arXiv AI
Jun 24
Exploring the relationship between human-centric AI and firm idiosyncratic risks
arXiv:2606. 24224v1 Announce Type: new Abstract: Despite the extensive discussions of human-centric AI (HCAI) in Industry 5.
Buyer Artificial Intelligence-Enabled Environmental Governance and Supplier Environmental Controversies: An Organizational Information Processing and Signaling
The study investigates how exposure to buyers’ artificial intelligence (AI)-enabled environmental governance affects supplier environmental controversies. Using text analysis and panel data from 2,505 suppliers of U.S.-listed firms across 41 countries (2020‑2024), the authors find that such exposure is negatively associated with controversies in the following year. The effect is stronger in countries with higher AI readiness and regulatory quality.
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Hugging Face Trending Papers
Jun 23
Exploring the relationship between human-centric AI and firm idiosyncratic risks
Despite the extensive discussions of human-centric AI (HCAI) in Industry 5. 0, its effects on firms' idiosyncratic risks (IR) remains underexplored.
arXiv AI
Jun 12
The Challenges of Balancing AI Compliance and Technological Innovations in Critical Sectors: A Systematic Literature Review
arXiv:2606. 12423v1 Announce Type: cross Abstract: The rapid integration of artificial intelligence (AI) into critical infrastructure including healthcare, finance, energy, and defense, offers transformative benefits but also conflicts with evolving regulatory and governance frameworks.
arXiv AI
Jun 26
The Governance Inversion Hypothesis: Why More AI Regulation May Produce Less Organisational Control
arXiv:2606. 26117v1 Announce Type: cross Abstract: This paper introduces the Governance Inversion Hypothesis (GIH) to explain a growing paradox in artificial intelligence (AI) governance: under conditions of increasing regulatory expansion and technological complexity, organisations may become more formally governed while simultaneously experiencing a decline in operational control over AI systems.
arXiv AI
Jul 24
Regulating autonomous and agentic AI
arXiv:2607. 21345v1 Announce Type: new Abstract: Regulating activities where regulatees use autonomous and agentic AI is challenging.
arXiv AI
Jun 11
Irresponsible AI: big tech's influence on AI research and associated impacts
arXiv:2512. 03077v2 Announce Type: replace-cross Abstract: The accelerated development, deployment and adoption of artificial intelligence systems has been fuelled by the increasing presence of big tech in the AI field.
arXiv AI
Aug 14
Why AI Governance Frameworks Are Hard to Adopt: A Role-Based Stress Test of the NIST AI RMF
arXiv:2608. 12352v1 Announce Type: cross Abstract: AI governance frameworks can be known, used, and implemented in form without becoming governance in practice.
arXiv AI
Jul 20
Closing the AI Trust Gap: The Case for Independent Certification for Trustworthy AI
arXiv:2607. 15992v1 Announce Type: new Abstract: Over the past decade, responsible AI (RAI) has produced a substantial body of practice for identifying and mitigating the risks AI poses in high-stakes settings.
arXiv AI
Sep 2
When the Algorithm Becomes the Brand Crisis: A Sociotechnical Theory of Distributed Responsibility and Accountable Transparency
The paper examines how responsibility is assigned when AI systems fail, proposing a sociotechnical theory that distinguishes between AI incidents, organisational crises, and scandals. It argues that the configuration of an incident shapes actor-specific attribution, which in turn influences perceptions of capability, integrity, fairness, and relationships, and that public moralisation can elevate an incident to scandal. The authors introduce ‘accountable transparency’—a response framework combining timely notice, intelligible accounts, role acknowledgement, remedy, evidence of correction, and recourse—as a way to manage blame, trust, and communication credibility.
arXiv AI
Aug 12
What We Know about Responsible AI Practices in Industry: A Half Decade of Empirical Research
arXiv:2608. 10431v1 Announce Type: cross Abstract: Responsible AI (RAI) has become a central concern for technology companies, regulators, and the public.
arXiv AI
Jul 17
Global Index on Responsible AI: 2026 Report
arXiv:2607. 14782v1 Announce Type: new Abstract: Grounded in human rights-based frameworks such as the UNESCO Recommendation on the Ethics of AI, the Global Index on Responsible AI (GIRAI) examines how countries translate responsible AI commitments into enforceable protections, institutional capacity, and redress mechanisms.
Hugging Face Trending Papers
Aug 13
AI and Consumer Rights in India Working Paper
As AI systems proliferate in consumer facing applications, questions about liability for AI related harms remain unresolved. This working paper examines whether India's Consumer Protection Act, 2019, adequately addresses harm caused by defective AI products and services, and whether it proportionately allocates liability across the AI value chain.