The AI Decision Trust Framework Preparing for Safe AI Infrastructure скачать в хорошем качестве

The AI Decision Trust Framework Preparing for Safe AI Infrastructure

AI is beginning to influence how we deploy, manage and remediate infrastructure, but giving AI any level of control introduces a far more fundamental question: how do we trust it? While exploring AI adoption in a fintech environment, I started building a small personal project to map out how AI could participate safely in infrastructure workflows. The result is a practical model I call the AI Decision Trust Framework, which outlines the boundaries, safeguards and validation steps needed before AI is allowed to make or influence operational decisions. This talk walks through how this framework was developed and how it can be applied in real environments. We'll cover: It breaks down the different levels of AI involvement, the types of risks each level introduces, and the guardrails required to keep infrastructure reliable and compliant. Examples of how to categorize actions, define trust levels, enforce approvals and maintain an audit trail that satisfies both engineering needs and regulatory expectations. How to evaluate whether systems are ready for AI-driven operations and what must be in place before autonomous behavior becomes safe. Even if your organization is early in its AI journey, this session offers a practical starting point for thinking about trust, safeguards and governance in AI-powered infrastructure.