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Structured analysis to identify, characterize, and prioritize potential harms and risks.
Also in Risk & Assurance
Reasoning
Assesses environmental impact and sustainability of AI training activities, identifying and documenting risks pre-deployment.
Assess safety to physical environments when deploying GAI systems
2.2.1 Risk AssessmentDocument anticipated environmental impacts of model development, maintenance, and deployment in product design decisions.
2.2.1 Risk AssessmentMeasure or estimate environmental impacts (e.g., energy and water consumption) for training, fine tuning, and deploying models: Verify tradeoffs between resources used at inference time versus additional resources required at training time.
2.2.1 Risk AssessmentVerify effectiveness of carbon capture or offset programs for GAI training and applications, and address green-washing concerns.
2.2.2 Testing & EvaluationLegal and regulatory requirements involving AI are understood, managed, and documented.
2.1.3 Policies & ProceduresLegal and regulatory requirements involving AI are understood, managed, and documented. > Align GAI development and use with applicable laws and regulations, including those related to data privacy, copyright and intellectual property law.
2.1.3 Policies & ProceduresThe characteristics of trustworthy AI are integrated into organizational policies, processes, procedures, and practices.
2.1.3 Policies & ProceduresThe characteristics of trustworthy AI are integrated into organizational policies, processes, procedures, and practices. > Establish transparency policies and processes for documenting the origin and history of training data and generated data for GAI applications to advance digital content transparency, while balancing the proprietary nature of training approaches.
2.1.3 Policies & ProceduresThe characteristics of trustworthy AI are integrated into organizational policies, processes, procedures, and practices. > Establish policies to evaluate risk-relevant capabilities of GAI and robustness of safety measures, both prior to deployment and on an ongoing basis, through internal and external evaluations.
2.1.3 Policies & ProceduresProcesses, procedures, and practices are in place to determine the needed level of risk management activities based on the organization’s risk tolerance.
2.1.3 Policies & ProceduresArtificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (NIST AI 600-1)
US National Institute of Standards and Technology (NIST) (2024)
This document is a cross-sectoral profile of and companion resource for the AI Risk Management Framework (AI RMF 1.0) for Generative AI, 1 pursuant to President Biden’s Executive Order (EO) 14110 on Safe, Secure, and Trustworthy Artificial Intelligence.2 The AI RMF was released in January 2023, and is intended for voluntary use and to improve the ability of organizations to incorporate trustworthiness considerations into the design, development, use, and evaluation of AI products, services, and systems.
Other (multiple stages)
Applies across multiple lifecycle stages
Other (multiple actors)
Applies across multiple actor types
Measure
Quantifying, testing, and monitoring identified AI risks
Primary
6.6 Environmental harm