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Blockchain Information Finance: From Prediction Market to Widespread Governance Applications
From Prediction Markets to Information Finance: A New Paradigm for Blockchain Applications
Prediction markets, as an important branch of blockchain applications, are gradually maturing. As an early supporter of prediction markets, I have been closely following the development of this field. The recent U.S. elections have once again fueled the excitement around prediction markets, attracting not only profit-seeking participants but also becoming an important channel for many to obtain information. Prediction markets combine on-chain funds with real-world predictions, showcasing immense potential.
This article will explore the concept of "information finance" behind prediction markets and its prospects for application in broader fields. I believe:
The current prediction market is already a very useful tool;
The prediction market is just a pioneer in the emerging field of "information finance" and is expected to be applied in various aspects such as social media, scientific research, news reporting, and public governance in the future.
The Dual Value of Prediction Markets
Taking a certain prediction market platform as an example, it played an important role in the recent U.S. elections. Not only did it accurately predict the election results, but it also quickly reflected the real situation after the results were announced, being more objective and timely than many professional analyses and news reports.
What's even more interesting is its performance during the presidential election in Venezuela. At that time, there was over $100,000 in funds on the platform betting on the opposition's chances of winning at 23%, which caught my attention. Although Maduro ultimately remained in power, the market data made me realize that this opposition attempt was serious, and there were indeed large-scale protests and organized actions. Without the initial signals from the platform, I might have completely overlooked this significant event.
Of course, we should not fully rely on prediction market data, nor should we blindly trust news reports. The best approach is to combine both: when we see sensational news, we can check the market data as a reference; when the market experiences abnormal fluctuations, we need to delve into the reasons behind them. In this way, we can obtain more comprehensive and accurate information.
For ordinary users, prediction market platforms can serve as both gambling websites and news information platforms. Personally, I have incorporated viewing platform data as part of my information-gathering process, alongside traditional media and social media. This approach helps me to acquire and analyze information more effectively.
The Broad Prospects of Information Finance
Predicting election outcomes is just one application scenario of information finance. The broader concept is to use financial mechanisms as incentives to provide users with valuable information. Although all financial activities are inherently related to information, information finance places more emphasis on structured design:
First, identify the facts you want to understand;
Then carefully design the market mechanism to optimally acquire that information from participants.
In addition to prediction markets, decision markets are also a typical application. By establishing conditional markets, the expected outcomes of different decision schemes can be assessed. This mechanism is expected to play an important role in areas such as corporate governance and public policy formulation.
In the next ten years, artificial intelligence is likely to have a huge impact on information finance. AI can significantly reduce the operational costs of the market, enabling high-quality information to be obtained even on micro issues with very low trading volumes. This will greatly expand the application scope of information finance.
The Application of Information Finance in Governance
Information finance provides new ideas for decentralized governance. For example, human judgment can be "refined" through prediction markets. The specific approach is to establish a prediction market for each decision, predicting what results would come from invoking an expensive human judgment mechanism. In most cases, it is sufficient to rely on market predictions, and only in very rare cases is human judgment actually triggered, with rewards and punishments for participants based on this outcome.
This mechanism can provide an efficient decision-making solution for DAOs. By using prediction markets, it is possible to significantly reduce voting costs and participation thresholds while maintaining decision quality. The key lies in the balance between market mechanisms and non-market trust mechanisms: the market acts as the "engine", while other mechanisms serve as the "steering wheel".
Other Potential Applications of Information Finance
Personal tokens: By improving economic design, it can better address issues such as talent discovery.
Advertising: Based on signals from users' actual purchasing behavior, helping people make better purchasing decisions.
Scientific peer review: Identify research results that need to be revalidated through prediction markets to improve research quality.
Public goods funding: Distributing funds more fairly by tracking the entire dependency graph, avoiding "popularity contests".
Conclusion
Although these ideas have existed for many years, I believe that information finance has great potential in the current decade, mainly for the following reasons:
Information finance can solve trust issues in reality, especially in fields such as politics, science, and business.
Scalable blockchain technology provides the infrastructure support to realize these ideas.
The development of artificial intelligence has made it possible to establish effective markets even for small-scale issues.
In the future, artificial intelligence and humans are likely to participate together in these markets. To fully seize this opportunity, we need to go beyond simple election predictions and explore the broader application prospects of information finance.