One of the central challenges for blockchain-based decentralized applications is what’s known as the oracle problem. Blockchains are closed systems with no knowledge of the outside world; if an application or smart contract wants to reference data that isn’t on the blockchain itself, it must rely on a trusted bridge to deliver that information from the real world to the blockchain. These bridges are known as oracles, and they can often be the weakest or most centralized part of an otherwise fully decentralized system. Blockchain applications that rely on oracles must find ways to minimize the amount of trust required in the bridge that delivers the information, so that they can have confidence that the information brought on-chain reflects reality and isn’t subject to censorship or manipulation.
For blockchain-based decentralized prediction markets like PredIQt, the oracle problem is especially relevant. Nearly every market that is created will likely reference events or data that exist outside the blockchain — political elections, sports matches, asset prices, and more. In order for a market to be resolved, there needs to be some source of truth (the oracle) that takes that outside source of information and logs it on-chain in order to trigger the payout of the smart contract. Centralized prediction markets simply rely on their operating company to resolve markets. This model creates a single point of failure that can be manipulated or censored. In order to avoid those issues, decentralized markets like PredIQt must use new models to ensure accurate information reporting without a central source of authority.
In this article, we’ll provide an overview of the PredIQt approach to oracles. We will discuss the oracle system that we’ve put in place for the beta launch of PredIQt, as well as the various other models that we will integrate and experiment with in the near future.
One of our key learnings from observing other...