Research in SISL
The interplay of algorithmic, economic, and social systems is now fundamental to a variety of new services and marketplaces, such as online and advertising auctions, social networks, electricity markets, cloud computing, and even privacy. The Social and Information Sciences Laboratory - SISL, pronounced "sizzle" - studies how markets and other social systems function in a world in which economics can no longer be separated from the information and communication systems around us.
To address this interplay, SISL brings together researchers from economics, computer science, engineering, and mathematics in a truly interdisciplinary environment (given the 10+ years that SISL has been active, it is sometimes hard to tell the computer scientists from the economists and vice versa). These SISL researchers strive to improve the basic sciences of complex markets and social/communication networks while helping to develop our understanding of the emerging interaction between the two.
Some of the specific topics being investigated by SISL researchers include:
Sensitive information is held by an enormous variety of entities, particularly in today's online world. Some of the challenges in handling it include developing principled models and definitions for privacy guarantees, along with privacy-preserving algorithms and provable bounds on how information privacy can be traded off against its usefulness. Integrating notions of privacy into utility theoretic and decision theoretic frameworks will provide us with more sophisticated means of reasoning about sensitive information. Work in this area is led by Katrina Ligett and Federico Echenique.
Social and Economic Networks
The precise structure of social interactions can impact a variety of behaviors and outcomes – learning a new computer or spoken language may depend on the number of acquaintances who already know it, information about job openings may flow through word-of-mouth interactions, financial investments and outcomes may depend on the underlying connections between firms, etc. These observations have opened the door to an array of theoretical and empirical questions: How do individuals and organizations strategically interact with neighbors on complex social and economic networks? What are network architectures that are more conducive to diffusion of behavior and financial outcomes? How do we quantify the impacts of these networks on outcomes using field and experimental data? Work in this area is led by Leeat Yariv, Matt Elliott, and Omer Tamuz.
Rethinking Electricity Markets
Over the coming decade, the electricity network will undergo a complete architectural transformation, similar to what has happened to the communication network over the last decades. However, there are huge engineering and economic challenges in making this transformation possible. A key challenge for this transformation is the fact that the economic market structure and engineering architecture are inherently intertwined in the electricity grid, which necessitates a new architectural theory for guiding this transformation. Work in this area is led by Mani Chandy, Adam Wierman, John Ledyard, and Steven Low. More details can be found at the Smart grid project page and the Resnick Institute website.
It is almost impossible to study computer networks today without considering economic issues. Economics plays a defining role in routing (e.g., hot potato routing and net neutrality) and further, economics has come to play a major role in how protocols are designed and analyzed (e.g., the analysis of TCP and the design of BitTorrent). In fact, even the study of cloud computing cannot be isolated from the strategic economic interactions with respect to pricing and provisioining between infrastructure providers and the services that run on top of them. Work in this area is led by Adam Wierman, Steven Low, and Matt Elliott.
Extracting revenue from search algorithms increasingly depends on sophisticated computational algorithms for advertising. Many of these algorithms are based on auction theory. Research in this area thus requires very close interaction between computation and economics. Caltech was at the forefront of computational advertising right from the inception of its use on the internet. Our involvement began with work on the generalized second price auction in concert with Goto.com (which morphed into Overture, which morphed into Yahoo), the company that originated the use of auctions for location on search results pages. This work was both theoretical and experimental and was led by Matthew Jackson, John Ledyard, and Simon Wilkie. Later work on more advanced and computationally intensive advertising work was led by Preston McAfee for webpages and John Ledyard for television and radio advertising.