Last month, the 10,000th Syrian refugee was admitted to the United States in FY2016, the Congressional Research Service noted in a newly updated report. The report “details the U.S. refugee admissions process and the placement and resettlement of arriving refugees in the United States.”
See Syrian Refugee Admissions and Resettlement in the United States: In Brief, updated September 16, 2016.
Other new and updated reports from the Congressional Research Service include the following.
Super PACs in Federal Elections: Overview and Issues for Congress, updated September 16, 2016
FY2017 Defense Spending Under an Interim Continuing Resolution (CR): In Brief, September 16, 2016
Israel: Background and U.S. Relations In Brief, updated September 16, 2016
Behavioral Health Among American Indian and Alaska Natives: An Overview, September 16, 2016
Department of State and Foreign Operations Appropriations: History of Legislation and Funding in Brief, September 15, 2016
Researching Current Federal Legislation and Regulations: A Guide to Resources for Congressional Staff, updated September 19, 2016
Corporate Tax Integration and Tax Reform, September 16, 2016
Nanotechnology: A Policy Primer, updated September 15, 2016
Navy Force Structure: A Bigger Fleet? Background and Issues for Congress, September 16, 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.