The Bharat Pacific Principles
The Prayagraj Principles on Responsible and Accessible Legal Automation Technologies [The Prayagraj AI Principles]
April 30, 2025 | Version 1
Imperative Classification as per AiStandard.io Alliance Charter, Schedule 1, Part B
Miscellaneous Standard [Legal: Universal legal principles]
Stakeholder-attribution as per AiStandard.io Alliance Charter, Schedule 1, Part C
Government: [Judicial Institutions: Principles 1, 3, 4, 6, 7] [Central Government Ministries/Departments: Principles 1, 2, 5, 7] [Constitutional Bodies: Principles 3, 6] [Regulatory Bodies: Principles 4, 5, 7]
Communities: [Open-Source Communities: Principles 2, 7] [Legal Experts: Principles 1, 3, 4, 5, 7] [Digital Rights Groups: Principles 2, 5, 6] [Capacity Building Networks: Principles 2, 7]
Organisations: [Startups: Principles 1, 2, 5, 7] [Technology Providers: Principles 1, 2, 4, 5, 7] [Non-Profit Organisations: Principles 2, 6] [Educational Institutions: Principles 2, 7]
full text of Principles
Algorithmic Reasoning Transparency: Legal automation technologies must provide clear, auditable explanations of their reasoning processes in language accessible to both legal professionals and laypeople, allowing users to understand the basis for automated conclusions without requiring technical expertise.
Access to Justice Enhancement: Legal automation technologies must be deliberately engineered to reduce barriers to legal services for underserved populations, with interfaces designed for varying literacy levels and deployment models that reach resource-constrained environments and eliminating the errors with full accurate standards of outputs without eradicating the original works..
Evidentiary Chain Integrity: Automated legal systems must maintain comprehensive audit trails documenting every source relied upon accurately, ensuring provenance verification of all legal authorities cited, with particular attention to maintaining the distinction between binding precedent, persuasive authority, and non-authoritative sources.
Autonomous Competence Boundaries: Legal automation technologies must be designed to recognize their operational limitations, providing clear signals when encountering legal questions beyond their reliability threshold, preventing domain encroachment into domains requiring human jurisprudential judgment. and preventing ambiguity or any kind of error in the comprehension of the human mind which may or may not be inclined with the perspective and maybe subjective to more nuanced approach yet simplistic.
Meaningful Contestability Architecture: Legal systems that incorporate automation must offer meaningful challenge mechanisms, enabling affected parties to contest automated decisions through clear processes. Remedial pathways should be proportionate to potential harms and accessible to everyone, regardless of their technical skills..
Proportional Human Engagement: Legal automation deployment must permit human involvement proportionate to the gravity, complexity, and potential consequences of the legal matter, rather than treating human oversight as a binary compliance checkbox or liability shield.
Authorised Knowledge Interoperability: Legal automation technologies must respect intellectual property considerations in legal knowledge bases while enabling appropriate access to public legal resources, incorporating standardised API frameworks for accessing judicial and statutory databases that balance open access principles with document integrity requirements.