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Input validation, output filtering, and content moderation classifiers.
Also in Non-Model
Supplementary information can be shown to the user in specific query topics where factual accuracy is critical. This intervention can effectively divert users from potential inaccuracies generated by AI models in sensitive contexts. For example, during electoral processes, where model hallucinations can be particularly costly or have a negative impact on society, LLMs can offer their users the option of being redirected to accurate and up-to-date information sources [11]. Since pop-up interventions can be intrusive to workflows, they are best used in situations where the benefits of the information outweigh the cost of distraction
Reasoning
Pop-up interventions filter or interrupt model outputs at runtime before user delivery.
Post-deployment practices
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.
Operate and Monitor
Running, maintaining, and monitoring the AI system post-deployment
Deployer
Entity that integrates and deploys the AI system for end users
Manage
Prioritising, responding to, and mitigating AI risks
