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.
Week in Review
New CFPB rule protects customers with short-term loans, EPA reportedly fails to follow a deadline on ozone standards, and more…
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.
Week in Review
Trump Administration temporarily waives Jones Act, London does not renew Uber’s operating license, and more…
Agency Removes Yellowstone Grizzly Bears from Endangered Species List
Final rule creates tension between conservationists and wildlife officials.
Concluding Thoughts on Cost-Benefit Analysis and the Public’s Impact in Rulemaking
The Supreme Court’s decision in Michigan v. EPA illustrates that the public has a serious role to play in the rulemaking process.