The “smart grid” refers to an ongoing modernization of the nation’s electrical power system that makes it possible to dynamically allocate power and optimize system operation. It’s a work in progress.
A new report from the Congressional Research Service reviews smart grid technologies, costs and concerns including privacy and cybersecurity. See The Smart Grid: Status and Outlook, April 10, 2018.
Other new and updated reports from the Congressional Research Service this week include the following.
An Overview of Discretionary Reprieves from Removal: Deferred Action, DACA, TPS, and Others, April 10, 2018
Class Action Lawsuits: A Legal Overview for the 115th Congress, April 11, 2018
The Bipartisan Budget Act of 2018 and an FY2019 Budget Resolution, April 10, 2018
Trade Promotion Authority (TPA): Frequently Asked Questions, updated April 10, 2018
Infantry Brigade Combat Team (IBCT) Mobility, Reconnaissance, and Firepower Programs, updated April 10, 2018
Tort and Litigation Reform in the 115th Congress, CRS Legal Sidebar, April 10, 2018
Mississippi Court Halts Enforcement of New Abortion Law, CRS Legal Sidebar, April 10, 2018
OMB and Treasury Disagree over Process for Issuing New Tax Rules, CRS Insight, April 10, 2018
Balanced Budget Amendments, CRS Insight, April 10, 2018
U.S. Foreign Aid to Israel, updated April 10, 2018
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.