arXiv AI
Aug 11
Unaccountable Delegation, Fading Skills: Mapping the Risks of Workplace AI Agents
arXiv:2608. 08601v1 Announce Type: new Abstract: To anticipate socio-technical risks from AI agents, organizations need taxonomies to classify them.
Vertical Standardisation for High-Risk AI Systems under the EU AI Act: A Domain-Specific Framework for Algorithmic Hiring
arXiv:2607. 12588v1 Announce Type: new Abstract: According to the recent European legislation, high-risk AI systems will have to adapt in order to comply with requirements related to specific areas, like risk management, data quality and governance, logging and traceability, technical documentation, transparency, human oversight, and accuracy, as outlined in the European Artificial Intelligence (AI) Act.
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arXiv AI
Jun 12
The AI Legal Specialist: A Juridically Autonomous Professional Profile for AI Governance
arXiv:2606. 12415v1 Announce Type: cross Abstract: The rapid global expansion of artificial intelligence regulation has generated, across multiple jurisdictions, a demand for legal expertise dedicated to AI that the market has addressed in a fragmented manner.
arXiv Machine Learning
Jun 5
Towards AI epidemiology: a measurement standardisation framework for prospective risk detection
arXiv:2512. 15783v3 Announce Type: replace-cross Abstract: This paper proposes a measurement standardisation framework that compresses expert-AI interactions into structured, comparable fields for prospective risk detection in deployed AI systems, without access to model internals.
arXiv AI
Jun 2
GovAI-Pipe: A Layered AI Governance Pipeline for Citizen-Facing AI in Turkey's e-Government Gateway
arXiv:2606. 01417v1 Announce Type: new Abstract: Turkey's e-Government Gateway (e-Devlet) serves over 68 million registered users with more than 9,200 government services, and is increasingly integrating artificial intelligence into citizen-facing applications such as chatbot assistants and eligibility assessments.
arXiv AI
Jul 16
Post-Deployment Accountability in AI Governance: A Cross-Regulatory Empirical Analysis of AI Incidents
arXiv:2605. 16281v2 Announce Type: replace-cross 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.
arXiv AI
6d ago
Co-constructing sociotechnical AI governance: participatory system mapping using algorithm registers
arXiv:2608. 12166v1 Announce Type: cross Abstract: Algorithm registers have been championed as a means of providing transparency on the use of algorithms in public services.
arXiv AI
Jul 28
Robustness and Cybersecurity in the EU Artificial Intelligence Act
arXiv:2502. 16184v3 Announce Type: replace Abstract: The EU Artificial Intelligence Act (AIA) establishes different legal principles for different types of AI systems.
arXiv AI
1d ago
Position: AI Governance Needs ISO-like Interoperability Protocols, Not Just Laws
arXiv:2608. 14568v1 Announce Type: new Abstract: As Artificial Intelligence (AI) systems become deeply integrated into critical global infrastructure, the urgency for robust governance frameworks has intensified.
arXiv AI
Jul 17
Traccia: An OpenTelemetry-Based Governance Platform for AI Systems
arXiv:2607. 14309v1 Announce Type: new Abstract: The rapid development of Large Language Models (LLMs) and Artificial Intelligent (AI) powered autonomous agents has fundamentally changed the existing forms of software governance.
arXiv AI
Jul 29
Why Public Service AI Governance Frameworks Risk Failing in the Age of General-Purpose AI: Lessons from Policing
arXiv:2607. 25648v1 Announce Type: cross Abstract: Public services face growing pressure to adopt artificial intelligence (AI) to close the gap between rising demand and falling resources.
arXiv AI
6d ago
Variable Selection in the Context of AI Fairness
arXiv:2608. 11251v1 Announce Type: cross Abstract: Fairness in AI systems has become more important with recent regulatory demands, such as the EU AI Act.
arXiv AI
Aug 11
Designing for Ethical AI: HCI Feature Considerations to Improve Fairness and User Experience in AutoML use for Human Resources
arXiv:2608. 07477v1 Announce Type: cross Abstract: This thesis examines the fairness of Automated Machine Learning (AutoML) tools in human resource hiring systems through the combined lenses of regulation, business strategy, and Human-Computer Interaction (HCI).