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Navigating the Risks of Generative AI: A Comprehensive Guide to the NIST AI Risk Management Framework

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This document serves as a companion resource to the AI Risk Management Framework, focusing on the unique risks associated with Generative AI (GAI). It outlines specific risks, actions for management, and insights for organizations to align their risk management strategies with GAI's capabilities and challenges.
  • main points
  • unique insights
  • practical applications
  • key topics
  • key insights
  • learning outcomes

  • • main points

    • 1
      Comprehensive identification of unique risks associated with Generative AI.
    • 2
      Practical actions and strategies for organizations to manage GAI risks.
    • 3
      Informed by diverse stakeholder feedback, enhancing credibility and relevance.

  • • unique insights

    • 1
      Detailed analysis of risks like confabulation and data privacy specific to GAI.
    • 2
      Cross-sectoral applicability of the risk management framework for various industries.

  • • practical applications

    • The article provides actionable insights for organizations to effectively manage GAI-related risks, making it a valuable resource for risk management professionals.

  • • key topics

    • 1
      Generative AI risks
    • 2
      Risk management strategies
    • 3
      Cross-sectoral applications of AI RMF

  • • key insights

    • 1
      Focus on the novel risks posed by Generative AI.
    • 2
      Guidance on aligning risk management with organizational goals.
    • 3
      Incorporation of public feedback to enhance framework relevance.

  • • learning outcomes

    • 1
      Identify unique risks associated with Generative AI.
    • 2
      Implement effective risk management strategies aligned with organizational goals.
    • 3
      Understand the implications of GAI on various sectors.
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“ 1. Introduction

Generative AI introduces risks that differ from traditional software risks, exacerbating existing challenges while creating new ones. These risks can manifest at various stages of the AI lifecycle and may have significant societal impacts. Organizations must understand how these risks evolve and allocate resources accordingly.

“ 3. Key Risks Associated with GAI

Organizations are encouraged to implement specific actions to mitigate GAI risks. This includes: - Developing a glossary of terms relevant to GAI. - Categorizing identified risks to enhance understanding and management. - Establishing protocols for monitoring and evaluating risks associated with GAI applications. - Engaging with stakeholders for feedback and continuous improvement.

 Original link: https://airc.nist.gov/docs/NIST.AI.600-1.GenAI-Profile.ipd.pdf

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