CDT Submits Comments Urging Careful Approach for Expansion of Do Not Pay System

The Center for Democracy and Technology has been tracking agencies’ increased sharing with the Department of the Treasury’s Do Not Pay initiative. While CDT appreciates the role played by the Do Not Pay initiative in the effort to reduce improper payments by government agencies, contributing to a centralized collection of sensitive data must be approached with care and caution, particularly against the backdrop of the Trump Administration’s broader efforts to amass and consolidate vast amounts of personal information from a variety of federal and state programs, with little regard for privacy and security protections.
Consequently, CDT urges agencies to protect the personal data with which they have been entrusted by applying robust data minimization practices, enacting strong security protocols, limiting redisclosure, and mitigating data quality issues. Failing to do so may result in vulnerable individuals being wrongly denied critical supports and open them up to harms such as identity theft, as well as putting agencies at risk for legal and reputational harms if its data is used in ways that violate legal frameworks governing the privacy and use of that data, or do not comport with the intended purpose of collection.
To ensure people’s sensitive information is properly stewarded, CDT recommends that agencies sharing with the Do Not Pay initiative establish agreements that Treasury will protect agencies’ data by:
- Employing robust data minimization practices,
- Using strong security protocols,
- Adhering to redisclosure limitations, and
- Following clear processes for matching records across datasets.
Comments to individual agencies can be found below:

Facts Only

* The Center for Democracy and Technology has been tracking agency sharing with the Do Not Pay initiative.
* CDT expressed concern about contributing to a centralized collection of sensitive data.
* CDT urged agencies to protect entrusted personal data by applying robust data minimization practices.
* Agencies must enact strong security protocols.
* Agencies must limit redisclosure of data.
* Agencies must mitigate data quality issues.
* Failing to protect data may result in vulnerable individuals being wrongly denied supports or facing identity theft.
* Data misuse can expose agencies to legal and reputational harms if usage violates privacy laws or intended purposes.
* CDT recommends agencies establish agreements where the Treasury protects data by employing robust data minimization, strong security protocols, redisclosure limitations, and clear record matching processes.

Executive Summary

The Center for Democracy and Technology has urged government agencies to adopt robust data protection practices when sharing information with the Department of the Treasury’s Do Not Pay initiative. The concern stems from the potential for centralizing sensitive data, especially given broader administration efforts to collect personal information without adequate privacy safeguards. Consequently, CDT recommends that agencies employ data minimization, strong security protocols, limitations on redisclosure, and clear processes for matching records across datasets. Failure to implement these measures risks denying critical supports to vulnerable individuals and exposes agencies to legal or reputational harm if data misuse occurs. To ensure proper stewardship of sensitive information shared with the Do Not Pay initiative, CDT advises establishing agreements where the Treasury guarantees data protection through these specific operational standards.

Full Take

The narrative centers on a tension between the utility of centralized government data initiatives and fundamental privacy rights. The core implication is that the pursuit of administrative efficiency through data sharing must be fundamentally balanced against the duty to protect individual autonomy and security. The warning against consolidating sensitive data under broad initiatives reflects a broader skepticism regarding unchecked governmental data aggregation, especially when juxtaposed with external political contexts suggesting a prioritization of information consolidation over explicit privacy guarantees. The recommended actions—data minimization and strict protocols—are not merely technical suggestions but defenses of human dignity and agency; they frame the system as conditional on adherence to principled stewardship rather than being an inherent right. The underlying pattern suggests that institutional efforts, even those ostensibly for public good, require external, stringent constraints to prevent mission drift toward surveillance or potential harm against specific populations. What assumptions about the necessity of such data aggregation are being tacitly accepted by the agencies involved? And how does the risk of secondary harm, like denying support, weigh against administrative convenience in these complex trade-offs?

Sentinel — Human

Confidence

The text reads like a formal public comment or policy position statement, exhibiting the measured, conditional language typical of human advocacy writing rather than pure algorithmic generation.

Signals Detected

Moderate sentence length variance; rhetorical flow suggests human drafting intent.

Logically structured argument focusing on policy advice, exhibiting a consistent, if formal, voice.

Standard organizational flow; the core points are directly linked to the stated concerns of an advocacy group.

Claims rely on established policy frameworks (Do Not Pay, privacy concerns) rather than novel, unverifiable assertions.

Human Indicators

The text successfully navigates complex regulatory/policy language and adopts a specific advocacy tone characteristic of non-governmental organization commentary.