Averting Framework Fatigue in AI Governance [IPLR-IG-013]

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Description

This report addresses the critical challenge of “framework fatigue” in AI governance, where the rapid proliferation of ethical guidelines, policy documents, and industry standards has created decision-making paralysis across sectors. It combines theoretical analysis with practical tools to help stakeholders prioritise effectively.

Chapter Breakdown

  1. AI Ethics & Governance 101
    A foundational primer for product managers, technical professionals, and enterprises, explaining core concepts like algorithmic accountability, bias mitigation, and regulatory compliance.
  2. The Overload of AI Frameworks
    Examines six distinct forms of decision paralysis caused by competing frameworks in law, ethics, marketing, and policy. Examples include conflicting compliance requirements and divergent ethical priorities.
  3. Timeline of AI Framework Overload (2023–2025)
    A curated chronology of major AI policy developments, including legislative milestones, industry standards, and ethical guidelines, contextualizing how systemic overload emerged.
  4. From Paralysis to Priorities
    Provides sample exercises to help organizations:

    • Identify mission-critical governance areas
    • Align frameworks with operational goals
    • Develop simplified, actionable roadmaps
  5. Conclusion & Recommendations
    Advocates for sector-specific prioritization matrices, collaborative policymaking, and dynamic governance models adaptable to technological shifts.

Acknowledgments
The report acknowledges Ayushi Agarwal (42.ai) for her motivational support and conceptual contributions.

Context
Developed for a workshop on “Framework Fatigue in AI Governance” (February 1, 2025, Hyderabad), this document references global publications, legal opinions, and industry practices to ground its analysis.

Audience: Policymakers, corporate legal teams, AI ethicists, and tech leaders navigating multijurisdictional compliance and ethical challenges.

Additional information

VLiGTA Resource Identifier

IPLR-IG-013

ISBN/ISSN

Author(s)

Publisher

Publication Type

Digital

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