So far, most we have spoken to are literally SHOCKED that we require SOC3 (one company even told me they'd never even heard of SOC3) and everything needs to be hashed before it goes out and be mapped on our end back to actual. They think we're being too cautious and are really trying to get to sale without understanding that it's literally NOT something we can do and NO ONE else should be doing it either.
The humans at TaskUS are moderating prompts, and then you have Azure, CloudFlare, and Snowflake as sub-processors, each with their own list of sub-processors and on and on.
https://platform.openai.com/subprocessors
Data breaches can happen, so any data that you throw over the wall to OpenAI you must be willing to accept that it could become public.
The de-identification itself requires a complex language model, which has its own complexity and costs to operate. At Cape we're going as far as we can to offer a secure API that's self-serve and easy to use to make these feature accessible to developers, but it does require trust in Cape and the underlying AWS Nitro Enclaves that we use. Client-side attestation is a security feature that can help provide cryptographic verification to the client of the secure enclave. But local is always better when possible!
I want less parties involved with secure data, not more. This should be an on-prem solution with no external network access and no direct calls to OpenAI. A call is made to this service to obfuscate, then another call to OpenAI, all managed by a coordinating mechanism that is opensource / trusted.
Better yet, maybe LLMs should be required to have weights released considering they are trained on the collective of human knowledge. Seems strange to use a significant sum of human knowledge that is publicly available then deny everyone access to the weights.