New preprint (engrXiv DOI): https://doi.org/10.31224/5792
Agentic AI is powerful—and risky—once tools and data are in reach. This preprint lays out a Zero-Trust architecture for AI agents
When intelligence learns to upgrade itself, progress turns into a feedback loop. From a Skyrim glitch to real-world AI, the lesson is clear: without alignment and governance, optimisation can spiral beyond control. The question is whether we forge wisdom before we forge gods.
AI’s promise is undermined by scandals like faulty exam grading. To rebuild trust, we need independent oversight, clear rules, public involvement and global cooperation so AI serves everyone fairly and earns legitimacy. This piece calls for enforceable regulation, public oversight and global action.
Boards now face an AI dilemma: how to balance cost efficiency, safety, and performance at planet scale. This whitepaper shows how trust can be made auditable through measurable SLOs, global standards, and case lessons—turning governance from compliance into competitive advantage.
