Legal Ethics Map
ActiveQuestion: What professional duties are triggered when lawyers use generative AI?
competence · confidentiality · candor · supervision · billing
Output: issue map + checklist
View mapAI-Law Research Atlas
Map an AI legal issue across law, jurisdiction, ethics, contracts, and risk.
Aidicia organizes AI-law developments into searchable issues, source types, jurisdictions, risk maps, and legal-research pathways.
Educational research only · Source-grounded summaries · Last-reviewed dates · No legal advice
Research console
Legal layer map
Choose the starting point
Navigate by fact pattern, jurisdiction, or legal domain.
Start with a fact pattern
Start with a jurisdiction
Start with a legal domain
AI law is a layered problem
Most AI-law questions are not only federal or state. They often involve overlapping law, ethics, procedure, contracts, data, and product risk.
Legal stack
- 1Federal law and agencies
- 2State AI-specific laws
- 3Existing state privacy, employment, and consumer law
- 4Court rules and filing orders
- 5Bar ethics and professional responsibility
- 6Vendor contracts and data rights
- 7Evidence, authentication, and litigation procedure
- 8International and comparative pressure
Example issue
Law firm uses an AI tool to summarize client documents.
One fact pattern can trigger multiple overlapping legal layers:
Bar ethics
confidentialitycompetencesupervision
Court rules
AI disclosurecitation verification
Vendor contract
data retentiontraining rights
Privacy/data
client informationsecurity
Malpractice risk
relianceverification
Billing
reasonablenessdisclosure
Research maps
Structured issue maps for understanding where AI-law risk tends to cluster.
Vendor Contract Map
ActiveQuestion: Which AI vendor clauses create the highest legal exposure?
data use · training · indemnity · liability · retention
Output: clause-level risk map
View mapFederal/State Map
DevelopingQuestion: How do federal and state AI-law layers apply to the same feature?
agencies · statutes · privacy overlays · ethics
Output: jurisdiction sorting framework
View mapAI Hiring Map
DevelopingQuestion: What employment-law risks attach to AI-assisted screening?
EEOC · state hiring AI · vendor audits · notice
Output: employment risk map
View mapCourt Rules Map
ActiveQuestion: What AI disclosure rules apply in litigation filings?
standing orders · local rules · certification
Output: court rules tracker
View mapEvidence/Deepfake Map
DevelopingQuestion: How should parties authenticate AI-generated evidence?
evidence rules · forensics · discovery · deepfakes
Output: authentication issue map
View mapLatest research
Research notes, issue maps, and practical explainers on AI law.
articleLegal Ethics
United States · Legal Ethics
Why Law Firms Need an Internal AI Use Policy
Takeaway: A practical overview of why firms need internal rules before using generative AI with client work.
Updated 2026-06-07Reviewed 2026-06-07Review: Fresh3 sources tracked
Read analysisarticleContracts
United States · Contracts
AI Vendor Contracts: Clauses Lawyers Should Review First
Takeaway: A structured review framework for high-risk clauses in AI vendor agreements.
Updated 2026-06-05Reviewed 2026-06-05Review: Fresh3 sources tracked
Read analysisarticleGovernance
United States · Governance
Federal vs State AI Law: How to Sort the Layers
Takeaway: A jurisdiction-layer framework for sorting federal, state, and ethics rules that apply to AI systems.
Updated 2026-06-03Reviewed 2026-06-03Review: Fresh3 sources tracked
Read analysisTrackers and toolkits
Live research categories and educational checklists for AI-law issue spotting.
Research systems behind Aidicia
Knowledge-management workflows supporting source tracking, update monitoring, and structured research.
Source dependency model
plannedLinks articles to the authorities they rely on for update monitoring.
ViewArticle staleness review
prototypePrototype workflow for review dates and re-review flags.
ViewJurisdiction tagging
portfolio systemInternal research workflow for federal, state, and court-layer sorting.
ViewClaim/source registry
internal research workflowTracks which public summaries depend on which source types.
ViewFuture source-grounded assistant
plannedPlanned retrieval-limited research assistant — not open-ended generation.
ViewResearch standards
portfolio systemCitation-first discipline, review dates, and transparent educational limits.
ViewResearch standards
Because AI law changes fast, Aidicia is designed around careful sourcing, update dates, and transparent limits.
Educational onlyNo legal adviceNo fake citationsSource verificationLast-reviewed datesFast-moving topics flagged
About the project
Aidicia is built by Muhammad Tariq, a JD Candidate developing a focused research portfolio in AI law, legal ethics, governance, and practical legal-risk analysis. The project is designed to demonstrate structured legal research, issue spotting, source verification, and legal-technology systems thinking.
Start with an AI-law question.
Search by issue, jurisdiction, source type, or legal domain.