ADPPA Mimics GDPR’s Flaws, and Goes Further Still

Mikolaj Barczentewicz —  22 June 2022 — Leave a comment

Just three weeks after a draft version of the legislation was unveiled by congressional negotiators, the American Data Privacy and Protection Act (ADPPA) is heading to its first legislative markup, set for tomorrow morning before the U.S. House Energy and Commerce Committee’s Consumer Protection and Commerce Subcommittee.

Though the bill’s legislative future remains uncertain, particularly in the U.S. Senate, it would be appropriate to check how the measure compares with, and could potentially interact with, the comprehensive data-privacy regime promulgated by the European Union’s General Data Protection Regulation (GDPR). A preliminary comparison of the two shows that the ADPPA risks adopting some of the GDPR’s flaws, while adding some entirely new problems.

A common misconception about the GDPR is that it imposed a requirement for “cookie consent” pop-ups that mar the experience of European users of the Internet. In fact, this requirement comes from a different and much older piece of EU law, the 2002 ePrivacy Directive. In most circumstances, the GDPR itself does not require express consent for cookies or other common and beneficial mechanisms to keep track of user interactions with a website. Website publishers could likely rely on one of two lawful bases for data processing outlined in Article 6 of the GDPR:

  • data processing is necessary in connection with a contractual relationship with the user, or
  • “processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party” (unless overridden by interests of the data subject).

For its part, the ADPPA generally adopts the “contractual necessity” basis for data processing but excludes the option to collect or process “information identifying an individual’s online activities over time or across third party websites.” The ADPPA instead classifies such information as “sensitive covered data.” It’s difficult to see what benefit users would derive from having to click that they “consent” to features that are clearly necessary for the most basic functionality, such as remaining logged in to a site or adding items to an online shopping cart. But the expected result will be many, many more popup consent queries, like those that already bedevil European users.

Using personal data to create new products

Section 101(a)(1) of the ADPPA expressly allows the use of “covered data” (personal data) to “provide or maintain a specific product or service requested by an individual.” But the legislation is murkier when it comes to the permissible uses of covered data to develop new products. This would only clearly be allowed where each data subject concerned could be asked if they “request” the specific future product. By contrast, under the GDPR, it is clear that a firm can ask for user consent to use their data to develop future products.

Moving beyond Section 101, we can look to the “general exceptions” in Section 209 of the ADPPA, specifically the exception in Section 209(a)(2)):

With respect to covered data previously collected in accordance with this Act, notwithstanding this exception, to perform system maintenance, diagnostics, maintain a product or service for which such covered data was collected, conduct internal research or analytics to improve products and services, perform inventory management or network management, or debug or repair errors that impair the functionality of a service or product for which such covered data was collected by the covered entity, except such data shall not be transferred.

While this provision mentions conducting “internal research or analytics to improve products and services,” it also refers to “a product or service for which such covered data was collected.” The concern here is that this could be interpreted as only allowing “research or analytics” in relation to existing products known to the data subject.

The road ends here for personal data that the firm collects itself. Somewhat paradoxically, the firm could more easily make the case for using data obtained from a third party. Under Section 302(b) of the ADPPA, a firm only has to ensure that it is not processing “third party data for a processing purpose inconsistent with the expectations of a reasonable individual.” Such a relatively broad “reasonable expectations” basis is not available for data collected directly by first-party covered entities.

Under the GDPR, aside from the data subject’s consent, the firm also could rely on its own “legitimate interest” as a lawful basis to process user data to develop new products. It is true, however, that due to requirements that the interests of the data controller and the data subject must be appropriately weighed, the “legitimate interest” basis is probably less popular in the EU than alternatives like consent or contractual necessity.

Developing this path in the ADPPA would arguably provide a more sensible basis for data uses like the reuse of data for new product development. This could be superior even to express consent, which faces problems like “consent fatigue.” These are unlikely to be solved by promulgating detailed rules on “affirmative consent,” as proposed in Section 2 of the ADPPA.

Problems with ‘de-identified data’

Another example of significant confusion in the ADPPA’s the basic conceptual scheme is the bill’s notion of “de-identified data.” The drafters seemed to be aiming for a partial exemption from the default data-protection regime for datasets that no longer contain personally identifying information, but that are derived from datasets that once did. Instead of providing such an exemption, however, the rules for de-identified data essentially extend the ADPPA’s scope to nonpersonal data, while also creating a whole new set of problems.

The basic problem is that the definition of “de-identified data” in the ADPPA is not limited to data derived from identifiable data. The definition covers: “information that does not identify and is not linked or reasonably linkable to an individual or a device, regardless of whether the information is aggregated.” In other words, it is the converse of “covered data” (personal data): whatever is not “covered data” is “de-identified data.” Even if some data are not personally identifiable and are not a result of a transformation of data that was personally identifiable, they still count as “de-identified data.” If this reading is correct, it creates an absurd result that sweeps all information into the scope of the ADPPA.

For the sake of argument, let’s assume that this confusion can be fixed and that the definition of “de-identified data” is limited to data that is:

  1. derived from identifiable data, but
  2. that hold a possibility of re-identification (weaker than “reasonably linkable”) and
  3. are processed by the entity that previously processed the original identifiable data.

Remember that we are talking about data that are not “reasonably linkable to an individual.” Hence, the intent appears to be that the rules on de-identified data would apply to non-personal data that would otherwise not be covered by the ADPPA.

The rationale for this may be that it is difficult, legally and practically, to differentiate between personally identifiable data and data that are not personally identifiable. A good deal of seemingly “anonymous” data may be linked to an individual—e.g., by connecting the dataset at hand with some other dataset.

The case for regulation in an example where a firm clearly dealt with personal data, and then derived some apparently de-identified data from them, may actually be stronger than in the case of a dataset that was never directly derived from personal data. But is that case sufficient to justify the ADPPA’s proposed rules?

The ADPPA imposes several duties on entities dealing with “de-identified data” (that is, all data that are not considered “covered” data):

  1. to take “reasonable measures to ensure that the information cannot, at any point, be used to re-identify any individual or device”;
  2. to publicly commit “in a clear and conspicuous manner—
    1. to process and transfer the information solely in a de- identified form without any reasonable means for re- identification; and
    1. to not attempt to re-identify the information with any individual or device;”
  3. to “contractually obligate[] any person or entity that receives the information from the covered entity to comply with all of the” same rules.

The first duty is superfluous and adds interpretative confusion, given that de-identified data, by definition, are not “reasonably linkable” with individuals.

The second duty — public commitment — unreasonably restricts what can be done with nonpersonal data. Firms may have many legitimate reasons to de-identify data and then to re-identify them later. This provision would effectively prohibit firms from effective attempts at data minimization (resulting in de-identification) if those firms may at any point in the future need to link the data with individuals. It seems that the drafters had some very specific (and likely rare) mischief in mind here but ended up prohibiting a vast sphere of innocuous activity.

Note that, for data to become “de-identified data,” they must first be collected and processed as “covered data” in conformity with the ADPPA and then transformed (de-identified) in such a way as to no longer meet the definition of “covered data.” If someone then re-identifies the data, this will again constitute “collection” of “covered data” under the ADPPA. At every point of the process, personally identifiable data is covered by the ADPPA rules on “covered data.”

Finally, the third duty—“share alike” (to “contractually obligate[] any person or entity that receives the information from the covered entity to comply”)—faces a very similar problem as the second duty. Under this provision, the only way to preserve the option for a third party to identify the individuals linked to the data will be for the third party to receive the data in a personally identifiable form. In other words, this provision makes it impossible to share data in a de-identified form while preserving the possibility of re-identification. Logically speaking, we would have expected a possibility to share the data in a de-identified form; this would align with the principle of data minimization. What the ADPPA does instead is effectively to impose a duty to share de-identified personal data together with identifying information. This is a truly bizarre result, directly contrary to the principle of data minimization.

Conclusion

The basic conceptual structure of the legislation that subcommittee members will take up this week is, to a very significant extent, both confused and confusing. Perhaps in tomorrow’s markup, a more open and detailed discussion of what the drafters were trying to achieve could help to improve the scheme, as it seems that some key provisions of the current draft would lead to absurd results (e.g., those directly contrary to the principle of data minimization).

Given that the GDPR is already a well-known point of reference, including for U.S.-based companies and privacy professionals, the ADPPA may do better to re-use the best features of the GDPR’s conceptual structure while cutting its excesses. Re-inventing the wheel by proposing new concepts did not work well in this ADPPA draft.

Mikolaj Barczentewicz

Posts

Mikolaj Barczentewicz is a Senior Lecturer in Public Law and Legal Theory and the Research Director of the Law and Technology Hub at the University of Surrey School of Law in Guildford, England.

No Comments

Be the first to start the conversation!

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.