As AI technology becomes more sophisticated, prediction markets, as a tool to measure public opinion and future events, have been increasingly used in daily life. But how does AI ensure that predictions are fair and accurate? Let’s start with the development of prediction markets and gradually deconstruct them.
How do prediction markets work?
Prediction markets actually have a long history, evolving from simple gambling to todays more complex technical tools. Now, many prediction markets rely on a protocol called Optimistic Oracle (OO for short) to process market results. For example, the famous UMA protocol serves markets like Polymarket. The process is not complicated: after the market is established, the system will wait for the proposer to submit an answer. If no one raises an objection to the answer within 2 hours, it will be confirmed; if there is a dispute, the system will reprocess it and may even upgrade it to a vote by UMA token holders.
In the prediction market, participants make predictions based on their own information and can profit from the results. Because everyones information comes from different sources, this information will be continuously integrated and updated in the market. Since participants all want to make more money, they will bet based on the truth as much as possible. This mechanism will allow the market to continuously present more real information.
Design advantages of prediction markets
The design of the prediction market determines that it is more objective than traditional media. Traditional media may be influenced by various positions and biases, but the prediction market encourages participants to seek the truth through economic incentives, rather than just expressing opinions.
Challenges of prediction markets
Although prediction markets can theoretically provide results that are close to the truth, there are still some loopholes in their actual operation, especially in settlement.
On the one hand, prediction markets are vulnerable to manipulation by large amounts of money, especially by purchasing large amounts of governance tokens to influence the results. For example, the trading volume of the 2024 US presidential election market was as high as $1.1 billion, and the price of the UMA token was about $2.76. If one person bought 51% of the governance tokens, he would only need about $170 million to manipulate the settlement results of the market and profit from it. The risk of this kind of economic manipulation is very high and will greatly reduce the fairness of the prediction market.
Second, humans have a herd mentality, which is particularly evident in the PoS consensus mechanism. Participants will follow the decisions of the majority rather than make independent judgments, especially when there are large market disputes. This group effect may cause market settlement to deviate from objective facts.
How does AI solve these difficulties? — Taking the US presidential election as an example
To solve these problems, AI settlement mechanism is one of the most effective solutions at present. By integrating AI settlement oracle into smart contracts, the prediction market can reduce human manipulation and ensure fairer results.
Take the prediction market for the 2024 US presidential election as an example. The trading volume is huge and there are many participants. Markets of this size can easily be manipulated or influenced by group decisions. However, by introducing AI settlement oracles, market settlement can become more fair and transparent.
First, AI’s automation and intelligent reasoning capabilities can make autonomous decisions based on evidence and data in the market, avoiding human interference. For example, when election results are controversial, AI can automatically make judgments based on existing evidence, rather than relying on the votes of individual token holders. This not only improves market fairness, but also reduces the trouble caused by disputes.
Moreover, AI settlement oracles can effectively prevent economic manipulation through decentralized reasoning and decision-making mechanisms, because AI will autonomously evaluate evidence in the market to ensure that settlement results are accurate. For major events such as the US presidential election, AI can make more objective inferences based on a large amount of historical data and market information to prevent large funds from controlling market results.
Third, AI’s decisions are based on data and evidence, rather than human subjective judgment. This avoids the bias caused by the herd effect. When the election results are controversial, AI can act as an independent and objective third party to provide more accurate settlement results, rather than relying on majority decisions under the PoS mechanism.
How to improve the accuracy of prediction markets?
The introduction of AI settlement oracles has added new possibilities for the future of prediction markets. Prediction markets combine human intelligence, machine intelligence, and incentive consensus systems to better reflect the direction of the real world and may also influence real-world decisions, such as overturning election results or becoming legal evidence.
AI settlement oracles are not only applicable to major events such as the US presidential election, but can also be applied to other complex prediction markets, such as economic trends and international situations. As the scale of the prediction market continues to expand, the use of AI will become increasingly indispensable, not only helping the market to expand in size, but also ensuring the accuracy and fairness of settlement results, providing protection for the healthy development of the market.
Summarize
Through automated intelligent decision-making, AI can not only effectively prevent economic manipulation and herd effects, but also ensure that market settlement is closer to the truth. This innovation can not only solve current market problems, but also provide unlimited possibilities for future expansion and application. So, did you use AI to predict the results of this years US election?
References:
https://mirror.xyz/orablog.eth/VlrdcPu7aUJkYUCiiPobUTxPsxoiSqL2 dKZMAyHOZYU