Prediction markets in 2026 will be larger than they are today. Already used extensively for major elections and global events, more complex, interconnected events will start to be covered, making real-time information increasingly useful.
According to Andy Hall, an advisor to a16z Crypto and a Stanford professor, more contracts will unlock implicit social trends and outcome probabilities. But with this comes the question of how transparent they are and how we can verify what they depict.
Disputed events will be settled with the help of decentralized governance and AI-powered oracles. The Zelensky lawsuit and the Venezuelan election are examples from past market controversies that really highlight the need to relativize, depending exclusively on centralized decisions.
AI agents can scan many data sources to find new predictors for social events and offer new ways to forecast results. This does not replace traditional polling; prediction markets will work with it, using crypto tools to prove that survey participants are real humans and to give verifiable signals.
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For a long time, cryptographic proofs like SNARKs were only run on blockchains because running anywhere else was too expensive.
Justin Thaler, from a16z and Georgetown University, said this is changing thanks to zkVM provers. They cut the overhead to roughly 10,000 times lower and keep the memory use manageable.
This jump enables real-time, verifiable cloud computing. For the first time, companies and individuals who run CPU tasks in the cloud have a way to prove the correctness of computations without special GPU setups.
While the proofs are optimized for GPUs, they can run on regular devices, meaning industries beyond blockchain can use these tools for auditing, security, and trust in computations.
Traditional media have often been criticized for bias and not being accountable. In 2026, a new idea called “staked media” will arise.
By utilizing tokenized assets, programmable lockups, and on-chain histories, creators and analysts can publicly back their claims with financial commitments.
This creates a self-interested text that the readers can trust, because it can be verified. At a time when AI-generated media supports propagating disinformation, staked media complements rather than replaces traditional media.
It introduces a new level of credibility assessment, which is dependent on what participants put at risk. Podcasters, analysts, and commentators can demonstrate their care for accuracy by being transparent to their audience in real-time ways.
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