Motivation
The past decade has seen a tremendous increase in both the breadth
and the complexity of computational systems society has come to rely
on. This increase in turn is giving rise to a number of new and challenging
societal, management and policy issues, which themselves often call
for new technological innovations. Examples include privacy rights management,
data privacy, electronic market mechanisms and automated negotiation,
dynamic network modeling, online dispute resolution, etc. Attacking
these new problems requires profound understanding of computation and
the interplay between the managerial, personal and policy networks in
which technology operates. Unfortunately, current degree programs in
traditional disciplines (e.g. computer science, policy or management)
fail to provide the kind of multi-disciplinary curriculum needed to
train tomorrow’s leaders in this emerging area. Today’s
demand for integrated expertise far exceeds supply. As demand for this
new breed of researchers continues to grow, it becomes increasingly
important to offer a PhD program that fills the void.
There is a general lack of understanding by computer scientists of social,
economic and policy issues impacted by computational systems. Yet, increasingly
more and more ACM and IEEE computer science conferences and journals,
as well as traditional funding sources, focus on work that integrates
these disciplines. The Privacy in D.A.T.A. workshop held at Carnegie
Mellon University in March 2003 brought together some of the world’s
leading computer science theorists to examine data privacy problems;
the biggest hurdle was helping these computer scientists understand
the personal, organizational and policy settings in which well-defined
theoretical computer science problems related to data privacy exist.
Similarly, multi-agent research has increasingly had to combine methods
of social and economic science with computer science, and, conversely,
social and economic sciences are increasingly turning to multi-agent
modeling for solutions to problems that elude traditional analytical
methods. Dynamic network analysis, multi-agent systems, market mechanisms
and privacy-preserving data mining, to name just a few, have become
major themes at ACM, IEEE, and AAAI conferences. Yet, while computer
science researchers are increasingly asked to address or integrate social,
economic or legal dimensions into the emerging technologies they develop,
traditional doctoral programs continue to emphasize computation as a
standalone discipline and ignore its many social, economic and policy
ramifications. In contrast, the PhD program in Computation, Organizations
and Society (COS) is a computer science based cross-disciplinary program
that aims to train computer scientists to understand the bigger picture
in which computation operates and to create technology from this broader
vantage point.
