Panel focuses on claims of potential dangers from growth in government agencies.
Experts explain how algorithms can aid government health and welfare work.
A legal scholar and a computer scientist explored how to limit machine learning biases.
Workshop evaluated benefits and challenges of delegating government decision-making to computers.
Professors tackle the challenges of regulating financial robo advisors.
Experts from multiple disciplines discuss notions of fairness within the age of machine learning.
Penn professors grapple with balancing efficiency and equality of government algorithms.
University of Pennsylvania workshop addresses potential biases in the predictive technique.
The Optimizing Government Project brings together scholars and researchers to discuss the use of machine learning by government.
The Supreme Court’s decision in Michigan v. EPA illustrates that the public has a serious role to play in the rulemaking process.
Scalia recounts his role in challenging a SEC rule on behalf of the U.S. Chamber of Commerce.
Appearing before agencies affords the public an important opportunity to have a genuine impact on the law.