Communication With Unknown Perspectives (original) (raw)

Perspectives, Opinions, and Information Flows

SSRN Electronic Journal, 2000

Consider a group of individuals with unobservable perspectives (subjective prior beliefs) about a sequence of states. In each period, each individual receives private information about the current state and forms an opinion (a posterior belief). He also chooses a target individual whose opinion is then observed. This choice involves a fundamental trade-off between well-informed targets, whose signals are precise, and well-understood targets, whose perspectives are well known by the observer. Observing an opinion provides information not just about the current state, but also about the target's perspective; hence observed individuals become better-understood over time. This leads to path dependence and the possibly that some individuals never observe certain others in the long run. We identify a simple condition under which long-run behavior is efficient and history-independent. When this condition fails, with positive probability, a single individual emerges as an opinion leader in the long-run. Moreover, the extent to which an individual learns about a target's perspective depends on how well-informed both agents are in the period of observation. This gives rise to symmetry breaking, and can result in observational networks involving information segregation, or static graphs with rich and complex structures. * We thank Daron Acemoglu and Sanjeev Goyal for helpful suggestions, and the Institute for Advanced Study at Princeton for hospitality and support.

Ignorance and Bias in Collective Decision

2014

We study theoretically and experimentally a committee with common interests. Committee members do not know which of two alternatives is the best, but each member can acquire privately a costly signal before casting a vote under either majority or unanimity rule. In the experiment, as predicted by Bayesian equilibrium, voters are more likely to acquire information under majority rule, and attempt to counter the bias in favor of one alternative under unanimity rule. As opposed to Bayesian equilibrium predictions, however, many committee members vote when uninformed. Moreover, uninformed voting is strongly associated with a lower propensity to acquire information. We show that an equilibrium model of subjective prior beliefs can account for both these phenomena, and provides a good overall fit to the observed patterns of behavior both in terms of rational ignorance and biases.

Ignorance and bias in collective decisions

Journal of Economic Behavior & Organization, 2016

We study theoretically and experimentally a committee with common interests. Committee members do not know which of two alternatives is the best, but each member can acquire privately a costly signal before casting a vote under either majority or unanimity rule. In the experiment, as predicted by Bayesian equilibrium, voters are more likely to acquire information under majority rule, and attempt to counter the bias in favor of one alternative under unanimity rule. As opposed to Bayesian equilibrium predictions, however, many committee members vote when uninformed. Moreover, uninformed voting is strongly associated with a lower propensity to acquire information. We show that an equilibrium model of subjective prior beliefs can account for both these phenomena, and provides a good overall fit to the observed patterns of behavior both in terms of rational ignorance and biases.

Opinion Formation by Informed Agents

Journal of Artificial Societies and Social Simulation, 2010

Opinion formation and innovation diffusion have gained lots of attention in the last decade due to its application in social and political science. Control of the diffusion process usually takes place using the most influential people in the society, called opinion leaders or key players. But the opinion leaders can hardly be accessed or hired for spreading the desired opinion or information. This is where informed agents can play a key role. Informed agents are common people, not distinguishable from the other members of the society that act in coordination. In this paper we show that informed agents are able to gradually shift the public opinion toward a desired goal through microscopic interactions. In order to do so they pretend to have an opinion similar to others, but while interacting with them, gradually and intentionally change their opinion toward the desired direction. In this paper a computational model for opinion formation by the informed agents based on the bounded confidence model is proposed. The effects of different parameter settings including population size of the informed agents, their characteristics, and network structure, are investigated. The results show that social and open-minded informed agents are more efficient than selfish or closed-minded agents in control of the public opinion.

Ignorance and bias in collective decision:Theory and experiments

2014

We consider a committee with common interests. Committee members do not know which of two alternatives is the best, but each member may acquire privately a costly signal before casting a vote under either majority or unanimity rule. In the lab, as predicted by Bayesian equilibrium, voters are more likely to acquire information under majority rule, and attempt to counter the bias built in favor of one alternative under unanimity rule. As opposed to Bayesian equilibrium predictions, however, some committee members vote for either alternative when uninformed. Moreover, uninformed voting is correlated with a lower disposition to acquire information. We show that an equilibrium model of subjective prior beliefs may account for this correlation, and provides a good fit for the observed patterns of behavior both in terms of rational ignorance and biases.

Ignorance and Bias in Collective DECISIONS1

2014

We study theoretically and experimentally a committee with common interests. Committee members do not know which of two alternatives is the best, but each member can acquire privately a costly signal before casting a vote under either majority or unanimity rule. In the experiment, as predicted by Bayesian equilibrium, voters are more likely to acquire information under majority rule, and attempt to counter the bias in favor of one alternative under unanimity rule. As opposed to Bayesian equilibrium predictions, however, many committee members vote when uninformed. Moreover, uninformed voting is strongly associated with a lower propensity to acquire information. We show that an equilibrium model of subjective prior beliefs can account for both these phenomena, and provides a good overall fit to the observed patterns of behavior both in terms of rational ignorance and biases.

False Consensus, Information Theory, and Prediction Markets

arXiv (Cornell University), 2022

We study a setting where Bayesian agents with a common prior have private information related to an event's outcome and sequentially make public announcements relating to their information. Our main result shows that when agents' private information is independent conditioning on the event's outcome whenever agents have similar beliefs about the outcome, their information is aggregated. That is, there is no false consensus. Our main result has a short proof based on a natural information theoretic framework. A key ingredient of the framework is the equivalence between the sign of the "interaction information" and a super/sub-additive property of the value of people's information. This provides an intuitive interpretation and an interesting application of the interaction information, which measures the amount of information shared by three random variables. We illustrate the power of this information theoretic framework by reproving two additional results within it: 1) that agents quickly agree when announcing (summaries of) beliefs in round robin fashion [Aaronson 2005]; and 2) results from [Chen et al 2010] on when prediction market agents should release information to maximize their payment. We also interpret the information theoretic framework and the above results in prediction markets by proving that the expected reward of revealing information is the conditional mutual information of the information revealed.

Dynamic Opinion Aggregation: Long-run Stability and Disagreement∗

2021

This paper proposes a general model of non-Bayesian social learning in networks that accounts for heuristics and biases in opinion aggregation, as well as the coexistence of layers of networks corresponding to different interaction levels. We provide conditions on the layers of networks that guarantee opinions’ convergence, consensus formation, and effi cient or biased information aggregation. Under the descriptive phenomena that we capture, at times agents ignore some of their neighbors’opinions, reducing the number of effective connections. This generates new channels toward the formation of disagreement and polarization of opinions in networks. Moreover, we show that our class of updating procedures precisely characterizes agents’optimal behavior in response to a concern of disagreeing with others. Our framework bridges several scattered models and phenomena in the non-Bayesian social learning literature, thereby providing a unifying approach to the field. JEL: D81, D83, D85

Expertise and Bias in Decision Making

2004

In this paper, we develop a model of a decision maker using an expert to obtain information. The expert is biased toward some favoured decision but cares also about its reputation on the market for experts. We then analyse the corresponding decision game depending on the nature of the informational linkage with the market. In the case where the expert is biased in favour of the status quo, the final decision is always biased in the same direction. Moreover, it is better to rely on experts biased against the status quo. We also show that it is optimal to publically disclose the expert report. Finally, we prove that the intuitive results that hiring an honest inside expert raises the outside expert's incentives to report truthfully holds when reports are public but not when they are secret.

Information Sampling, Conformity and Collective Mistaken Beliefs

Societies sometimes stick to the status quo instead of switching to superior technologies and institutions. Existing explanations often attribute this to a coordination failure due to payoff externalities: people may know that another alternative is superior but nobody has an incentive to switch unless many others do so. We show that a simple learning argument can provide an alternative explanation. When people learn about the alternatives from their own experiences but tend to adopt the behaviors of others, they will mistakenly learn to believe that a popular alternative is superior to a better, but unpopular alternative. Our model neither assumes that agents engage in motivated cognition nor that they transmit mistaken information to others. Rather, it emphasizes the role of a fundamental asymmetry in access to information about popular versus unpopular alternatives. Our model thus provides a novel, sampling-based, explanation of how conformity in behavior can lead to private acce...