Deconstructing Data Mining: Protecting Privacy and Civil Liberties in Automated Decision-Making
Year: 2016
Type: preprint
Abstract: “Big Data” is the bogeyman of the information age: powerful, and as ill-defined as it is abstractly threatening. The belief in the prescient value of big data has led to widespread collection of information on citizens and consumers in both the public and private sectors, though that distinction has become increasingly permeable. Data brokers, companies that create and sell detailed profiles of consumers for profit, sell their products to private and public entities alike, and often do not have data quality control clauses in the contracts governing those interactions.These profiles also often refer directly or indirectly to sensitive attributes, such as race, gender, age, and socioeconomic status. This brave new world of big data is no longer new. But the mechanics of the algorithms relying on that data, and the process by which decisions are made using that information, merit a sharpened focus. The following will provide an overview on the basics of algorithms and data mining, and explore how automated decision-making can unintentionally reveal sensitive information, or unintentionally base its predictions on protected traits, implicating individual privacy and civil liberties.
Source: SSRN Electronic Journal
Author: Lindsey Barrett
Institution: Georgetown University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3127101559