Quality Assurance and Reliability

Section 1: The Hallucination Problem

1.1 What Hallucination Is and Why It Happens

Hallucination is when an AI generates plausible-sounding but false information. For legal AI, this typically means:

• Fabricated case citations: "As established in Smith v. Jones, 456 F.2d 789 (5th Cir. 1998)" — case doesn't exist
• Misquoted statutes: Paraphrasing statutory language that's incorrect in actual law
• Wrong procedural rules: Confident claims about filing deadlines or requirements that don't match local rules
• Invented case facts: Assumptions about what a prior case held that actually said something different

1.2 The Scale of the Problem

Studies on Legal AI Hallucination Rates

Critical insight: Even leading models hallucinate on legal content at rates that create significant malpractice risk. Without proper controls, attorneys may unknowingly rely on fabricated citations or misinterpreted statutes. Professional-grade legal AI requires industry-leading accuracy standards that far exceed what generic consumer AI can deliver.

1.3 Real-World Malpractice Scenario

Attorney uses generic AI to draft probate petition:

• AI confidently states: "Florida Statute §733.504 requires service of the petition on all beneficiaries within 15 days of filing"
• Actual statute requires notice within 30 days and contains exceptions
• Attorney relies on AI and serves beneficiaries at 15 days
• Beneficiary claims improper notice; challenges estate administration
• Litigation costs: $15K-$30K; malpractice claim: $50K-$100K+

This is a hallucination creating legal liability.

1.4 Why Generic AI Hallucinstes on Legal Content

Large language models are trained on internet text, including:

• Outdated case summaries
• Non-authoritative legal blogs with errors
• Competing legal theories (not settled law)
• Multiple jurisdictions mixed together

The model learns patterns, not facts. It generates statistically likely text, not verified information.

Result: Models are excellent at language patterns but poor at legal accuracy without specialized training and verification.

Section 2: Professional-Grade QA Standards

2.1 Domain-Specific Validation Testing

Professional legal AI requires systematic testing against known-correct answers:

Test Suite Components

Statutory Accuracy Tests (100+ test cases)

• Florida Probate Code statute questions with verified answers
• Federal probate/trust code sections
• Guardianship statute accuracy
• Estate tax law questions

Probate Procedure Accuracy (50+ test cases)

• Filing requirements and deadlines
• Notice and service requirements
• Court filing procedures by jurisdiction
• Probate timeline accuracy

Case Law Verification (100+ test cases)

• Landmark probate cases (verified citations)
• Judicial interpretation questions
• Precedent-based reasoning
• Circuit split awareness

Estate Planning Scenarios (50+ test cases)

• Trust distribution disputes
• Capacity and undue influence questions
• Creditor claims and priority
• Tax planning accuracy

2.2 Confidence Scoring System

Professional legal AI should indicate confidence levels, not treat all statements equally:

Confidence Level Framework

Example output with confidence scoring:

Question: What notice period applies to creditor claims in Florida?

Answer: Florida Statute §733.702 requires notice of administration 
to creditors with known or reasonably ascertainable addresses.

[VERIFIED] - Citation confirmed against current Florida Statutes
[HIGH] - Consistent across Florida probate authority sources

Creditors have 3 months from publication of notice to file claims 
(§733.702(11)).

[HIGH] - Well-established timeline in Florida probate procedure

Note: Creditors in other states may have different notice requirements.
[MEDIUM] - Jurisdiction-specific; see choice of law analysis for details

2.3 Auditable Source Documentation

Attorneys must see where information comes from. Professional QA requires:

• Source citation: Every factual claim linked to source
• Training data provenance: What sources informed the model
• Verification method: How the system verified accuracy
• Exceptions/limitations: Known edge cases or exceptions noted
• Update frequency: When information was last verified

2.4 Continuous Regression Testing

Professional QA is ongoing, not one-time:

Testing Schedule

• Daily: Smoke tests on core functionality (basic statutory questions, procedure accuracy)
• Weekly: Regression tests on legal accuracy benchmarks (100+ test cases)
• Monthly: Full validation suite across all domains (300+ test cases)
• Quarterly: Probate-specific accuracy audit with attorney review
• Annually: Independent legal accuracy assessment by external attorneys

Failure thresholds are strict:

• Any regression in statutory accuracy triggers rollback
• New models tested extensively before production deployment
• Hallucination rates must remain at industry-leading levels through continuous validation

Section 3: Probate-Specific Accuracy Requirements

3.1 Why Probate Requires Extra Rigor

Probate law is extraordinarily nuanced:

• Jurisdiction-specific rules: Florida probate differs significantly from California, New York, federal rules
• Statutory interpretation challenges: Same statute word might mean different things in different contexts
• High-stakes consequences: Errors delay distributions, create liability, trigger litigation
• Client vulnerability: Executors/beneficiaries aren't lawyers; they depend on attorney accuracy

3.2 Florida Probate Accuracy Validation

AutoDrafter includes Florida-specific validation for:

Estate Administration Timeline

Probate Procedures Verified

• Petition for administration requirements and format
• Notice to creditors publication requirements
• Inventory filing requirements and timing
• Accounting requirements and review process
• Discharge petition procedures and final order
• Trust administration procedures under §736.0201 et seq.
• Guardianship specific procedures

3.3 Comparative Jurisdiction Accuracy

AutoDrafter includes accuracy testing for multiple jurisdictions:

• Federal probate rules: For bankruptcy-adjacent estates
• Other major states: California, New York, Texas procedures
• Multi-state issues: Choice of law, ancillary probate, non-resident executor rules
• Multi-jurisdictional estates: Tax implications of different estate locations

Section 4: Reliability Standards and Accountability

4.1 SLA (Service Level Agreement) for Accuracy

Professional platforms should guarantee reliability standards:

AutoDrafter Accuracy SLA

Statutory Citation Accuracy: 99%+

• All statutes cited verified against authoritative sources
• If citation error discovered, immediate notification and correction

Procedural Accuracy (Probate-Specific): 98%+

• All deadlines, filing requirements verified for Florida probate
• Quarterly independent attorney review

Case Law Accuracy: Industry-leading standards

• No fabricated cases in legal analysis
• All case citations verifiable
• Reasoning based on actual case holdings, not hallucinations
• Continuous validation ensures accuracy far exceeds generic AI tools

Jurisdiction-Specific Accuracy: 97%+ for stated jurisdiction

• Florida-specific rules accurate for Florida practice
• Clear labeling of jurisdiction-specific vs. general rules

4.2 Error Reporting and Remediation

When errors occur (because they inevitably will), professional platforms should:

• Detect errors: Continuous monitoring catches hallucinations
• Notify users: Immediate alert if documented error affects your work
• Document errors: Maintain audit trail of all corrections
• Improve models: Errors fed back to improve accuracy over time
• Accountability: Platform takes responsibility, not "use at your own risk"

4.3 Professional Liability and Insurance

Platforms confident in their accuracy carry professional liability insurance:

• Errors & Omissions insurance: Covers errors in legal AI output
• Professional indemnity: Platform stands behind accuracy claims
• Claims process: If your client is harmed by AI hallucination, platform covers legal defense

This demonstrates the platform's confidence in its quality assurance.

4.4 Auditable Decision Making

Attorneys must understand how the AI reached its conclusions:

What Professional QA Enables

• "Explain your reasoning": AI shows the chain of logic
• Source transparency: Attorney sees what the AI relied on
• Confidence levels: Attorney knows what to trust vs. verify
• Alternative analysis: AI suggests competing interpretations
• Exceptions noted: AI flags jurisdiction-specific exceptions

Result: Attorneys can verify the AI's work independently, not blindly trust it.

Section 5: Implementation and Testing Framework

5.1 Continuous Quality Monitoring

Professional QA requires infrastructure:

Monitoring Dashboard

• Daily metrics: Hallucination rate, statute accuracy, procedure accuracy
• Regression detection: If accuracy drops below threshold, automatic alert
• Error categorization: Tracks which types of errors are most common
• User feedback: Errors reported by users feed back into testing

5.2 Attorney-Driven Validation

No AI is perfect; the final check is human review:

Recommended attorney workflow:

1. AI drafts document with confidence scores visible
2. Attorney reviews HIGH/VERIFIED confidence sections lightly (spot check)
3. Attorney carefully reviews MEDIUM confidence sections (verify reasoning)
4. Attorney independently verifies LOW/UNCERTAIN confidence sections
5. Attorney adds their own analysis and judgment

This workflow balances speed (AI handles certain work) with accuracy (attorney verifies uncertain work).

5.3 Probate-Specific Best Practices

For estate administration documents specifically:

• Always verify deadlines: Use AI draft as starting point, verify against current statute
• Check jurisdiction rules: Confirm AI applied correct jurisdiction
• Verify procedural steps: Each step in probate process verified against statutory requirements
• Review accounting requirements: Probate accounting has specific format; verify compliance
• Check notices required: Different notice types (to beneficiaries, creditors, heirs) have different requirements

Conclusion: Professional Standards for Professional Practice

The Quality Assurance Imperative

Legal AI is not a novelty or convenience tool—it's a professional responsibility. When you use AI to draft documents, your professional obligations don't disappear. You're still liable for errors.

Professional-grade legal AI platforms recognize this. They implement rigorous QA, publish accuracy metrics, carry professional liability insurance, and enable auditable reasoning.

Anything less creates unacceptable malpractice risk.

Evaluating QA Standards

When selecting a legal AI platform, ask:

• What is your hallucination rate on legal content? (Should demonstrate industry-leading accuracy through rigorous testing)
• How do you test accuracy? (Should have 300+ test cases, weekly regression testing)
• What are your SLA guarantees? (Should specify accuracy %, consequences of failure)
• How do you verify probate-specific rules? (Should have jurisdiction-specific testing)
• Do you carry professional liability insurance? (Yes = confidence in QA; No = risk for you)
• Can users see confidence scores? (Should be visible for all statements)
• How do you handle discovered errors? (Immediate notification, correction, user compensation)

The AutoDrafter Commitment

AutoDrafter's QA standards reflect professional accountability:

We don't disclaim responsibility. We own our accuracy. We test rigorously. We notify users of errors. We carry liability insurance. We enable attorneys to verify our work.

This is what professional-grade legal AI looks like: reliable, verifiable, accountable, and safe for client work.

Anything less shouldn't be used on client files.