The agent boom is turning mistakes into “liability laundering,” where vendors blame prompts, users blame models, and no one can be meaningfully held to account. The fix is not another safety slogan. It is standardizing proof at the moment of action, so agents cannot become blameless proxies.
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
Leaders keep asking, “Can the model do it?” The better question is, “Can we govern it?” Durable organizations pair principled dissent with grounded realism and give both a single vantage point—a watchtower—to see weak signals early and act in time.
Frontier tech wins by shipping safely, not just fast. This piece shows how to resolve the release paradox with a four-stage Release Readiness Map: test hard, pilot small, scale with monitoring, and plan rollback. Leaders get metrics and gates to launch responsibly across US, EU and Asia.
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.
