The Ph.D. program in Societal Computing

“Computing About and For Society”

The Ph.D. program in Societal Computing:

• Prepares students to be tomorrow’s leaders in designing, constructing and assessing technology that will transform society, business, policy, and law or be used to computationally reason about these complex socio-computational transformations.
• World-class interdisciplinary faculty
• Unique multi-disciplinary curriculum - focused on the cutting edge in computer science, statistical and network methods, theories and findings from the social, organizational, management and policy sciences.
• Engage in hands-on applications and cutting-edge research starting in year 1.
• Application areas include: privacy, dynamic social networks, link analysis, team and organizational performance, computer simulation, bio-surveillance, sustainability, electronic voting, and supply chain management, socio-technical ecosystems, and product development ecosystems.

Goals

The Ph.D. program in Societal Computing in the School of Computer Science at Carnegie Mellon University prepares students to be leading researchers. The program provides them with in-depth training not just in computation but also in fundamentals of relevant ways of looking at networks of people and organizations, and at their integration into management, law, and policy. The Ph.D. program in Societal Computing builds on a multi-discplinary team of world-class faculty. It exposes students to traditional tenets of computer science interwoven with interdisciplinary coursework, hands-on applications and cutting-edge research.

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, and platform-based product ecosytems. Attacking these new problems requires profound understanding of computation and the interplay between the managerial, personal and policy networks in which technology operates. Current degree programs in traditional disciplines such as computer science, policy and management fail to provide the kind of multi-disciplinary curriculum needed to train tomorrow’s leaders in these emerging areas. Today’s demand for integrated expertise far exceeds supply, and continues to grow, it becomes increasingly important to offer a PhD program that fills the void.

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 Societal Computing 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.