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.
Scholars present framework for the regulation of automated advisors in the financial services industry.
Rather than raising alarm bells, government uses of artificial intelligence fit well within existing legal frameworks.
Agencies, policymakers, and the courts can all address the risks associated with cyberdelegation.
Automation in the administrative state could upset the relationship between people and their government.