Fixing Cash Aid Is More Than Child’s Play
Streamlining administration of cash aid requires substantial legal and regulatory reform.
Alternatives to Data Sharing
Data sharing is not always required when firms use information to their advantage.
Machine Learning Could Make Government More Incomprehensible
Misaligned incentives can encourage incomprehensibility.
Procuring the Algorithmic State With Better Policy Analysis
Scholars assert that government agencies need a policymaking mindset when purchasing machine learning technology.
Artificial Intelligence in Government and the Law
Scholars analyze how artificial intelligence stands to disrupt the public and legal sectors.
Using Machine Learning to Improve the U.S. Government
Governmental use of artificial intelligence can fit well within existing administrative law constraints.
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.