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HBR: AI risk management needs collective team wisdom
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The rise of generative AI presents organizations with both unprecedented opportunities and significant challenges in implementing this transformative technology safely and effectively.

Current risk management landscape: Most organizations have implemented basic risk mitigation strategies for generative AI through policies and critical thinking protocols.

  • Companies typically rely on formal usage guidelines and individual assessment of AI outputs
  • These traditional approaches, while necessary, may not be sufficient given the complex and evolving nature of AI technology
  • Organizations need more robust frameworks to address AI-related challenges including accuracy issues, hallucinations, and inherited biases

The team-based judgment framework: A third layer of risk management emphasizing collective decision-making and expertise offers a more comprehensive approach to AI governance.

  • Collective judgment involves team discussions to evaluate AI outputs and ensure accuracy through multiple perspectives
  • Domain judgment leverages specific expertise by delegating AI-related decisions to team members with relevant knowledge or proximity to the work
  • Reflective judgment requires regular team meetings to share experiences and lessons learned from AI implementation

Implementation considerations: Successfully deploying team-based judgment requires thoughtful organizational structure and commitment.

  • Teams must establish regular communication channels and feedback loops
  • Organizations should clearly define roles and responsibilities for AI oversight
  • Regular assessment and adaptation of the framework ensures continued effectiveness as AI technology evolves

Benefits and outcomes: Organizations that successfully implement team-based judgment can expect improved AI risk management and better adaptation to technological change.

  • Enhanced accuracy and reliability of AI outputs through collective verification
  • Better alignment between AI applications and business objectives
  • Increased organizational learning and knowledge sharing about AI implementation
  • Improved ability to identify and address potential AI risks before they materialize

Looking ahead: As generative AI continues to evolve rapidly, organizations that develop robust team-based judgment capabilities will be better positioned to navigate future challenges and opportunities.

  • The collective intelligence approach provides a more resilient framework for managing unknown future risks
  • Organizations can build on existing team structures to create more sophisticated AI governance systems
  • Regular reflection and adaptation will remain crucial as AI technology and its applications continue to advance
To Mitigate Gen AI’s Risks, Draw on Your Team’s Collective Judgment

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