When Congress and the President fail to agree on government appropriations and previous funding expires, the result can be a massively disruptive shutdown of the federal government. This occurred most recently in October 2013, and lasted for 16 days.
“Government shutdowns have necessitated furloughs of several hundred thousand federal employees, required cessation or reduction of many government activities, and affected numerous sectors of the economy,” according to a newly updated report from the Congressional Research Service. See Shutdown of the Federal Government: Causes, Processes, and Effects, updated May 5, 2017.
“Our country needs a good ‘shutdown’ in September to fix mess!” tweeted President Trump last week.
Other new and updated reports from the Congressional Research Service include the following.
Job Creation in the Manufacturing Revival, updated May 5, 2017
The Meaning of “Made in U.S.A.”, updated May 5, 2017
Review of Offshore Energy Leasing: President Trump’s Executive Order, CRS Insight, May 5, 2017
Navy Force Structure and Shipbuilding Plans: Background and Issues for Congress, updated May 5, 2017
Iran’s Presidential Elections, CRS Insight, May 5, 2017
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.