TL;DR
It is argued that accountable, ethical AI is not a governance overlay applied after deployment but an architectural property that requires encoding ethical commitments as explicit, contestable constraints rather than as emergent properties of trained weights.
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...
ADAE is introduced, a proposed AI engineering subdiscipline concerned with establishing measurable, continuous, and actionable accountability for deployed AI systems and treats accountability as a deployment-layer property rather than solely as a property of an individual model.
LATTICE (Layered Agentic Triad Topology for Intelligent Coordinated Execution), a governance-first architecture that reframes the authorization question from “do the authors trust this AI?” to “do they trust this architecture?”
The proliferation of agentic artificial intelligence (AI) systems autonomous, goal-directed agents capable of acting with minimal human oversight, has exposed fundamental inadequacies in existing civil liability frameworks. Traditional tort, product liability, and custodian regimes struggle to accommodate systems whose...
This position paper argues that EBRB could serve as a core safety and reasoning governor within LLM-based agentic pipelines, yielding hybrid systems to better align agentic AI systems with emerging regulatory and ethical requirements for Trustworthy AI (TAI) in high-risk settings.
Agentic artificial intelligence (AI)—systems that reason, act, and interact with autonomy and persistence—presents qualitatively new governance challenges compared to traditional large language models. By operating across multimodal environments and pursuing goals without constant human input, agentic AI introduces b...
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