A campaign by citizens’ groups in Germany last month persuaded the Bundestag (the German parliament) to authorize the release of thousands of research reports prepared by the Wissenschaftlicher Dienst, the German equivalent of the Congressional Research Service.
“But not only that: The Parliament also changed its publication policy regarding all new reports. In the future, they will be released by the Parliament after a protective period of four weeks,” according to a blog post on the campaign from FragDenStaat.
Our own Congress is still not quite ready to follow suit.
For now, the latest products of the Congressional Research Service must be obtained through alternate channels:
Nigeria: Current Issues and U.S. Policy, March 11, 2016
Consumer Operated and Oriented Plan (CO-OP) Program: Frequently Asked Questions, March 11, 2016
Legal Issues with Federal Labeling of Genetically Engineered Food: In Brief, updated March 11, 2016
Veterans’ Benefits: Burial Benefits and National Cemeteries, updated March 11, 2016
FY2017 Budget Documents: Internet and GPO Availability, updated March 10, 2016
Navy DDG-51 and DDG-1000 Destroyer Programs: Background and Issues for Congress, updated March 10, 2016
U.S. Strategic Nuclear Forces: Background, Developments, and Issues, updated March 10, 2016
Americans are paying too much for almost everything, because the United States has long treated its trucking industry as an artifact to be preserved rather than as an opportunity for innovation.
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.