AI Trust & Safety Operations

AI Trust & Safety Operations is the operational discipline of running a T&S function the way modern engineering organisations run SRE or security: as a profession with detection-engineering tradecraft, investigation rigour, runbooks, SLAs, error budgets, on-call rotations, post-incident reviews, professional bodies, and standards. It complements content-moderation policy work but is distinct from it — policy decides what stays up; operations decides whether the system that enforces policy is fast, accurate, humane, durable, and defensible. Over the last five years T&S has stopped being a back-office activity and has become an engineering-grade discipline subject to regulator inspection, public reporting, and material business risk. The DSA, the UK Online Safety Act, the AI Act, NetzDG, India IT Rules, and a growing list of sectoral regulators all assume there is a running operational function with the rigour to defend its work.

This track is written for the practitioners doing this work day to day: T&S leaders, T&S operations managers, detection engineers, T&S software engineers, investigators, integrity / civic teams, threat-intel and CIB analysts, program managers, on-call commanders, and the cross-functional partners (security, RAI, legal, comms, product) who interlock with T&S. Every topic explains the underlying operational discipline (drawing on the T&S literature, TSPA professional materials, GIFCT and Tech Coalition operational guides, the SRE / IR playbooks adapted for T&S, regulator expectations, and hard-won production experience), the practical artefacts and rituals that operationalise it (runbooks, dashboards, OKRs, threat models, evidence packets, after-action reports), and the failure modes where T&S operations quietly break down in practice. The aim is that a reader can stand up a credible T&S operations function, integrate it with engineering and governance, and defend it to boards, regulators, customers, and the people the platform actually affects.