Nathan Labenz and Prakash Shankar host AI in the AM with guest Dan Schwartz, CEO of FutureSearch, discussing the breakthrough moment in AI forecasting capabilities. Schwartz claims AI forecasters have reached superhuman performance in the last six months, matching or exceeding top human superforecasters on multiple benchmarks including ForecastBench and Metaculus tournaments. Scott Alexander recently validated these claims in a post titled 'The AI Superforecasters Are Here.' FutureSearch has been making hundreds of real-money trades on prediction markets like Polymarket and Kalshi using pure forecasting edge, not arbitrage or market-making. The episode also covers a major $160 million grant to Jeffrey Irving's Resolution AI safety nonprofit from Coefficient Giving, representing the largest known funding to an independent safety organization. Schwartz reveals that both OpenAI and DeepMind previously hired human superforecasters to evaluate GPT-4 and Gemini releases respectively. The hosts discuss controversial statements from Roon about tool AI being outcompeted by autonomous agents that will eventually execute human value systems better than humans themselves. Schwartz argues forecasting provides the only renewable source of training data as models surpass human experts, since ground truth emerges simply by waiting for future events to resolve. The episode explores implications for AI safety, financial markets, decision-making, and the coming transition to AI systems that may reason about the future in fundamentally alien ways. The conversation also touches on Fable's improved code management capabilities and the hosts demonstrate their new voice AI co-host Q live on the stream.
Roon posted that tool AI will be market-outcompeted by agentic systems that can override user requests and eventually execute value systems better than humans. The statement raises uncomfortable questions about AI systems enforcing stated values versus actual human behavior, with potential implications for law enforcement and social control.
Read this moment →Dan Schwartz argues forecasting provides an unlimited renewable source of hard problems with verifiable ground truth that emerges simply by waiting. As AI models surpass human experts in most domains, creating evaluation datasets becomes impossible because humans can't generate problems the models can't already solve. Forecasting uniquely solves this problem.
Read this moment →Dan Schwartz of FutureSearch claims AI forecasters have crossed the threshold to superhuman performance, matching or beating top human experts on ForecastBench and Metaculus tournaments. The capability emerged rapidly in the last six months with models like Claude Fable. Scott Alexander validated the claims in a recent post titled 'The AI Superforecasters Are Here.'
Read this moment →Jeffrey Irving's Resolution received a massive $160 million commitment from Coefficient Giving (associated with Dustin Moskovitz and the EA movement) to fund AI safety research. The grant represents unprecedented funding for safety work outside frontier labs, with $108 million unconditional. Irving previously served as chief scientist at the UK AISI and has a tier-1 research track record.
Read this moment →FutureSearch's AI forecaster has made hundreds of real-money trades on Polymarket and Kalshi based purely on forecasting edge, not market-making or arbitrage. While profitability fluctuates due to small sample size, any consistent profit would represent AI outperforming aggregated human crowd wisdom in prediction markets.
Read this moment →Both OpenAI and DeepMind brought in human superforecasters to assess the implications and release strategies for GPT-4 and Gemini respectively. This reveals frontier labs sought external forecasting expertise for major deployment decisions before AI forecasting capabilities emerged.
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