Rather than optimizing for raw predictive accuracy, effective AI forecasting systems should support sensemaking by tracking probabilistic judgment, disagreement, and changing confidence over time.
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Cultivate Labs is announcing a new forecasting capability that uses AI to generate fast, continuously updated probabilistic judgments and integrate them into existing analytic workflows. The approach emphasizes combining multiple perspectives and pairing AI with human judgment to improve decision-making under uncertainty, rather than relying on any single model or replacing people.
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When something big happens in the world, it’s easy to ask questions that feel informed but don’t really help anyone decide what to do next. This post shows how I try to slow that moment down, using the Greenland episode to illustrate how better questions lead to better analysis.
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Tldr; - Hopefully, but it won’t be because of superhuman accuracy.AI forecasting systems are the talk of the forecasting world. AI forecasting tournaments are running, VC money is flowing, and benchmarks are being published. We’re building an AI forecasting system ourselves. As with the rest of crowdsourced forecasting’s history, most of the chatter is around accuracy. How accurate are the LLMs? When will they beat human and pro forecasters? Can you train models specifically for forecas
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When geopolitical analysts wrestle with a complex geopolitical question, say the future of European financial support to Ukraine, they tend to begin with familiar sources: Western media, think tank reports, and official statements. But what if using AI they ran the same scenario-building exercise with Russian sources threaded in? The same Russian sources a Russian analyst might leverage as part of their own analysis? What might change in the narratives, framing, and assessed likelihoods?
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A forecasting workshop on lunar diplomacy, co-facilitated by the Bertelsmann Foundation and the European Space Policy Institute, explored how national interests, private investment, and international competition will define future activity on the Moon. Participants identified signposts and used crowdsourced forecasting to track three plausible scenarios: rival lunar coalitions, China cislunar primacy, and a pluralistic lunar order.
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Recent disputes over Iran’s nuclear ambitions highlight the power of a now defunct internal U.S. intelligence forecasting capability, the Intelligence Community Prediction Market (ICPM).
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Last month I had the opportunity to travel to Kyiv for some work we’re doing there. Since not many people are traveling to Kyiv these days from the US, I thought I would share a few reflections on my visit.
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Before we close shop and take a few days off, I wanted to take a moment to reflect on the challenges, milestones, and relevant events that defined the year for our company + a few extra musings if you will so indulge me. So let’s take a step back and reflect on what made this year what it was.
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After a detailed vetting process earlier this year, Cultivate Labs has been awarded as a supplier on Crown Commercial Service’s (CCS) G-Cloud 14 framework. This means any UK Government agency or UK non-profit or charity can easily access Cultivate's cloud hosted software and professional services.
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The religion of probabilistic forecasting says SCORE EVERYTHING and we try to(!), but there are times when you want to ask a question that may not have good resolution criteria or the answer is 5+ years from being known so we've introduced unscored questions.
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The Canadian Forest Service utilizes crowd forecasting program called Firesight to predict wildfire occurrences and damages across Canadian regions. We sat down with Forest Fire Research Scientist Mike Wotton to learn more about how Firesight is supporting the fire management community.
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Georgetown graduate students participate in a Cultivate decomposition workshop to learn how policy analysts break down an issue such as the Israel-Hamas War - and combine it with crowd forecasting to track future outcomes.
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Crowdsourced forecasting is the process of soliciting quantitative forecasts (e.g. probabilities) about future events from a large group of people, then aggregating them into a "crowd" forecast. By harnessing the collective intelligence of a large, diverse group of people, crowd forecasting gives an analyst or decision maker valuable outside perspectives to consider.
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Cultivate supports government national security communities and multinational organizations in implementing crowdsourced forecasting. This methodology builds a cycle of information, in which experts can tap into the collective intelligence of their organization to bolster decision analysis.
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Our AI forecast rationale summaries have been updated to include citations, so you can see the original context of the forecast and rationale contributed.
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With the rise of AI, disinformation in mass media will only continue to grow and evolve. Turning our attention to crowd forecasting is one way that we can better understand, monitor, and respond to global uncertainty – together.
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New whitepaper explores how to use AI across different aspects of crowdsourced forecasting, including question development, reporting, engagement, and forecasting.
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We released a new feature on our forecasting platform: AI-powered forecast rationale summaries using Anthropic’s Claude2. Read about how forecasters and analysts are already using this capability.
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As a company, we hold small group forecasting sessions regularly. We’ve learned a few tactics to help other teams surface diverse viewpoints and avoid groupthink. Here are some recommendations for any teams forecasting together.
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Earlier this month, one of our client programs INFER – the crowd forecasting program supporting the U.S. Government – hosted a special forecasting event about the future of AI. The event was attended by select INFER forecasters and nearly two dozen forecasting enthusiasts who work at Google, joining in a personal capacity.
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We are launching a service offering: "issue decomposition" workshops – a new way of methodically understanding how the future will impact your most important decisions and policies.
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Cultivate has released a new “request for response” capability that allows you to send any audience a simple survey, in which they can submit forecasts that will automatically get aggregated with your crowd’s on your Forecasts platform.
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One of the first steps in a crowdsourced forecasting effort involves establishing a process for developing forecast questions that will deliver meaningful signals to decision-makers. We wanted to shed some light on our process, so we talked to a few of our team members that focus on developing questions for our client platforms.
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