Technology

All Hands on Deck for Cybercrime Regulation

Scholar analyzes how traditional police regulation must change in the face of cybercrime.

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.

Co-Regulating the Platform Economy

To regulate the digital economy, regulators must cooperate with platform firms, says scholar.

Improving the Public-Private Cybersecurity Partnership

State-sponsored cyber attacks may require revamping how the government helps companies fight back.

The FTC and Net Neutrality’s Plan B

Would the FTC be an effective body for regulating Internet openness?