Explore 18 AI terms in Risk Management
Aleatoric uncertainty refers to the inherent variability in a system or process that cannot be reduced.
Existential risk refers to threats that could end human civilization or permanently curtail its potential.
Extreme Value Theory (EVT) studies the behavior of maximum or minimum values in datasets, useful in risk assessment.
A guarded launch is a controlled release of AI systems to mitigate risks and ensure safety.
Harm Taxonomy is a classification system for categorizing different types of harm caused by various actions or events.
Hazard analysis identifies and evaluates potential risks in processes or systems to ensure safety and compliance.
Insurance pricing is the process of determining the cost of insurance coverage based on risk assessment.
Margin violation occurs when a trading account's equity falls below required margin levels.
Membership Risk refers to the potential dangers and vulnerabilities associated with being part of a group or organization.
Model Risk refers to the potential for errors in AI models that can lead to incorrect predictions or decisions.
Portfolio optimization is the process of selecting the best mix of assets to maximize returns while minimizing risk.
Red Teaming is a simulated attack to identify vulnerabilities in systems, processes, or organizations.
A Red-Teaming Playbook is a guide for simulating attacks to identify vulnerabilities in systems and strategies.
Risk assessment is the process of identifying and evaluating potential risks in order to minimize negative impacts.
A Risk Assessment Matrix is a tool used to evaluate and prioritize risks based on their likelihood and impact.
A safety classifier is an AI tool that assesses and mitigates risks in automated systems.
Soft targets are locations or individuals that are vulnerable to attacks due to their lack of security.
Uncertainty Quantification (UQ) is the science of quantifying and managing uncertainties in mathematical models and simulations.