Are prediction markets good for anything?

2025-11-03 · Source: Asterisk Magazine · Field: Finance & Economics — Capital Markets & Investment Management, Economic Analysis & Policy · Depth: Advanced, extended

Summary

Public prediction markets like Polymarket and Kalshi, despite transacting billions of dollars monthly by 2026, primarily serve sports and cryptocurrency gambling, not their intended purpose of improving public and private decision-making. While early proponents like Kenneth Arrow and Robin Hanson envisioned markets aggregating dispersed knowledge for policy, current platforms show limited utility. The author categorizes five potential benefits: risk monitoring, interpreting news, policy outcomes, accountability, and novel information. Risk monitoring markets, particularly for geopolitical events, show healthy volume and media citation, but lack detection capabilities for emerging risks like health or climate. Other categories, despite high trading volumes, are often dominated by entertainment-driven bets or duplicate existing financial indicators. Accuracy correlates with volume for long-term markets (90+ days), but overall useful market volume and accuracy have declined since late 2024/early 2025. The rise of AI superforecasters and chatbots, which offer narratives and interactive querying, challenges prediction markets' role in distributing wisdom.

Key takeaway

For AI Scientists or Directors of AI/ML evaluating forecasting tools, recognize that traditional prediction markets like Polymarket and Kalshi, despite high trading volumes, are largely entertainment-driven and offer limited actionable intelligence beyond specific risk monitoring. Instead, prioritize integrating advanced AI forecasting models and chatbots into your decision-making workflows. These AI tools provide more comprehensive, interactive insights, addressing the "distribution of wisdom" bottleneck more effectively than current market structures.

Key insights

Public prediction markets, despite high volume, primarily serve entertainment, while AI chatbots emerge as superior information aggregators.

Principles

• Markets aggregate dispersed, local knowledge.
• Increased bettors enhance market accuracy.

In practice

• Monitor prediction markets for geopolitical risks.
• Utilize AI chatbots for nuanced forecasting.
• Track tariff policy markets for business impact.

Topics

• Prediction Markets
• AI Forecasting
• Risk Monitoring
• Information Aggregation
• Forecasting Accuracy
• Polymarket
• Kalshi

Best for: AI Scientist, Director of AI/ML, Policy Maker

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• Pharos Network and Hong Kong University Are Quietly Building the Next Layer of On-Chain Forecasting — Prediction markets are evolving from entertainment to critical infrastructure for real-world asset pricing and information verification.
• How to Analyze Prediction Markets with AI: A Step-by-Step Guide — AI enhances prediction market analysis by amplifying existing competence through structured information aggregation and probability calibration.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Asterisk Magazine.