PII Meets GenAI: What Actually Happens When Sensitive Data Enters Your Prompt?
"Don’t put sensitive data into an AI prompt." I hear this advice a lot, and while it makes sense, I think it oversimplifies the problem. As more applications start using GenAI to summarize documents, answer questions, support employees, or process customer information, sensitive data is going to show up in some of these interactions. So instead of only asking whether sensitive data should enter a…
Putting sensitive data into an AI prompt may seem like a straightforward issue, but it overlooks the complex journey that data takes once it enters the prompt. Instead, it's more useful to ask: What happens to that data throughout the entire process? Consider a simple customer support request where the customer's name, email, account number, and complaint are all PII.
While one might look to the model provider for answers on data retention, usage, and storage, the journey is far more extensive. The request could be logged, logged in API calls, and stored in monitoring systems or conversation history. This means new risks can arise from logging mechanisms, application logs, and even the responses generated by the model.
It's crucial to ask questions about what the model truly needs, whether data can be redacted or tokenized before sending, and where the response is headed after the model call. By tracing data from its inception to its final destination, potential privacy and security issues become more apparent. The focus should be on understanding the data flow and ensuring that sensitive information is handled intentionally, rather than simply avoiding its inclusion altogether.
Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
