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Staged rollout strategies, phased deployment, and tiered access approaches for production systems.
Also in Operations & Security
When a model is developed by a provider for use in a certain AI system, it may also be useful to release the model itself more widely. Such developers can follow a staged release approach, in which they first grant access to the model via an API to trusted partners or the public, in order to scope the models’ capabilities and detect harmful or dangerous features [195]. After a period of an initial closed release and potentially further safety-training, the developers of the AI model can then release the weights, if they are confident that the AI model poses minimal systemic risk.
Reasoning
Staged release controls deployment pace and access scope to manage risks operationally.
Model Release
Model development
2.4 Engineering & DevelopmentModel development > Data-related
1.1 ModelModel evaluations
2.2.2 Testing & EvaluationModel evaluations > General evaluations
2.2.2 Testing & EvaluationModel evaluations > Benchmarking
3.2.1 Benchmarks & EvaluationModel evaluations > Red teaming
2.2.2 Testing & EvaluationRisk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems
Gipiškis, Rokas; San Joaquin, Ayrton; Chin, Ze Shen; Regenfuß, Adrian; Gil, Ariel; Holtman, Koen (2024)
Organizations and governments that develop, deploy, use, and govern AI must coordinate on effective risk mitigation. However, the landscape of AI risk mitigation frameworks is fragmented, uses inconsistent terminology, and has gaps in coverage. This paper introduces a preliminary AI Risk Mitigation Taxonomy to organize AI risk mitigations and provide a common frame of reference. The Taxonomy was developed through a rapid evidence scan of 13 AI risk mitigation frameworks published between 2023-2025, which were extracted into a living database of 831 distinct AI risk mitigations.
Deploy
Releasing the AI system into a production environment
Developer
Entity that creates, trains, or modifies the AI system
Manage
Prioritising, responding to, and mitigating AI risks
