AI in Class Action Defense: Document Review at Scale

End-of-lesson check

15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-legal-AI-class-action-defense-adults

1. In a class action document review, what fundamental challenge makes AI-assisted review necessary?

   1. Opposing counsel demands faster turnaround times than human reviewers can achieve
   2. The volume of documents exceeds what manual review teams can process within litigation timelines
   3. Class action rules require automated document processing without attorney involvement
   4. AI produces more legally accurate privilege determinations than experienced attorneys

2. What must a legal team establish BEFORE deploying AI for document review in a class action?

   1. A budget approval from the court for AI technology costs
   2. A statistical model predicting document relevance scores
   3. A list of all documents the AI will likely categorize as privileged
   4. A written protocol outlining the review methodology and validation procedures

3. What is the purpose of using a control set when validating AI document review accuracy?

   1. To provide a benchmark for measuring AI accuracy against human-reviewed documents
   2. To train the AI on which documents contain privileged content
   3. To generate statistical samples for court reporting requirements
   4. To create a secondary review team that checks the AI's work in real-time

4. Why must privilege review be conducted through a separate workflow from the main document review?

   1. Maintaining separation preserves privilege protections and prevents inadvertent disclosure of privileged materials
   2. Separation is required by federal court rules for all litigation
   3. Privilege review requires different technical skills than responsiveness coding
   4. AI cannot properly identify privileged documents, so human attorneys must handle all privilege matters separately

5. What is the primary purpose of maintaining an audit trail for production decisions in AI-assisted review?

   1. To track billable hours for client invoicing
   2. To allow the AI system to learn from past production mistakes
   3. To comply with federal data retention requirements
   4. To provide a defensible record if opposing counsel challenges the review methodology

6. What does it mean for an AI document review methodology to be 'defensible'?

   1. The methodology produces results that match what human reviewers would have found in every case
   2. The methodology uses only court-approved AI software platforms
   3. The methodology can withstand legal challenge because it was properly documented, validated, and applied consistently
   4. The methodology guarantees that no privileged documents will be inadvertently produced

7. In the context of AI document review, what is a 'seed set'?

   1. A small collection of documents manually reviewed by attorneys to train the AI on relevance criteria
   2. A database of all previously decided privilege determinations from prior class actions
   3. A statistical sample of documents submitted to the court for in camera review
   4. The initial group of documents produced to opposing counsel at the start of discovery

8. Why is accuracy validation performed separately for each responsiveness category rather than using one overall accuracy metric?

   1. Court rules require separate reporting for each document category
   2. This approach is more efficient because the AI learns each category faster
   3. Single overall metrics are not available in current AI software
   4. Different categories have different legal consequences requiring category-specific accuracy standards

9. What is the 'meet-and-confer' obligation regarding AI methodology in class action discovery?

   1. A requirement to meet with the AI vendor and discuss technical specifications
   2. A requirement to disclose AI review methodology to opposing counsel during discovery conferences
   3. A requirement for attorneys to meet with each other before using any AI tools
   4. A court requirement to confer with the judge before deploying AI in document review

10. What happens when AI methodology is not properly documented in a class action document review?

    1. The AI system becomes legally liable for any errors
    2. The statute of limitations for challenging the review is extended
    3. The review may be vulnerable to successful challenges from opposing counsel regarding the reliability of document categorization
    4. The court automatically rules in favor of the opposing party

11. What does 'contemporaneous documentation' mean in the context of AI document review protocols?

    1. Creating documentation after the review is complete to support any future legal challenges
    2. Documenting only the final production set of documents for court submission
    3. Recording protocols and decisions as they happen, not retroactively reconstructing the process
    4. Writing detailed descriptions of each AI-generated relevance score

12. Which of the following represents a core limitation of AI in class action document review?

    1. AI cannot substitute for attorney privilege review
    2. AI can reliably determine privilege without attorney involvement
    3. AI reduces litigation costs to near zero when deployed properly
    4. AI can review documents faster than any team of human attorneys

13. Why do class action courts increasingly scrutinize AI review methodology?

    1. Courts are generally skeptical of all technology used in litigation
    2. AI review involves high stakes where errors can affect large groups of people and significant damages
    3. Courts want to reduce their own workload by automating document review
    4. Class action defendants have successfully argued that AI review should be banned

14. What should a legal team do when the AI's accuracy on a control set falls below acceptable thresholds for a particular responsiveness category?

    1. Automatically classify all documents in that category as non-responsive
    2. Submit the low accuracy results to the court for guidance
    3. Adjust the AI model or re-train with additional seed documents until accuracy improves
    4. Continue with the review using the current AI settings

15. What is the relationship between AI-assisted review and the traditional attorney-driven privilege review?

    1. Attorneys and AI share equal responsibility for privilege determinations under court rules
    2. AI assists with the review but attorneys must still conduct privilege review to maintain legal protection
    3. AI has completely replaced traditional privilege review in most class actions
    4. AI privilege review results are binding without attorney sign-off