis of ancient Chinese characters demands integrating visual observation, linguistic analysis, and historical context. However, existing computational approaches focus narrowly on subtasks such as character recognition and retrieval, lacking the structured datasets and benchmarks required for comprehensive scholarly analysis. To address this limitation, we introduce Ancient Chinese Character Exegesis (ACCE), a vision-language question answering (VQA) task that models the schol", "authors": "Ran Li, Huiguo He, Jiahuan Cao, Junle Liu, Hiuyi Cheng, Lianwen Jin", "category": "research", "topics": "transparency", "published_at": "2026-08-12T07:30:00.000Z", "source": "arXiv", "ethics_ai_record_url": "https://ethics.ai/record/18790" }, { "id": 18854, "url": "https://artificialintelligenceact.substack.com/p/the-eu-ai-act-newsletter-108-enforcement", "title": "The EU AI Act Newsletter #108: Enforcement Begins", "summary": "New transparency obligations apply, and the AI Office opens complaint and whistleblower channels.", "authors": "Risto Uuk", "category": "org", "topics": "regulation,transparency", "published_at": "2026-08-12T06:15:58.000Z", "source": "The EU AI Act Newsletter", "ethics_ai_record_url": "https://ethics.ai/record/18854" }, { "id": 18796, "url": "https://arxiv.org/abs/2608.11632v1", "title": "Beyond Memory: A Transactional Continuity Kernel for Long-Lived AI Agents", "summary": "Persistent AI agents accumulate versioned state across long horizons, but storage retention alone does not identify authoritative state. Without an explicit control plane, unmediated updates by models, tools, and background workers risk stale overwrites, un-audited exposures, and self-authorizing privilege escalation. We argue that agent state governance is an infrastructural activation problem, defining continuity as an unbroken, authorized lineage of accepted branch heads. We present the Conti", "authors": "Jun He, Deying Yu", "category": "research", "topics": "regulation,agents-autonomy,transparency", "published_at": "2026-08-12T04:28:49.000Z", "source": "arXiv", "ethics_ai_record_url": "https://ethics.ai/record/18796" }, { "id": 18350, "url": "https://arxiv.org/abs/2608.10194", "title": "Context and Symmetry in Auditing: A Case Study of Skeleton Inference in Motion Capture", "summary": "arXiv:2608.10194v1 Announce Type: new Abstract: Humans are increasingly expected to interact with AI systems that observe and make inferences about them - but do these systems actually work? A standard approach to answering this question is AI auditing. Conducting an AI audit requires identifying how a system behaves (i.e., determining what types of inputs to audit it with and then observing and documenting actual system behavior) and contrasting that with how a system should behave (i.e., deter", "authors": "Emma Harvey, Emanuel Moss, Hauke Sandhaus, Abigail Z. Jacobs, Mona Sloane", "category": "research", "topics": "transparency", "published_at": "2026-08-12T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/18350" }, { "id": 18351, "url": "https://arxiv.org/abs/2608.10329", "title": "Who Gets Heeded? An Obligation-Level Audit of Responsiveness in EPA Rulemaking", "summary": "arXiv:2608.10329v1 Announce Type: new Abstract: Notice-and-comment rulemaking gives any affected party the same formal right to influence federal regulation, but formal access is not substantive capacity to shape rule text. Existing strategies operate at the rule or aggregate-corpus level, too coarse to capture the discrete regulatory obligations where commenters seek change. We introduce obligation-level responsiveness auditing, an auditable, AI-assisted framework for measuring whether public-c", "authors": "Jianing Fan, Yue Yao", "category": "research", "topics": "regulation,transparency", "published_at": "2026-08-12T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/18351" }, { "id": 18368, "url": "https://arxiv.org/abs/2608.10858", "title": "Auditable AI-Assisted Research Writing: An Engineering Discipline with Pre-Registered Process Observation", "summary": "arXiv:2608.10858v1 Announce Type: cross Abstract: Language models now draft, classify and criticise inside research production, yet the artifacts they help produce carry little accountable history. Rather than detecting machine involvement afterwards, we specify an auditability discipline built at production time: git sealing with an anchor lineage, hash-bound provenance, red-line gates that refuse non-compliant artifacts and log every refusal, cross-model role separation, and programmatic assem", "authors": "Yang Zhou, Chengqun Yu", "category": "research", "topics": "transparency", "published_at": "2026-08-12T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/18368" }, { "id": 18373, "url": "https://arxiv.org/abs/2606.17441", "title": "Patients With Personality: Realistic Patient Simulation through Controlled Diversity and Selective Disclosure", "summary": "arXiv:2606.17441v2 Announce Type: replace-cross Abstract: Simulating realistic patient interactions is a key requirement to testing clinical applications of LLMs at scale without time-consuming and expensive user studies. However, existing approaches often lack realism and controllability, often oversharing information unprompted, and failing to capture the wide variability of patient behavior. Here, we introduce PatientsWithPersonality (PWP), a patient simulation framework that generates realis", "authors": "Moritz Schlager, Friederike Jungmann, Samuel Schmidgall, Philipp Raffler, Franziska Hartl, Eva Wende, Paula Ro{\\ss}m\\\"uller, Conrad Ketzer, Avinatan Hassidim, Dale R. Webster, Yossi Matias, Yun Liu, Daniel Rueckert, Mike Schaekermann, Paul Hager", "category": "research", "topics": "healthcare,transparency", "published_at": "2026-08-12T04:00:00.000Z", "source": "arXiv cs.CY", "ethics_ai_record_url": "https://ethics.ai/record/18373" } ], "attribution": "via ethics.ai" }