Two-Track Robustness Templates for Legal AI Governance (Structure-Only, Non-Operational)

Key Points

• The research aims to define a framework for legal AI governance that ensures robustness and accountability.
• Developed structure-only templates for legal AI governance
• Implemented a one-prompt interface
• Outlined key principles: assumption discipline, fail-closed behavior, audit-ready outputs
• Created variants for different governance contexts such as big-law and multinational alliances.
• Established templates that do not provide legal advice or operational guidance
• Defined a framework emphasizing robustness and auditing capabilities
• Addressed governance needs across diverse legal AI contexts.