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AI - GENERATEDDOCUMENTS · A GUIDE FOR UK LAWYERS AI-Generated Documents: Provenance and Detection Fabricated Evidence, Invented Citations and the Return to Provenance COMPUTER FORENSICS LAB
§ ABOUT THE AUTHOR PREPARED BY COMPUTER FORENSICS LAB E-DISCOVERY TEAM ESTABLISHED 2007 · LONDON ISO 17025-ALIGNED PROCEDURES DOCUMENT PROVENANCE ANALYSIS
§ CONTENTS In this guide 01 Executive summary 02 The problem in plain English: plausible text is cheap now 03 How AI-generated and AI-assisted documents arise 04 Why text-based detection is weak 05 Provenance: the forensic answer 06 Metadata, corroboration and honest limits 07 Deployment: fabrication, hallucinated citations and duties 08 Source architecture: where else the evidence lives 09 Worked examples 10 Common mistakes and technical limitations 11 Questions to ask · Suggested wording 12 Checklist and red flags · When to involve a digital forensic expert 13 Frequently asked questions 14 Glossary · References · Disclaimer · How a specialist laboratory can assist
§ 01 · ORIENTATION Executive summary The headline point: AI can now fabricate a plausible document in seconds, but detecting AI from the text alone is unreliable, so the forensic answer is not a detector but provenance: where the document actually came support its claimed origin.
§ 02 · FIRST PRINCIPLES The problem in plain English: plausible text is cheap now
§ 03 · HOWTHEYARISE How AI-generated and AI-assisted documents arise
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§ 04 · WHYTEXTDETECTIONISWEAK Why text-based detection is weak
§ 05 · PROVENANCE Provenance: the forensic answer
§ 06 · METADATAANDHONESTLIMITS Metadata, corroboration and honest limits
§ 07 · DEPLOYMENT Deployment: fabrication, hallucinated citations and duties
§ 08 · THEWIDERMAP Source architecture: where else the evidence lives CORROBORATING RECIPIENT / SERVER / BACKUPS / APPLICATION / SOURCE COUNTERPART CLOUD VERSIONS DATABASE THE SENDER / DOCUMENT AUTHOR ITSELF SYSTEM
§ 09 · IN THE WILD Worked examples EXAMPLE1 · THEEMAILTHATEXISTEDONLYASAFILE EXAMPLE2 · THESUBMISSIONWITHAUTHORITIESTHATDIDNOTEXIST EXAMPLE3 · THEGENUINEDOCUMENTDEFENDEDBYITSPROVENANCE
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§ 10 · WHEREITGOESWRONG Common mistakes and technical limitations Common mistakes Technical limitations
§ 11 · INTERROGATORIES & DRAFTING AIDS Questions to ask · Suggested wording Ask your client Ask your opponent Ask your e Discovery / forensic provider SUGGESTED WORDING · INSTRUCTION FOR A DOCUMENT- PR OV ENANCEEXAMIN AT ION
§ 12 · QUICK CONTROL Checklist and red flags · When to involve a digital forensic expert The provenance checklist Red flags When to involve a digital forensic expert
§ 13 · COMMON QUESTIONS Frequently asked questions Can you tell if a document was written by AI? How do you prove a document is fabricated? Why do we need the native file and not a printout? Our opponent's submissions cite cases we cannot find. What does that mean? Can metadata itself be faked? Is using AI to draft documents a problem in itself?
§ 14 · REFERENCE Glossary Sources and authoritative references 19 reporting): cflab.uk/digital-forensics-services · guides library: cflab.uk/guides DISCLAIMER
§ HOW A SPECIALIST LABORATORY CAN ASSIST Working with Computer Forensics Lab Speak to a forensic examiner, not a salesperson. INSTRUCTTHELAB NEWENQUIRIESEMAILE - DISCOVERY
Cite as: Joseph Naghdi, AI Generated Documents Provenance And Detection, Computer Forensics Lab, https://e-discovery.uk/library/ai-generated-documents-provenance-and-detection/pdf.