The Prediction Society: AI and the Problems of Forecasting the Future

Speakers: Hideyuki Matsumi and Daniel J. Solove 

Matsumi is a PhD candidate/researcher at the Research Group on Law Science, Technology and Society (LSTS) as well as at the Health and Ageing Law Lab (HALL) of the Vrije Universiteit Brussel (VUB)

Solove is the Eugene L. and Barbara A. Bernard Professor of Intellectual Property and Technology Law at George Washington University Law School

Today’s predictions are produced by machine learning algorithms that analyze massive quantities of data, and increasingly, important decisions about people are being made based on these predictions. Algorithmic predictions are a type of inference, but predictions are different from other inferences and raise several unique problems. More broadly, the rise of algorithmic predictions raises an overarching concern: Algorithmic predictions not only forecast the future but also have the power to create and control it. Data protection/privacy law do not adequately address these problems. Many laws lack a temporal dimension and do not distinguish between predictions about the future and inferences about the past or present.  We argue that the use of algorithmic predictions is a distinct issue warranting different treatment from other types of inference.