Confident but wrong answers from generative systems are not just a quality issue - in cybersecurity, they can distort triage, remediation, and trust.
As the 2026 maturità approaches, AI is being framed as a study aid - but its real value, and its real danger, lie in how carefully students verify what it produces.
Generative systems can produce fluent answers that feel reliable while remaining only statistically plausible, and that mismatch is now a core trust problem.
AI hallucinations are not just accuracy bugs; in high-stakes environments, they can become trust bugs that distort real-world decisions.
Behind the dazzling facade of generative AI lies a world of costly errors, hallucinated results, and energy-guzzling inefficiency.