Law Commons^™

The Prediction Society: Algorithms And The Problems Of Forecasting The Future, Hideyuki Matsumi, Daniel J. Solove

GW Law Faculty Publications & Other Works

Predictions about the future have been made since the earliest days of humankind, but today, we are living in a brave new world of prediction. Today’s predictions are produced by machine learning algorithms that analyze massive quantities of personal data. Increasingly, important decisions about people are being made based on these predictions.

Algorithmic predictions are a type of inference. Many laws struggle to account for inferences, and even when they do, the laws lump all inferences together. But as we argue in this Article, predictions are different from other inferences. Predictions raise several unique problems that current law is ill-suited …

Using Ai To Reduce Performance Risk In U.S. Procurement, Jessica Tillipman

GW Law Faculty Publications & Other Works

In recent years, several U.S. government agencies have pioneered the use of artificial intelligence (AI) and other emerging technologies to improve the efficiency and accuracy of their "responsibility determinations" (reviews of, among other things, contractor representations and certifications, past performance history, civil and criminal settlements, exclusions (such as suspensions or debarments), and contract terminations). As federal agencies continue to think strategically about how to improve processes and reduce risk in their procurements, technology-driven solutions will play a critical role in this undertaking.

The Impending Judicial Regulation Of Artificial Intelligence In The Administrative State, Aram A. Gavoor

GW Law Faculty Publications & Other Works

Artificial Intelligence (AI) algorithms are being deployed in executive branch agencies at a brisk pace and with no executive branch account for their use. The proliferation of AI in government raises civil rights concerns because it has been found—at a general level—to succumb to racial and gender biases when AI algorithms are incompetently or intentionally trained. Policy solutions have been put forth to mitigate the issue of such AI uses in government, some of which are in the process of being implemented. Despite these gains, the political branches of the federal government have limited time to act before their primary …