COLLOQUIUM
Department of Computer Science and Engineering
University of South Carolina
 
Accountable Surveillance for
a Safe Brave New World

András Lorincz

Faculty of Informatics
Eötvös University

Date: August 25, 2006
Time: 1000-1100
Place: Swearingen 2A22

Abstract

The advent of technology may lead to unprecedented changes in social
networks. Therefore it is important to find methods that can detect
trends, anomalies and emergence of complex phenomena and can
characterize and forecast the dynamics, the evolution and the
interaction of networks. We also need methods that can influence these
networks and need to consider the influence of technology on social
networks. We should use our ethical imagination about decision making
in social networks. Intriguingly, these are core questions for
information science today. As an example, I will consider if one could
design a “Safe Brave new World” (SBW) that has the following
properties: (Property 1) it abides by the rules of the democracy game,
(Property 2) it executes the law with the power of the “Big
Brother,” and (Property 3) it preserves privacy.  I shall argue
that properties (1), (2), and (3) contradict each other, and that the
contradiction makes SBW feasible. The key is “Accountable
Surveillance,” which applies Blind Data Mining in an anonymous but
accountable self-organizing community.

András Lorincz has been a professor and senior researcher at the
Faculty of Informatics at Eötvös University, Budapest since 1998.  His
research focuses on distributed intelligent systems and their
applications in neurobiological and cognitive modeling, as well as
medicine. He founded the Neural Information Processing Group of Eötvös
University and directs a multidisciplinary team of mathematicians,
programmers, computer scientists and physicists. He acted as the PI of
several successful international projects in collaboration with
Panasonic, Honda Future Technology Research and the Information
Directorate of the US Air Force in the fields of hardware-software
co-synthesis, image processing and human-computer collaboration. He
graduated in physics and received his PhD degree at the Eötvös Loránd
University. He conducted research and taught at the Hungarian Academy
of Sciences, University of Chicago, Brown University, Princeton
University, the Illinois Institute of Technology and ETH Zurich. He
authored about 200 peer reviewed scientific publications. He has
received the Széchenyi Professor Award, Master Professor Award and the
Széchenyi István Award in 2000, 2001, and 2004, respectively. Four of
his students won the prestigious Pro Scientia Gold Medal in the field
of information science over the last 4 years. In 2004, he was awarded
the Kalmár Prize of the John von Neumann Computer Society of Hungary.