Process

Does the Administrative State Threaten U.S. Democracy?

Panel focuses on claims of potential dangers from growth in government agencies.

Building for Disaster

Data show that more stringent building codes deliver benefits greatly exceeding their costs.

Including Climate Change in Environmental Impact Analyses

D.C. Circuit holds federal energy regulators must consider pipeline project’s impact on climate change.

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.

Designing Safety Regulations for High-Hazard Industries

New National Academies of Sciences report offers much-needed clarity about regulatory design decisions.

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.