A tested strategy for AI-drafted interrogatories

 A strategy for AI-drafted interrogatories

1. Create a PDF file containing the relevant court rules relating to discovery and interrogatories. In federal court, that would include the general rules of discovery and mandatory disclosures in FRCP Rule 26, the specific interrogatory rules of FRCP 33, and any relevant local rules. 

2. Make copies of your case's complaint and answer PDF files, as amended. Place the copies in a working folder.

3. Create a PDF file containing a brief description of the essential legal elements for each of the plaintiff's COA and the defendant's affirmative defenses. Include on-point excerpts from relevant court decisions.  The objective is to provide the AI chatbot an accurate working guide to the applicable legal and evidentiary issues. Pattern jury instructions are a good source to use if available.

4. Copy my "GENERAL INSTRUCTIONS.PDF" and "CONSIDERATIONS.PDF" to your working folder.

5. Combine all of these files into a single PDF file named "DIRECTIONS.PDF"

This combined file PDF will be uploaded as an attachment to your chatbot prompt.

Enter the following PROMPT:

temperature = 0

Assume the role of experienced senior law clerk and follow the instructions in the attached file "DIRECTIONS.PDF." Draft 30 rule-compliant interrogatories for use as discovery in the pending litigation arising from the Complaint and Answer contained in the DIRECTIONS.PDF file.

Assume the enclosed statement of applicable legal principles is correct and authoritative for this jurisdiction. Write in a clear, concise, unambiguous, and professional business style without legalese or jargon. If you have any questions or uncertainty, please pause and ask for clarification.

When referencing the plaintiff or defendant, also include their proper name. Example: "Plaintiff, John Doe" or "Defendant XYZ, Inc." 

-- oOo --

Generated output using Claude - Raw & Unedited

Jeanne Flieger V. Eastern Suffolk Board Of Cooperational Educational Services Docket No. 13-CV-6282 (EDNY 2013)

1. Identify all witnesses not previously disclosed pursuant to FRCP Rule 26(a)(1)(A)(i) who have knowledge of the facts and circumstances surrounding Plaintiff Jeanne Flieger's employment, disabilities, requests for accommodation, the interactive process between the parties, and termination of Plaintiff Flieger's employment, as well as the defenses and denials of Defendant Eastern Suffolk Board of Cooperative Educational Services ("BOCES"). For each witness, provide their full name, job title, last known address, and last known phone number, as well as a brief summary of their knowledge related to this case.

2. Identify all documents, electronically stored information, and tangible things not previously produced that relate to Plaintiff Flieger's employment, disabilities, requests for accommodation, the interactive process, termination of employment, or Defendant BOCES's defenses and denials. For each, state the date, author, recipients, subject matter, and current location.

3. State all reasons why Defendant BOCES contends Plaintiff Flieger was not a "qualified individual" under the ADA, identifying any "direct threat" Defendant BOCES alleges Plaintiff Flieger posed and the basis for that contention.

4. Describe in detail the "essential functions" of Plaintiff Flieger's job as a Teaching Assistant that Defendant BOCES contends Plaintiff Flieger could not perform with or without reasonable accommodation.

5. State the date(s) when Defendant BOCES first became aware of Plaintiff Flieger's disabilities and her need for accommodation related to those disabilities.

6. Identify each request for reasonable accommodation made by Plaintiff Flieger, including the date of each request, how it was conveyed to Defendant BOCES, and Defendant BOCES's response.

7. For each request for accommodation identified in response to the preceding interrogatory, state whether Defendant BOCES deemed the requested accommodation reasonable and the basis for that determination.

8. Describe all steps taken by Defendant BOCES to engage in the interactive process with Plaintiff Flieger to identify potential reasonable accommodations.

9. Identify each potential reasonable accommodation, if any, that Defendant BOCES considered or discussed for Plaintiff Flieger, as well as the basis for determining whether each potential accommodation was reasonable.

10. If Defendant BOCES contends that reassignment to a vacant position was not a reasonable accommodation for Plaintiff Flieger, state all reasons for that contention, identifying each vacant position that existed when Plaintiff Flieger requested accommodation.

11. If Defendant BOCES contends that reallocating or redistributing marginal job functions was not a reasonable accommodation, identify the specific job functions at issue and explain why reallocating or redistributing those functions was not reasonable.

12. If Defendant BOCES contends that modifying Plaintiff Flieger's work schedule was not a reasonable accommodation, identify the requested schedule modification and explain why it was not reasonable under the circumstances.

13. Identify any accommodations offered by Defendant BOCES to Plaintiff Flieger and state whether Plaintiff Flieger accepted or rejected each offered accommodation.

14. If Defendant BOCES claims that providing the accommodation(s) requested by Plaintiff Flieger would have caused an undue hardship, describe the proposed accommodation(s) and the specific undue hardship it would have caused to Defendant BOCES's operations.

15. Identify and describe in detail Defendant BOCES's policies, practices and procedures in effect from 2010 to present regarding requesting, considering, and providing reasonable accommodations under the ADA.

16. State whether Defendant BOCES had a procedure in place from 2010 to present that an employee was required to follow to request an accommodation for a disability, and if so, describe that procedure in detail.

17. Identify by name, title and dates of employment all employees of Defendant BOCES responsible for administering, implementing or making decisions regarding reasonable accommodation requests under the ADA from 2010 to present.

18. Describe any training provided to Defendant BOCES's management and supervisory personnel from 2010 to present regarding responsibilities and obligations under the ADA for providing reasonable accommodations.

19. Identify all other employees of Defendant BOCES from 2010 to present who requested accommodations for disabilities and state whether each request was granted or denied, as well as the accommodation requested.

20. State the date Plaintiff Flieger's employment ended with Defendant BOCES, whether she resigned, was terminated, or separated through some other means, and the reason(s) for the separation.

21. If Plaintiff Flieger's employment was terminated, identify the person(s) who made the decision to terminate and the stated reason(s) for termination at the time it occurred.

22. If Defendant BOCES claims Plaintiff Flieger did not experience an adverse employment action because of her disability, state in detail all reasons for this contention.

23. If Defendant BOCES claims Plaintiff Flieger's alleged disability did not substantially limit a major life activity, state the basis for this claim and identify the specific major life activities that Defendant BOCES alleges were not substantially limited.

24. If Defendant BOCES claims Plaintiff Flieger did not have a disability covered by the ADA, state in detail all reasons for this contention.

25. If Defendant BOCES claims Plaintiff Flieger failed to mitigate her damages, identify all potential comparable employment opportunities that Defendant BOCES alleges Plaintiff Flieger failed to pursue.

26. State whether Defendant BOCES has an in force disability anti-discrimination policy and if so, describe the policy and identify any personnel responsible for its implementation and enforcement.

27. If Defendant BOCES had knowledge of any potential discrimination or failure to accommodate Plaintiff Flieger because of her disabilities, describe the information or circumstances that provided Defendant BOCES such knowledge.

28. Identify any complaints, whether informal or formal, made by Plaintiff Flieger or other employees to Defendant BOCES regarding disability discrimination or failure to accommodate prior to the events giving rise to this lawsuit.

29. Identify any disciplinary actions or performance issues related to Plaintiff Flieger's attendance, conduct or work performance prior to her requests for accommodation.

30. State the amount of alleged damages, including any claims for lost wages, benefits, emotional distress or other compensatory damages, that Plaintiff Flieger claims and describe how the amount was calculated.

 

The Centaur as a Modern Lawyering Metaphor

 The Centaur as a Modern Lawyering Metaphor

The Mythological Centaur As A Modern Metaphor For The Relation Between Lawyers And Artificial Intelligence Technology

The mythological centaur, a creature from Greek mythology that combines the upper body of a human with the lower body and legs of a horse, offers a vivid metaphor for the relationship between lawyers and artificial intelligence (AI) technology in the modern era. This metaphor can be dissected into several layers, each illustrating aspects of this evolving relationship.

The concept of "Centaur lawyering" refers to a hybrid approach to legal practice that integrates human expertise with artificial intelligence (AI) and technology. This term draws on the metaphor of a centaur, a mythical creature with the upper body of a human and the lower body of a horse, symbolizing the combination of human intuition and judgment with the speed and data-processing capabilities of AI.

Integration of Two Distinct Natures

The centaur is neither fully human nor entirely horse, yet it embodies characteristics of both, suggesting a seamless integration of two very different natures. Similarly, in the legal profession, AI integrates with the distinctly human skills of lawyers. AI efficiently handles data-driven tasks such as document review, legal research, and case prediction, while the human lawyer provides judgment, ethical oversight, and client interaction. This hybrid model suggests that the most effective use of AI in law is not a replacement for human lawyers but an enhancement of their capabilities.

Balance of Strengths

The horse part of the centaur symbolizes strength, speed, and endurance, qualities that can be likened to the computational power, speed of data processing, and capacity for handling vast amounts of information that AI brings to the legal field. The human part symbolizes intelligence, reasoning, and moral considerations, reflecting lawyers' skills in critical thinking, argumentation, and ethical judgment. The centaur metaphor underscores the idea that the optimal use of AI in law finds a balance between these strengths, leveraging technology to handle large-scale, repetitive tasks while reserving uniquely human capabilities for strategy and decision-making.

Navigational Dexterity

Ancient stories often depict centaurs as creatures of great agility, able to navigate difficult terrain with ease. This characteristic can be translated into the legal landscape, where AI helps lawyers navigate complex legal databases, process intricate legal precedents, and analyze patterns in case law that might elude a human researcher. However, just as a centaur must learn to balance its dual nature to move gracefully, lawyers must learn to integrate AI tools into their practice effectively, ensuring that they complement rather than complicate their workflow.

Ethical and Control Dilemmas

Centaurs in mythology sometimes struggled to control their animalistic instincts. This issue of control is a metaphor for the ethical and control dilemmas presented by AI in law. As AI systems become more advanced, bias, transparency, and accountability issues arise. Lawyers, representing the human part of the centaur, must guide and control the use of AI to ensure that it adheres to ethical standards and does not perpetuate biases or make opaque decisions.

Conclusion

The centaur metaphor richly encapsulates lawyers' and AI technology's dynamic and dualistic relationship. It illustrates an integrated model where the human and technological components play to their strengths and contribute to a more efficient and effective legal practice. The balance and interaction between these elements highlight the potential enhancements AI offers to the legal field and the critical human oversight necessary to harness this technology responsibly.

Key Takeaways:

AI and lawyers should function in an integrated, complementary manner.

Effective use of AI in law balances computational power with human judgment and ethical considerations.

Lawyers must navigate ethical and operational challenges in implementing AI.

The metaphor suggests a dynamic, evolving relationship that, when managed well, enhances the capabilities and effectiveness of the legal profession.

AI Prompt engineering or instruction tuning for legal applications

Prompt engineering or instruction tuning for legal applications like litigation, legal research, and document drafting involves carefully crafting prompts to guide large language models (LLMs) in generating relevant and accurate outputs

Here are some practical methods:

Defining Clear Objectives

Specify the precise task or goal you want the LLM to accomplish, such as summarizing case law, analyzing contracts, or drafting legal memos. This clarity helps tailor the prompt for optimal results.

Providing Context and Examples

Supply relevant context, background information, and examples to ground the LLM's understanding of the legal domain and task at hand. This could include case summaries, legal definitions, or sample documents.

Using Instruction Prompts

Craft detailed instruction prompts that break down the task into specific steps or guidelines for the LLM to follow. This can help ensure the output adheres to legal conventions and requirements.

Incorporating Domain-Specific Knowledge

Integrate domain-specific legal knowledge, such as legal terminology, citation formats, and precedents, into the prompt to enhance the LLM's understanding and output quality.

Iterative Refinement

Engage in an iterative process of prompt refinement, evaluating the LLM's outputs, and adjusting the prompts accordingly to improve accuracy and relevance over multiple iterations.

Fine-tuning on Legal Data

Fine-tune the LLM on a curated dataset of legal texts, such as case law, statutes, or legal documents, to adapt its language model to the specific legal domain and improve performance on legal tasks.

Prompt Chaining and Decomposition

Break down complex legal tasks into smaller subtasks and use prompt chaining or decomposition techniques to guide the LLM through each step, combining the outputs into a final result.

Not everything is suitable for automation. Some tasks are best done by hand.

Verify, verify, verify

By employing these prompt engineering methods, lawyers and legal professionals can more effectively leverage LLMs' capabilities for various legal applications while ensuring compliance with legal standards and requirements.

FDCPA Bona Fide Error - Putting ChatGPT 4.0 to the test

 FDCPA Bona Fide Error - Putting ChatGPT 4.0 to the test

Summary

One District Court  granted the plaintiff's motion for summary judgment on the issue of a bona fide error defense and a second District Court granted the defendant's motion for summary judgment. The text of these two decisions was fed to ChatGPT 4.0 along with a 7th Circuit opinion that affirmed a defendant's judgment following a bench trial and elaborated on the bona fide error defense.

As a preliminary matter, I identified a simple distinction between the two District Court summary judgment decisions and I asked ChatGPT the following question.

"Based on the three court opinions uploaded, what is the difference between an "unfounded assumption" and an "informal understanding"?" 

ChatGPT's response is reproduced below.

Background

First, it is essential to know that ChatGPT 4.0 is substantially better than ChatGPT 3.5. Version 4.0 is available only through Open/AI's paid subscription ($20 / mo.) Chat 3.5 is free. I use version 4.0. 

As I continue exploring practical applications for Chatbots in the practice of law, the possibility that AI can rapidly and accurately digest and summarize court decisions is at the top of my list. Since AI is no more reliable than a third-year law student, Ronald Reagan's "trust but verify" admonition takes on a new meaning.

I deployed a test for ChatGPT with three court decisions on the "bona fide error" affirmative defense provided by the Fair Debt Collection Practices Act (FDCPA 15 USC § 1692k(c)), which states:

"A debt collector may not be held liable in any action brought under this title . . .  if the debt collector shows by a preponderance of evidence that the violation was not intentional and resulted from a bona fide error notwithstanding the maintenance of procedures reasonably adapted to avoid any such error."

The meaning and proof of "maintenance of procedures" have been recurring sources of contention in FDCPA litigation. For example, debt collectors sometimes mistakenly attempt to collect from debtors in bankruptcy, violating the FDCPA's strict liability prohibitions. Notice of bankruptcy is typically sent to the original creditor and not to the collection agency, so the debt collector is partially reliant on the creditor for notice of a debtor's bankruptcy.

May a debt collector justifiably rely on a creditor to advise of a debtor's bankruptcy, or must the collector undertake an independent investigation? What evidence is sufficient to prove "the maintenance of procedures reasonably adapted to avoid" collection efforts directed toward a debtor in bankruptcy? These issues were the crux of the following decisions.

Hyman v. Tate, 362 F.3d 965 (7th Cir. 2004)
Turner v. JVDB Associates Inc., 318 F. Supp. 2d 681 (ND Ill. 2004)
Yu v. Kevin B. Wilson Law Offices, 919 F. Supp. 2d 661 (D. Md. 2013)

Hyman was an appeal to the 7th Circuit from the District Court's judgment after a bench trial. The standard of review is "clear error." 

The debt collector's general manager (the GM) testified that three primary sources provide notice of a bankruptcy filing: 

(1) the bankruptcy court, 
(2) a debtor's call or letter, or 
(3) the creditor-client.

The GM testified that there was no formal agreement with the creditor to provide notice of bankruptcy or to refrain from referring bankruptcy debtors for collection. The debt collector understood that the bank would not forward accounts for collection where the debtor had filed for bankruptcy because "it would not be in their best business interests to do so."

The 7th Circuit concluded,

"Because forwarding bankrupt accounts was not only a bad business practice but also because Cross Country would immediately notify T K if an account in bankruptcy slipped through, the district court could reasonably conclude that the bank would not intentionally forward accounts in bankruptcy in the first instance. Moreover, the defendants presented evidence that of the accounts referred to it for collection, only .01% of those accounts were later found to have been in bankruptcy. Given this evidence, the district court did not commit clear error in concluding that T K reasonably relied on Cross Country not to forward accounts in bankruptcy . . . and as the district court found, it would not be reasonable to require T K to independently confirm that the accounts forwarded by the bank were not in bankruptcy, where the bank, in the first instance, limited the accounts forwarded to those not in bankruptcy."

In Turner, the District Court granted the plaintiff's motion for summary judgment on the issue of a bona fide error defense, basing its decision on the defendant's failure to produce evidence to support its claim of procedures reasonably adapted to avoid the error. 

The court stated that relying "on its creditor-clients to provide it with the relevant, current and accurate information . . .  whether a debtor has filed for bankruptcy . . .  is merely an unfounded assumption that is not based on any fact or any understanding . . . ."

The debt collector never alleged that it had any understanding with its clients that they would not forward accounts in bankruptcy. It further offered no evidence that its clients would immediately notify the collector of accounts in bankruptcy or that such accounts were infrequently forwarded.

In Yu v. Wilson Law Offices, the undisputed evidence establishes that the debt collector had an understanding with its clients that they exchange information regarding accounts in bankruptcy with one another. Witnesses affirmed that such an understanding and practice was in place. Plaintiff did not dispute those facts, but characterized them as assumptions rather than a mutual understanding that would constitute a "procedure" for purposes of the FDCPA.

The court held that uncontested evidence of an informal agreement that creditors would not send accounts in bankruptcy for collection was sufficient to establish the bona fide error defense.

Having studied these three opinions myself, I put ChatGPT 4.0 to the test, uploaded the three court opinions, and asked the following:

Task

Based on the three court opinions uploaded, what is the difference between an "unfounded assumption" and an "informal understanding"?

ChatGPT 4.0 Response

The court opinions provided elucidate the distinction between an "unfounded assumption" and an "informal understanding" within the context of the Fair Debt Collection Practices Act (FDCPA) and related legal judgments.

Unfounded Assumption:

An "unfounded assumption" refers to an assumption made without any reasonable basis or substantial evidence to support it. In the legal context of the opinions reviewed, it refers to a scenario where a debt collector presumes, without verifiable evidence, that their client (usually a creditor) would not send them accounts involving debtors in bankruptcy​​. This assumption lacks a procedural or contractual basis and is not supported by an established or proven practice. In the case of Yu v. Kevin B. Wilson Law Offices, the court described the reliance on such an assumption as insufficient for establishing a "bona fide error" defense under the FDCPA because it does not constitute a procedure reasonably adapted to avoid the error of attempting to collect a debt that has been discharged in bankruptcy​​.

Informal Understanding:

An "informal understanding" refers to a non-contractual agreement or expectation between parties based on past practices or mutual acknowledgment that certain protocols will be followed. In the cases examined, this often involves a practice where creditors and debt collectors understand and operate under the mutual expectation that no accounts in bankruptcy will be forwarded for collection. For example, in Hyman v. Tate, it was established that there was an informal understanding that the creditor would not refer accounts in bankruptcy for collection, which contributed to a successful "bona fide error" defense​​. The understanding, while not formalized in a contract, was based on a consistent practice acknowledged by both parties.

In summary, the difference lies in the basis and reliability of the belief or practice:

An unfounded assumption is a belief without evidence or historical practice, deemed insufficient to establish procedures that avoid violations of the FDCPA.

An informal understanding is based on a history of consistent practice or mutual acknowledgment, which can be sufficient to establish a bona fide error defense if it is part of a system designed to avoid wrongful debt collection activities.

Law as Rhetoric, Rhetoric as Argument - by Kurt M. Saunders

 

Law as Rhetoric, Rhetoric as Argument

Journal of Legal Education, volume 44, number 2, December 1994

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4384713

The text "Law as Rhetoric, Rhetoric as Argument" by Kurt M. Saunders focuses on the intrinsic relationship between law and rhetoric, emphasizing the importance of understanding legal argumentation. The primary thesis is that classical and contemporary rhetorical theories provide essential frameworks for grasping the structure and process of legal arguments, which is crucial for effective legal advocacy.

Key Points of the Text:

1. Foundation in Rhetoric:

   • Law and rhetoric share a historical and cultural heritage. This relationship suggests that insights from rhetorical theory are beneficial for legal practitioners and students.

2. Nature of Legal Arguments:

   • Legal arguments are fundamentally about persuasion and are practical rather than theoretical. They aim to establish one claim as more reasonable compared to another, acknowledging the possibility of opposing arguments and the inherent ambiguity of language.

3. Theoretical Contributions:

   • Stephen Toulmin and Chaim Perelman are highlighted for their contributions to the understanding of practical argumentation. They shift the focus from formal logic to practical arguments that reflect real-world reasoning.

4. Toulmin’s Model of Argumentation:

   • Toulmin introduces a model that includes claims, grounds, warrants, backing, qualifiers, and rebuttals. This model is procedural and reflects the dynamic nature of legal reasoning, where the movement from accepted data, through a warrant, leads to a claim.

5. Perelman’s New Rhetoric:

   • Perelman focuses on the role of rhetoric in shaping legal arguments by emphasizing the practical side of argumentation and the role of the audience in determining the persuasiveness of an argument.

6. Applications in Legal Education and Practice:

   • Both Toulmin and Perelman’s theories are suggested as valuable for legal education and practice. They help in understanding and constructing legal arguments, particularly in the context of litigation and advocacy.

7. Practical Implications:

   • The theories provide a foundation for teaching how to construct arguments at various stages of litigation and emphasize the heuristic nature of legal argumentation, which is about finding the most persuasive arguments based on the evidence and legal authority available.

8. Heuristics and Argument Construction:

   • The text discusses heuristics from both Toulmin and Perelman that can be applied to the construction and analysis of arguments in legal settings, aiding students and practitioners in effective argumentation and advocacy.

In conclusion, the text advocates for a more explicit integration of rhetorical theory into legal education to improve the understanding and effectiveness of legal argumentation. This approach helps bridge the gap between theoretical concepts and practical application in legal settings, enhancing the persuasive and justificatory capabilities of legal professionals.