Of “Workarounds” and Bureaucrats
Civil service reformers should consider changes to lengthy, single-agency employee tenures.
Getting Back to the Basics with Agency Rulemaking
The United States needs a bipartisan push to bring transparency and accountability back into the rulemaking process.
Repealing the CFPB’s Arbitration Rule
President Trump signs measure rescinding the financial consumer watchdog’s recent rule.
Does the Administrative State Threaten U.S. Democracy?
Panel focuses on claims of potential dangers from growth in government agencies.
How Machine Learning Can Improve Public Sector Services
Experts explain how algorithms can aid government health and welfare work.
How Can We Reveal Bias in Computer Algorithms?
A legal scholar and a computer scientist explored how to limit machine learning biases.
Should Robots Make Law?
Workshop evaluated benefits and challenges of delegating government decision-making to computers.
Regulating the Robots that Help Us Decide
Professors tackle the challenges of regulating financial robo advisors.
Experts Weigh in on Fairness and Performance Trade-Offs in Machine Learning
Experts from multiple disciplines discuss notions of fairness within the age of machine learning.
Machine Learning’s Implications for Fairness and Justice
Penn professors grapple with balancing efficiency and equality of government algorithms.
The Usefulness—and Possible Dangers—of Machine Learning
University of Pennsylvania workshop addresses potential biases in the predictive technique.
Optimizing Government
The Optimizing Government Project brings together scholars and researchers to discuss the use of machine learning by government.