ETSI publishes lifecycle specification for AI systems, intended to reduce likelihood of deepfakes

Developed by the Technical Committee on Securing Artificial Intelligence (TC SAI) of The European Telecommunications Standards Institute, a technical specification known as ETSI TS 104 275 takes a preventive approach to deepfake-related risks in AI systems.

Rather than focusing primarily on detecting manipulated content after its creation, ETSI TS 104 275 addresses safeguards throughout an AI system’s lifecycle, from design and development to deployment and ongoing operation.

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The specification calls upon AI systems developers to conduct risk assessments before deployment, to identify potential misuse and establish safeguards. Organizations would also be expected to maintain human oversight, introduce protections such as content filtering, AI-generated-content labelling and user warnings where appropriate, and monitor emerging threats and incidents.

The recommendations also call for organizations to maintain documentation and records showing that the relevant controls have been implemented and are working as intended. It includes test scenarios and pass/fail criteria to help assess whether the safeguards effectively reduce deepfake-related risks.

Why it matters

The specification provides practical measures to help organizations identify and mitigate the risks of harmful deepfakes, supporting objectives of the EU AI Act and extending security considerations beyond systems classified as high-risk. It builds on baseline cybersecurity requirements set forth in ETSI EN 304 223 for baseline cybersecurity requirements in AI models and systems.

Further reading

ETSI introduces standard to prevent harmful deepfakes at source. Press release. October 29, 2026. Civil Society Alliances for Digital Empowerment (CADE), a project co-funded by the European Union