AI Risk Management Framework | NIST
The NIST AI Risk Management Framework (AI RMF) is intended for voluntary use and to improve the ability to incorporate trustworthiness considerations into the design, development, use, and evaluation of AI products, services, and systems.
Risk Management in AI | IBM
2024年6月20日 · AI risk management is the process of systematically identifying, mitigating and addressing the potential risks associated with AI technologies. It involves a combination of tools, practices and principles, with a particular emphasis on deploying formal AI …
AI risk management is a key component of responsible development and use of AI sys-tems. Responsible AI practices can help align the decisions about AI system design, de-velopment, and uses with intended aim and values. Core concepts in responsible AI em-phasize human centricity, social responsibility, and sustainability. AI risk management can
ISO/IEC 23894:2023 - AI — Guidance on risk management
This document provides guidance on how organizations that develop, produce, deploy or use products, systems and services that utilize artificial intelligence (AI) can manage risk specifically related to AI. The guidance also aims to assist organizations to integrate risk management into their AI-related activities and functions.
To achieve a strong AI governance and risk management, it is crucial to establish multiple security layers when deploying AI programs. The three Lines of Defence (3LoD) model is a fundamental framework that delineates three integral layers of defence, each with unique
AI RMF profiles assist organizations in deciding how to best manage AI risks in a manner that is well-aligned with their goals, considers legal/regulatory requirements and best practices, and reflects risk management priorities.
HITRUST AI Risk Management Program Overview
2 天之前 · The core element of compliance with the HITRUST AI Risk Management Framework (AI RMF) is the implementation of a comprehensive, risk-based approach to managing AI-related risks. To comply with the HITRUST AI Risk Management Program, companies need to take some essential steps: Build a Strong AI Risk Management Strategy. Start by identifying and ...
Derisking AI: Risk management in AI development | McKinsey
2020年8月13日 · Risk management by design allows developers and their business stakeholders to build AI models that are consistent with the company’s values and risk appetite. Tools such as model interpretability, bias detection, and performance monitoring are built in so that oversight is constant and concurrent with AI development activities and consistent ...
NIST AI RMF Playbook | NIST - National Institute of Standards …
2022年7月8日 · In collaboration with the private and public sectors, NIST has created a companion AI RMF playbook for voluntary use – which suggests ways to navigate and use the AI Risk Management Framework (AI RMF) to incorporate trustworthiness considerations in the design, development, deployment, and use of AI systems.
NIST developed the voluntary NIST AI Risk Management Framework (AI RMF) to help individuals, organizations, and society manage AI’s many risks and promote trustworthy development and responsible use of AI systems. NIST was directed to prepare the Framework by the National Artificial Intelligence Initiative Act of 2020 (P.L.116-283).
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