Reviewing and Producing AI Chatbot and Social Media Data: Key Legal Considerations for Discovery

From AI Chatbots to Social Media: Data Review and Production Enter New Territory

With the increasing role of AI, the review and production of data now includes AI-generated content and its origins. Generative AI tools have the potential to make data review more accurate, efficient, and cost-effective. However, legal professionals must still address fundamental procedural requirements when handling novel data sources like chatbot transcripts and social media content.

Procedural Basics Apply to Novel Data Sources

The Federal Rules of Civil Procedure govern discovery for all electronically stored information, including unconventional sources such as social media posts and AI chatbot logs. Discovery requests must remain relevant to the claims or defenses and proportional to the case’s needs. For example, casual communications in workplace messaging apps or private social media groups can hold as much evidentiary value as formal emails in employment disputes.

Key Considerations for Reviewing Novel Data Sources

Data from new technologies presents specific challenges regarding relevance, reliability, and admissibility. Here are critical points attorneys should keep in mind:

Authorship and Attribution

AI-generated content complicates the question of authorship. The output originates from AI responding to user prompts, blurring who "wrote" the message. Attorneys must determine if the chatbot’s output reflects a party’s intent or knowledge, which impacts evidentiary weight. This involves understanding how the AI was developed, trained, and whether it is scripted or generative. Contextual knowledge is also essential to assess the meaning and intent behind the communication.

Context and Prompt History

AI chatbot responses depend heavily on the prompt history. Reviewing isolated outputs can be misleading without related prompts or prior messages. Similarly, third-party messaging app data often requires examining entire conversation threads to provide proper context. Legal teams should consider producing full sessions or threads and may need additional discussions with opposing counsel to handle the non-linear flow common in chat data.

Evidentiary Reliability

AI outputs can contain inaccuracies or fabricated information presented convincingly. Legal teams must critically evaluate the factual reliability of AI-generated content and avoid relying on it without corroboration. Consider the chatbot’s training data for verifiability, the context of use, and its known limitations, such as interpreting nuance. Cross-checking AI-generated information with other evidence remains essential.

Confidentiality and Privilege

Users may unintentionally disclose sensitive or privileged information to public AI systems or through messaging apps. Attorneys should carefully screen these sources for potential privilege waivers or confidentiality breaches and assess any impact on privilege claims or ethical duties.

Possession and Control

When chatbots or messaging platforms are operated by third parties, the user might not have full control or access to conversation histories. Attorneys must evaluate whether the producing party has legal control over responsive data and be ready to address access issues with opposing counsel or the court.

The complexities introduced by AI chatbots and social media as data sources require a cautious, well-documented, and informed approach. Legal teams should combine technical understanding with sound judgment to ensure effective review and production of these novel data types.