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Segnalazione degli Incidenti AI
AI incident reporting is the structured process by which an organization documents, communicates internally, and possibly discloses publicly the cases in which an AI system caused harm, dangerous behavior, or significant violations of its own safety policies. An incident can range from an isolated error with limited impact to a systemic failure affecting many users simultaneously.
An incident reporting program typically includes dedicated channels for collecting reports from users, employees, or automated monitoring systems, a severity classification based on predefined criteria, a root-cause analysis process to determine whether the problem stems from the model, the data, the application integration, or misuse, and corrective actions that can include modifying the model, updating safety filters, or transparently communicating with affected users.
In modern AI, incident reporting is increasingly a regulatory obligation as well as a best practice: regulations such as the EU AI Act require providers of high-risk systems to report serious incidents to competent authorities within defined timeframes. Public, cross-organization databases also exist where AI incidents are collected in anonymized form, aiming to help the whole industry learn from others' mistakes.
The concept is borrowed from incident management in other regulated, high-reliability sectors, such as civil aviation and cybersecurity, where systematic reporting and sharing of error causes have been established practice for decades; it was adapted to AI starting in the second half of the 2010s as automated systems scaled up in production.
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