A privacy expert recently offered a genuinely blunt, sobering assessment worth taking seriously: while the penalty for violating the Family Educational Rights and Privacy Act is technically the loss of federal funding, the law reportedly lacks meaningful enforcement in practice, having, according to this expert's account, essentially never been formally enforced against a violation. This is a genuinely important piece of context for anyone evaluating AI education vendors, including grading tool vendors specifically, based partly on their claimed legal compliance with data privacy law.

This doesn't mean FERPA compliance is meaningless, the law still establishes genuine, important standards worth vendors meeting, but it does mean that a vendor's claim of FERPA compliance shouldn't be treated as sufficient, self-verifying assurance on its own. Given the apparent enforcement gap, districts and schools have genuine reason to conduct their own real, independent due diligence rather than relying primarily on a vendor's legal compliance claims as the sole basis for trust.

This reinforces a theme that's been building across current, more careful discussion of AI vendor evaluation: genuine transparency, specific, written commitments, and independent verification where possible matter considerably more than general legal compliance assurances alone, precisely because meaningful enforcement mechanisms don't always exist to back those assurances up.

What this enforcement gap means practically for vendor evaluation

Given this apparent enforcement gap, districts and schools benefit from treating vendor data privacy evaluation as genuinely their own responsibility, not something adequately handled simply because a vendor claims legal compliance. This means requesting specific, written data handling commitments, asking direct questions about what happens to student data, whether it's used for model training, how long it's retained, and treating a vendor's transparency and specificity in answering these questions as more meaningful evidence than a general compliance claim alone.

• Treat vendor FERPA compliance claims as a starting point, not sufficient assurance on their own, given this apparent enforcement gap
• Request specific, written data handling commitments directly from any AI grading vendor, rather than relying on general compliance language
• Ask directly whether student data is used to train models beyond your own district's use, and get that answer in writing
• Weigh a vendor's transparency and specificity in answering these questions as more meaningful than the legal compliance claim alone
• Consider that agreements with real, binding enforcement mechanisms built in, like the recent Microsoft-AFT agreement, offer a genuinely stronger accountability model than general legal compliance assurance

Why this reinforces the value of contractually binding commitments

Given genuine gaps in how well underlying privacy law actually gets enforced, contractually binding commitments negotiated directly into a district's own vendor agreements, similar in spirit to the recent Microsoft-AFT national standard, offer considerably stronger, more genuinely enforceable protection than relying on general federal privacy law alone. Districts have real reason to build specific, binding data privacy language directly into their own vendor contracts, rather than assuming underlying federal law provides sufficient protection on its own.

This is a useful, practical takeaway for any department negotiating a grading tool contract: ask for the same kind of specific, binding commitments, rather than accepting general compliance language, that recent industry agreements have started to establish as a genuinely stronger model.

A sobering context worth factoring into every vendor conversation

This candid assessment of FERPA's real-world enforcement gap is worth keeping in mind for any AI vendor evaluation this year, reinforcing why genuine transparency, specific written commitments, and independent scrutiny matter considerably more than general legal compliance language alone.