Information Dynamics in the Networked World
Guest Editors: B. Huberman, HP Labs, CA and J. Ledyard CalTech, CA

Foreword by Kenneth Arrow, Prof of Economics (Emeritus), Stanford University, CA

1. Information Dynamics in the Networked World: Introduction
by B. Huberman, HP Labs, CA and J. Ledyard, CalTech, CA

2. Internet Privacy and Security: A Startup’s Perspective
by Stephen Hsu, Co-founder and Chairman, SafeWeb, Inc., Professor of Theoretical physics, University of Oregon, OR

ABSTRACT:
SafeWeb, a venture-backed startup founded by a team of physics PhDs, created a widely used Internet privacy service which was used by millions of people worldwide. Despite widespread adoption, its advertising-based business model proved unsupportable, and the service was discontinued in late 2001. SafeWeb’s main product now is a hardware device based on its core technology (the Secure Extranet Appliance), which is used by enterprise security customers such as corporations and government agencies. I discuss my experiences as co-founder of SafeWeb, and topics such as the Internet in China and the future of privacy in the information age.

3. Shock: Aggregating Information While Preserving Privacy
by Eytan Adar, Rajan Lukose, Caesar Sengupta, Josh Tyler, Nathaniel Good; Information Dynamics Lab, HP Laboratories, CA

ABSTRACT
An important problem facing large, distributed organizations is the efficient management and distribution of information, knowledge, and expertise. In this paper we present the design and implementation of a low-cost, extensible, flexible, and dynamic peer-to-peer (P2P) knowledge network that helps address this problem. This system, known as Shock, is designed to protect the privacy of user’s personal information, such as email, web browsing habits, etc., while making that information available for knowledge management applications. It reduces participation costs for such applications as expert finding, allows highly targeted messaging, and enables novel kinds of ad hoc conversation and anonymous messaging. The system is tightly integrated with users’ email clients, taking advantage of email as habitat.

4. Pricing Network Services
by  Jun Shu and Pravin Varaiya; UC Berkeley, CA

ABSTRACT
We propose a pricing mechanism for statistically guaranteed service in packet switched networks. The mechanism provides congestion control and efficient resource allocation. For users, the mechanism offers better quality and lower price. Service providers can base service and revenue models in the mechanism. We apply this mechanism to the Internet.

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6. Eliminating Public Knowledge Biases in Small Group Predictions
by Kay-Yut Chen, Leslie R. Fine and Bernardo A. Huberman; HP Laboratories, CA 

ABSTRACT
We present a novel methodology for identifying public knowledge and eliminating the biases it creates when aggregating information in small group settings.  A two-stage mechanism consisting of an information market and a coordination game is used to reveal and adjust for individuals’ public information.  A nonlinear aggregation of their decisions then allows for the calculation of the probability of the future outcome of an uncertain event, which can then be compared to both the objective probability of its occurrence and the performance of the market as a whole.  Experiments show that this nonlinear aggregation mechanism outperforms both the imperfect market and the best of the participants. 

7. Information Aggregation in Double Auctions: Rational Expectations and the Winner’s Curse
by Serena Guarnaschelli †, California Institute of Technology, CA; Anthony M. Kwasnica* Penn State University, PA; Charles R. Plott ‡, California Institute of Technology, CA

ABSTRACT
This paper inquires about the ability of double auction institutions to aggregate information in the context of a “common value” information structure that is known to produce the winner’s curse in sealed bid environments. While many fundamental features of the economic environment are different from those studied in the context of sealed bids, the pattern of information distributed to the population of traders is the same. This gives us an opportunity to determine if the behaviors reported in sealed bid environments can be detected in the more active market environment. As such the experiments are also a test of the robustness of earlier experiments that demonstrate that in economies with homogeneous preferences similarities single compound securities organized by double auctions are able to aggregate information. The basic result is that a severe winner’s curse is not observed. The irrationality observed in sealed bids does not extend itself to the double auction environment. Information aggregation is observed and the rational expectations model receives support.

8. Prediction Markets as Decision Support Systems
by Joyce Berg and Thomas Reitz ; Tippie College of Business, University of Iowa, IA

ABSTRACT
Valuations from “prediction markets” reveal expectations about the likelihood of events. “conditional prediction markets” reveal exceptions conditional on other events occurring. For example, in 1996, the Iowa Electronic markets ran markets to predict the chances that different candidates would become the Republican Presidential nominee. Other markets predicted the vote shares that each party would receive conditional on the Republican Nominee chose. Here, using these markets as examples, we show how such markets could be used for decision support. In this case, Republicans could have inferred that Dole was a weak candidate and that his nomination would result in a Clinton victory. This is only one example of the widespread potential for using specific decision support markets.

9. The Effect of Electronic Markets on Forecasts of New Product Success
by Thomas S. Gruca, Joyce Berg, Michael Cipriano, Tippie College of Business, University of Iowa, IA

ABSTRACT
In this paper, we extend field experiments of real money prediction markets to the problem of forecasting the success of a new product.   We collect forecasts using a traditional survey mechanism and a market mechanism.  Our results suggest that market prices summarize the information contained in survey forecasts and improve those forecasts by reducing the variability of the forecast.  However, we find no evidence of a “crystal ball” equilibrium.  Our markets have considerable variability and predict only as well as the public signal provided by the HSX movie market game.

10. COMBINATORIAL INFORMATION MARKET DESIGN
by Robin Hanson, George Mason University, VA

ABSTRACT
Information markets are markets created to aggregate information. Such markets usually estimate a probability distribution over the values of some variable, via bets on those values. Combinatorial information markets would aggregate information on the entire joint probability distribution over many variables, by allowing bets on all variable value combinations. To achieve this, we want to overcome the thin market and irrational participation problems that plague standard information markets. Scoring rules avoid these problems, but suffer from opinion pooling problems in the thick market case. Market scoring rules avoid all these problems, by becoming automated market makers in the thick market case, and simple scoring rules in the thin market case. Logarithmic versions have cost and modularity advantages. After introducing market scoring rules, we consider several design issues, including how to represent variables to best support both conditional and unconditional estimates, how to avoid becoming a money pump via errors in calculating probabilities, and how to ensure that users can cover their bets, without needlessly preventing them from using previous bets as collateral for future bets.