Transparent accountable inferencing for privacy risk management

Abstract

There is an urgent need for transparency and accountability for government use of large-scale data mining systems for law enforcement and national security purposes. We outline an information architecture for the Web that can provide transparent access to reasoning steps taken in the course of data mining, and accountability for use of personal information as measured by compliance with rules governing data usage. Legislative debates and judicial oversight will determine how large and how fast the expansion of data mining power available to homeland security and crime prevention efforts will be. Our approach to the privacy challenges posed by data mining is to concentrate on transparency and accountability in the use of personal information. As technology designers, we can help society feel more certain that data mining power is used only in legally-approved ways, and that the data that may give rise to adverse consequences for individuals is based on inferences that are derived from accurate data. We can meet these goals by making sure that the architecture of new Web technologies provides transparency into the inferencing mechanisms and creates technical means for assuring that government data mining efforts are accountable for improper use of data.