Who do you trust with your personal data? And what happens when that “who” becomes a “what”, as AI models are increasingly entrusted with high-stakes decisions?
Every time an AI system determines how data should be routed across a network, it is making decisions that directly affect privacy, security, and reliability. Yet the skepticism many of us feel is entirely rational. AI models that make these decisions are inherently opaque. They optimize for performance in ways that are often difficult – if not impossible – to explain, operating at speeds and scales far beyond human oversight.
At the same time, the benefits of AI-driven decision-making in mission-critical environments, like healthcare, essential transport services, and emergency communications, are impossible to ignore. In these contexts, delaying adoption risks foregoing significant gains in efficiency and operational performance.
Trust is not a feature you add to an AI system at the end; it is built through rigorous, verifiable testing and optimization at every stage
Sameh Yamany, Viavi
