People worldwide will ask key questions in 2024. Who’ll become the next U.S. President? Which athlete will set the highest number of records at the Paris Olympics? Will BTC’s market price cross $100K post-halving? And so on.
It’s the year prediction markets — ‘the holy grail of epistemics technology’ in Vitalik’s view — could reach their full potential. Progressive governance models, like Futarchy, can finally ensure better policies and resource usage at scale.
Bitwise’s ‘10 Crypto Predictions for 2024’ thus showcased prediction markets as the new ‘killer app’ for crypto. It also estimated a $100+ million capital inflow into this sector.
Can Web3 prediction markets meet this demand? Yes. The underlying tech stack has become performant enough for intent-centric asset trading. While next-gen platforms like PredX use AI for deeper markets, better information access, and sustainable incentives.
Investors and end-users have shown confidence in such innovations. PredX thus raised $500K in pre-seed funding and attracted over 60K+ active users in the second month after launch.
Four Problems, One Solution
Vitalik’s bullish case for prediction markets is based, partly, on its ability to accommodate ‘AI as a player in the game.’ PredX executes on this premise, using blockchain-powered ‘AI Agents’ to overcome the major challenges to mass retail participation in prediction markets.
Not Enough Events
Traditionally, maintaining a steady event supply is also highly resource-intensive for creators. Besides finding events, they must understand the community well enough to ensure high participation and trading volumes.
AI Agents, however, are willing to work at less than $1/hour. Moreover, PredX uses generative AI engine to enable systems for AI and humans to efficiently co-create events and solve tasks. These broaden the scope for event discovery by analyzing multiple news sites, social channels, forums, past market interactions, etc., to suggest better, more diverse, and potentially high-engagement topics.
Sub-par Engagement
Since creators in traditional prediction markets can’t achieve the ideal level of insight into the community’s beliefs, interests, etc., their recommendation models are mostly inadequate.
PredX’s targeted recommendation engine uses AI Agents to serve highly relevant topics based on users’ interest graphs and trading histories, besides cultural icons, regional trends, and more. This ensures buzzing prediction markets that benefit every stakeholder.
Humans and AI participating in adversarial games in open-world scenarios is another level where PredX improves the scope for engagement. Though the winner takes all, there’s a level playing field and incentives for all parties, humans or AI.
Low Event Liquidity
Ensuring adequate liquidity for both ‘Yes’ and ‘No’ parties to trade smoothly is a big challenge for prediction markets. Known as the thin markets problem, this particularly affects niche events. It either discourages participation altogether or increases exit risks for traders.
The popular Logarithmic Market Scoring Rule (LMSR) is not enough for new-age prediction markets. AI Agents thus use more advanced, reinforcement learning or meta-learning algorithms. It allows the PredX platform to automatically allocate event liquidity from on-chain Liquidity Providers (LPs). LPs receive token rewards for their contributions.
Limited Information
Like liquidity, events in prediction markets must have enough information to pique users’ interest and help them make informed choices. This, again, can easily become economically restrictive and unfeasible for non-AI models.
Hallucinations in ‘black-box AI’ further complicate the issue. There’s a lack of solid evidence to support decisions. It’s also very difficult for humans to understand and use AI-generated evidence for practical decision-making, let alone determine if the evidence is reliable or valid.
PredX’s AI-based information aggregation agents unlock a cost-effective means to generate insights and guidance for events. More than the usual news, etc., it provides a fuller picture with a degree of press coverage, sentiment scores, technical indicators, probability projections, etc.
Web3 x AI — The Fairness Combo
While AI solves the core problems of prediction markets, it increases the risk of bias. These occur at multiple levels: over or under-representation of facts in the training data, bugs in the algorithm, or gaps in the cognition model.
Usually, solving AI bias is very challenging, both technically and culturally. But PredX found a way out by using the Web3 stack. Blockchain’s immutability and transparency played a key role here, improving accountability.
PredX’s community-centric framework implements generative coevolution networks and systems like Bittensor. Anyone can check the validity or fairness of AI-generated information on-chain. Its multi-level network has dedicated nodes to optimize for performance, vitality, and security at once.
Task nodes create and assign event-related tasks that AI and humans can solve together or adversarially, maximizing information yield. Collection nodes ensure broad data collection and insight gathering. Inference nodes analyze the data from collection nodes to generate reusable, human-understable, and on-chain verifiable evidence. Validation nodes validate information and inferences, besides enabling fair and prompt reward distribution.
Besides solving the AI-Bias Problem, PredX’s Web3-AI combo lays the foundation for inclusive, accessible, and equitable prediction markets. For example, its upcoming Telegram Mini App will provide a familiar, hassle-free interface for anyone wanting to make predictions from their phone.
Overall, platforms like PredX have cracked the code for predicting markets to reach their full potential in 2024. Balancing efficiency, reliability, and accessibility was a crucial first step. Reaching more people, pushing the bullish narrative for prediction markets, and addressing concerns or prejudices are the keystones for the next phase.
Once Web3 and AI-powered prediction markets go mainstream, they’ll transform how communities make and monetize decision-making. This will further unleash use cases with immense potential for social good — i.e., enable the equitable future of our dreams.
Image by Gerd Altmann from Pixabay
