machine learning

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.

Regulating Automated Financial Advice

Scholars present framework for the regulation of automated advisors in the financial services industry.

Adjudicating by Algorithm, Regulating by Robot

Rather than raising alarm bells, government uses of artificial intelligence fit well within existing legal frameworks.

Deciding Whether Software Will Eat the Bureaucracy

Agencies, policymakers, and the courts can all address the risks associated with cyberdelegation.

Preparing for Cyberdelegation and Its Risks

Automation in the administrative state could upset the relationship between people and their government.