arXiv AI
Ctrl-F-Resist. Practices, Challenges, and Technical Needs of Civil Society Organizations Monitoring the Far-Right Online
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arXiv AI
Jun 17
Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit
arXiv:2604. 09998v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have recently emerged as promising tools for augmenting Security Operations Center (SOC) workflows, with vendors increasingly marketing autonomous AI solutions for SOCs.
arXiv AI
Jul 20
A Critical Analysis of Trustworthy AI Tools, Mark Frameworks, and the Implementation Chasms
arXiv:2607. 15480v1 Announce Type: new Abstract: As artificial intelligence (AI) systems increasingly impact society, ensuring their ethical and trustworthy deployment has become a global priority.
arXiv AI
4d ago
The Landscape of Generative AI in Information Systems: A Synthesis of Secondary Reviews and Research Agendas
The paper reviews secondary studies and research agendas on generative AI (GenAI) in information systems, synthesizing evidence from 28 selected papers. It identifies GenAI’s transformative benefits—productivity, innovation, personalization, and democratized expertise—while highlighting challenges such as technical unreliability, ethical risks, and governance gaps. The authors propose a research agenda that shifts IS scholarship toward shaping the co‑evolution of AI capabilities with organizational routines, societal values, and regulatory institutions, emphasizing hybrid human‑AI ensembles, situated validation, design principles for probabilistic systems, and adaptive governance.
arXiv AI
Jun 2
Authenticity Debt and the Synthetic Content Threat Landscape: A Layered Framework for Trust, Provenance, and IP Governance in the Generative AI Era
arXiv:2606. 00621v1 Announce Type: cross Abstract: Generative artificial intelligence has fundamentally changed how content is now produced.
arXiv AI
Jun 15
Regulating the Machine Contributor: Governance and Policy Alignment in Open Source
arXiv:2606. 14594v1 Announce Type: cross Abstract: AI-assisted software development has moved from line-level autocomplete to agents that can plan changes, edit files, and submit pull requests with limited human supervision.
Hugging Face Trending Papers
Aug 27
LAAF: A Layered Accountability Architecture Framework for LLM Applications
The paper presents LAAF, a Layered Accountability Architecture Framework for Large Language Model (LLM) applications, developed through a systematic review of 122 primary studies and 12 regulatory documents. It identifies five dimensions of accountability and four families of mechanisms—technical controls, human oversight, organisational governance, and documentation/traceability—each assessed for maturity. The framework is mapped onto major regulatory standards (EU AI Act, NIST AI RMF, ISO/IEC 42001) and highlights persistent gaps such as under‑specified human oversight and lack of shared accountability metrics.