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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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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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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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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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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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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Crowd forecasting allows you to get signals about events before they happen. We're making it even easier to be alerted to important signals by introducing crowd forecast change alerts – which notify you of sudden shifts in the consensus forecast.
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Many effective altruist (EA) core values illustrate why they are enthusiastic to use crowd forecasting methods. EAs seek to tackle problems of global significance, placing an emphasis on not only doing good, but doing good effectively. "When decision-makers in government have to make high-stakes judgment calls, using rigorous forecasting techniques can improve our ability to predict the future and make better decisions."
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As consumers learn to use these forecasts as part of their own analysis and decision-making, we've been thinking through how we can make sure they see a complete picture - not just the one represented by the graph visualization that tracks the consensus, but why that consensus may be wrong. We want the consumer to always question their assumptions and question the consensus.
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With increased attention to crowdsourced generated forecasts as guidance to critical decisions comes the need to be as transparent as possible about the credibility of a current forecast.
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The latest Cultivate Forecasts platform updates as of June 9, 2020.
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New presentation feature lets people forecast -- and see the results update in real-time.
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Forecasting in teams can lead to greater accuracy, and we've got the features to make it possible, like private team pages with discussion boards and team rankings.
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I talk to Anna Dreber Almenberg, an economist at the Stockholm School of Economics about prediction markets she's running to try and address the reproducibility crisis in science.
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Schedule chicken is when someone is personally behind on their work, but doesn't say anything because they think someone else will, and take the heat for it, thus protecting their own ass. This apparently goes on at Apple, and is completely absurd. There's another way.
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We're excited to announce the availability of a new product, Flashcast. Flashcast is an entirely new way to interact with your audience. Ask them to make predictions about a related topic and watch the results, live.
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No one enjoys being wrong. It’s an unpleasant emotional experience for any of us. But that’s exactly the risk we’re suggesting people take when we ask them to make a forecast about the future.
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When we start projects with our clients, one of the first items we talk about is whether they want people to be anonymous in our prediction market or if they’ll use their real identities. The answer often reveals a lot, both about company culture and their personal fears of what will be made transparent. The spoiler alert is most don’t want anonymity.
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After working with dozens of companies who have culture initiatives, I’m convinced their multi-million dollar investments in consultants, employee time, internal marketing, and the like will only see a partial return because a blocker is in their way: their culture of fear.
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Our bread and butter working with clients is organizing their employees to participate in crowdsourcing exercises. Recently we have been approached more to help get forecasts from external crowds, either to support research projects, or to better understand what outside experts or customers think.
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In the last month we’ve had two potential clients, after receiving proposals from us for projects, say they needed to step back and start the projects very differently than what we had originally discussed. They just weren't ready yet, they acknowledged...
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I've been watching for the last few years the announcement, long delay, then recent launch of Augur, the decentralized, blockchain-based prediction market. First off, despite it taking a long time to launch, Augur finally did, and kudos to them for doing so. Building a prediction market from scratch is not easy, building a prediction market on top of immature technology is harder, and building a prediction market to be completely decentralized with smart contracts is downright scary.
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We're pairing up with Lending Club to sponsor a monthly event where cybersecurity startups pitch their companies, and the audience gets to make predictions on our prediction market about how they're going to do in the next year in terms of fundraising, hiring, etc.
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Everyone who has worked in corporate America has seen or used it. The traffic light metaphor for status. Red, there’s significant problems with a project. Yellow, there are some issues, but we’re going to make it. Green, all is good. Unfortunately, this system is a disaster for decision making.
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