1. Background of the Decision

The decision in question was made within the scope of a massive lawsuit filed on claims of copyright infringement. Publishers demanded millions of ChatGPT conversations based on the allegation that artificial intelligence models were trained on their content. Judge Wang accepted this request, ruling for the delivery of the dataset despite all objections from OpenAI.

However, the Federal Rules of Civil Procedure (FRCP) in the U.S. require a "relevant and proportional" data request during the discovery process. This demand indicates that it is legally questionable for the court to request a vast quantity of unrelated content belonging to millions of individuals.

OpenAI's objection emphasized the following points:

• The overwhelming majority of the requested conversations are not related to the case,

• The majority of users are not parties to the case,

• The requested volume of data is inconsistent with the principles of necessity and proportionality,

• Anonymizing a dataset of this scale is not practically possible.

However, the court seems to have concluded that the existing protective measures and anonymization would be sufficient. This approach reflects a perspective that does not adequately consider the properties of modern data structures and the nature of artificial intelligence interactions.

2. The Anonymization Problem

One of the justifications underlying the decision is the assumption that OpenAI can anonymize conversations through an “exhaustive de-identification” method. However, it is now a well-known fact that anonymization provides very limited legal and technical protection.

Recent studies have clearly revealed the extent of this risk:

• Techdirt analysis: 1,000 leaked conversations were examined, revealing numerous discussions containing explicit PII.

• Washington Post review: Among 47,000 chat records, there were email addresses, phone numbers, internal communications, and personal sensitive information.

ChatGPT conversations are not a traditional database; they consist of contextual data created by users' own expressions, meaning they have the quality of a “semantic fingerprint” that allows for identifying a person based on the text.

Therefore, removing names does not signify much in most cases. The presence of job titles, company names, specific incidents, or specific service information facilitates easy re-identification of an individual.

3. The Risk to Privacy, Personal Data, and Corporate Secrets

In practice, when users communicate with chat-based AI tools like ChatGPT:

• Case strategies,

• Texts related to terminations,

• Financial statements,

• Internal information regarding KVKK, GDPR, or MASAK processes,

• Employee performance, internal disputes,

• Personal emotional issues

they easily express sensitive content that they would never share in an email or official correspondence. The reason for this is the chat-based structure of AI tools and the user’s perception of a “private space.”

At this point, it has become clear that this perception does not have a legal basis.

In other words:

From today onward, every AI chat has potentially become a digiital trail subject to discovery.

The risk of corporate secrets, employee information, or financial data being exposed can lead to serious liabilities, especially in multinational companies.

4. Corporate Perspective

The direct implication of this decision for organizations is that the use of AI should now be evaluated at the same risk level as email, messaging or written documents. In fact, it often carries a higher risk; because emotional or personal comments, which do not exist in written documents, frequently appear in AI chats.

Therefore, companies must take the following steps:

a. Review AI policies immediately

It must be clearly stated which information can be shared, which topics are absolutely prohibited, and which tools employees can use.

b. Create training and awareness processes

Employees must be clearly informed with the message, "Every conversation you have with ChatGPT may resurface someday."

c. Consider closed-loop or local models

To minimize legal risk, in-house models or systems with stronger privacy principles should be preferred.

d. Establish procedures for recording, storing and accessing AI interactions

AI chats may legally qualify as “business records”; monitoring this is a corporate responsibility.

5. 20th Century Rules Cannot Accommodate 21st Century Technology

One of the most striking points in this case is the tendency of courts to still evaluate artificial intelligence communication like traditional digital data. However, since AI reconstructs users' behaviors and identities through textual traces, classic “anonymization” or “limited discovery” principles are insufficient.

If this decision becomes final and sets a precedent, it will open the door for every lawsuit filed against AI companies to request all conversations belonging to millions of people. This directly affects both data privacy and companies' trade secrets.