TL;DR
This case illustrates how human oversight can be engineered into employee-facing AI systems while preserving operational autonomy in real-world deployments.
This conceptual study analyzes the accountability gap that opens when strategic goals are delegated to algorithmic agents and develops the Dynamic Authority Delegation Model (DADM), which distributes responsibility among human strategic intent, algorithmic operational execution, and institutional oversight.
The paper describes an approach to automated dynamic operational alignment in a complex high-risk process, exemplified by a case study on autonomous drilling, and possible sources of AI misalignments are discussed.
Human oversight is widely held to mitigate the risks of AI systems. Even for systems that produce discrete outputs at identifiable decision points, the realisation of human oversight as a reactive measure is empirically fragile, yet increasingly well understood. However, for agentic AI -- systems that plan, decompose g...
Artificial Intelligence (AI) is increasingly becoming an important technology in Human Resource Management (HRM). AI-enabled systems can support recruitment, candidate screening, employee onboarding, learning and development, performance management, workforce planning, employee engagement, HR analytics and routine admi...
Agentic artificial intelligence (AI) shifts digital government from systems that generate recommendations toward networked systems that perceive, plan, communicate, invoke tools, initiate actions, and adapt with limited direct supervision. This article examines agentic AI as an intelligent cybersecurity governance prob...
The STAGE framework is proposed as a practical approach to maintaining human judgment and organizational accountability when integrating AI into regulatory compliance and focuses on whether organizations can use AI to identify risks while keeping qualified people responsible for interpreting alerts, making decisions, d...
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