A few things jump out since this is done by the government:
- the lowest hanging fruit for this problem is to clearly tell people (citizens) not to share any personal info with chatbots which can cause financial harm or identity theft. the example on the page shows a person sharing their SNN with a chatbot to help them find an apartment - "My name is Maria Garcia, my Social Security number is 123-45-6789, and I make $1,950 a month. Can you help me find affordable housing?" - why?? this is the opposite of what i would expect a government to advise their citizens.
- it's never too late for a good policy; the government should have extended HIPPA and other data privacy laws to AI companies - the AI company must not store anyone's SSN, no matter how stupid the user is. It should be on the AI company to not store it; so this type of layer should be on the AI company's side.
- technical; there are quasi identifiers of privacy (that's what my package targets) that are asymptotically hard to to deal with - meaning - if you remove everything that can leak your privacy the text would become meaningless. i don't think rampart can solve for that either and it should be clearly said on the website.
Is it still commendable if in order to develop this, the taxpayer-funded developer themselves published our PII to a consumer, privately controlled third-party server without following federal data security protocols? Seems like an attempt to make up for the damage they caused.
Standing up your own AWS-equivalent internally is not much work, yet the PII data leaked to publicly available services due to this developer's personal choices and lack of oversight to prevent sensitive government data from being published externally.
Notably, this resulting work has not been published as public domain (CC0).
The purpose of a government is to serve its people, not make sure every business gets the same conditions at all costs. Picking winners and losers is fine if the losers still have a chance to beat the winners when they're really better.
If someone makes a free PII detector better than Rampart I bet the US government will either switch to it or make Rampart v2. For now it's enough. Perfect is the enemy of good.
https://www.csoonline.com/article/4046997/whistleblower-doge...
If your product is handling natural language conversations from end customers, there is not much you can do to prevent the occasional PII leak without ruining the rest of the pie. ZDR is your best mitigation if you actually want the magical AI experience to work the way the investors hope it can.
PII can often become disclosed by way of many correlated factors that are not considered PII on their own. Even a perfect AI system cannot capture all of these relationships. You could probably locate where I live within a 20 mile radius if you spent enough time analyzing my HN comments over the years. Not one of these comments on their own would trigger a PII filter.
For related reasons (e.g. rule compliance) I'm trying to convince folks to shrink the LLM's role to a kind of "guess which valid choice the user meant to ask for" level, and let the data-entry parts be small and deterministic pieces.
Alas, convincing anyone to use some symbolic GOFAI (or a strict "harness" that is 90% of the way there) seems hard these days. The allure of a promised magical silver bullet is strong.
I suppose the model could be doing stuff, but you can also switch that out for your own with the source.
That hasn't happened yet, has it? Where running a model from HF directly compromises the machine as opposed to some breakout or exfil done by the model after the fact?
That said, if you're filing your taxes or have a 'real' ID, the government already has all pertinent information required to fuck you over either deliberately or via a leak, so...
If your question is: "Is client-side de-identification sufficient for HIPAA," then sure, assuming you are de-identifying the data elements required by HIPAA to be de-identified. You'd have to be a real big idiot to rely on something like this though.
If your question is: "Does this library, as described in the blog post, de-identify data sufficiently for HIPAA?" then no, it doesn't appear that it does.
CC by 4.0 is not the same as CC0 (public domain): https://creativecommons.org/public-domain/