Although it “has stirred significant controversy in recent years,” the Congressional Research Service policy of restricting direct dissemination of its products to members of Congress is well-founded, argued CRS director Daniel P. Mulhollan in a lengthy internal memorandum (pdf) last month.
“The reasons for limiting public distribution of our work can be summarized as follows,” he wrote.
“First, there is a danger that placing CRS in an intermediate position [between Congress and the public] would threaten the dialog on policy issues between Members and their constituents.”
“Second, the current judicial … perception of CRS as ‘adjunct staff’ of the Congress might be altered if CRS were seen as speaking directly to the public, putting at risk Speech or Debate Clause constitutional protections afforded the confidential work performed by this agency.”
“And third, if CRS products were routinely disseminated broadly to the public, over time these products might come to be written with a large public audience in mind and would no longer be focused solely on congressional needs.”
A copy of Director Mulhollan’s seven page memorandum on “Access to CRS Reports,” dated April 18, 2007, was obtained by Secrecy News and is available here.
The arguments detailed by Mr. Mulhollan seem singularly unpersuasive to an outsider. CRS is not being called upon to mediate between Congress and the public or to engage in a public dialog on policy issues. Rather, proponents of broader dissemination are simply asking for the same public access that commercial vendors of CRS reports already enjoy.
These ideas aim to advance the detailed policy solutions needed to foster public trust and implement fairness in the adoption of AI across diverse domains, from healthcare and government benefits to rural access, education, and worker protections.
The evidence is clear: algorithmic pay-setting is established in app-based work, and payroll/timekeeping failures show how software can produce systemic wage harm at scale
While a few states have taken steps to implement decision-making mechanisms for certain AI systems, too many leaders are simply accepting narratives about AI’s purported public benefit at face value – jumping to the “how” of AI implementation before thoroughly vetting potential systems and deciding whether they are appropriate to use at all.
When properly structured — with specific numeric targets, secured financial obligations, independent monitoring, and meaningful enforcement — CBAs transform data center deals into durable community partnerships.