Comment Text:
I’m filing this comment as the founder and CEO of The Intelligent Search Company, where we build decision-intelligence systems for high-stakes environments, starting in college athletics. My work focuses on turning fragmented evidence — video, statistics, expert observations, and contextual judgment — into decisions under uncertainty. In that work, I see the same problem repeatedly: the bottleneck is often not the absence of information, but the absence of mechanisms for converting scattered information into calibrated judgment.
That is why I believe event contracts can serve a genuine price-discovery and information-dissemination function under CEA § 3(a). A well-designed prediction market forces beliefs into a public, continuously updating probabilistic signal. That signal is useful even when participants are not hedging a conventional commercial exposure. In many scientific, policy, and institutional domains, the relevant “risk” is not a corn price or an interest rate; it is uncertainty about whether a future event will occur, how likely a scenario is, or whether expert consensus is moving. A nonprofit research market can make that uncertainty more visible and measurable.
This distinction matters for how the Commission approaches guidance under the DCM Core Principles. Commercial prediction markets and nonprofit research markets may use similar contract mechanics, but they do not serve the same institutional function. A retail-facing platform built around sports, politics, entertainment, or mass speculation raises different questions than a nonprofit research market designed to study forecasting, publish aggregate results, and improve public understanding of future risks.
The Commission should therefore avoid treating all event-contract platforms as one undifferentiated category. For nonprofit research markets, the relevant factors should include mission, governance, participation limits, data transparency, publication of research results, conflicts of interest, and safeguards against retail-gambling dynamics. That would not give nonprofit markets a blank check. It would simply recognize that a market designed as research infrastructure should be evaluated differently from a commercial trading venue.
I support Cassandra’s view that nonprofit research markets deserve a clear regulatory pathway separate from commercial prediction-market venues. In the right institutional setting, a forecasting market is not just another venue for betting. It is a measurement instrument for uncertainty. That is a public-interest function worth preserving.
