Metaculus @metaculus
Forecasts on critical topics. Labor Automation Forecasting Hub: https://t.co/jHtSvLhuih FutureEval: https://t.co/AuPHSXYWU7 Partner: https://t.co/9Ld1Xrk4eY metaculus.com Santa Cruz, CA Joined November 2015-
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@World_Data_A To this, we recently launched our Labor Automation Forecasting Hub, which provides forecast data on the impacts of AI automation on the US workforce through 2035, with 15 dedicated occupation pages for individual analysis metaculus.com/labor-hub/
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@besttrousers @SearchlightInst To this, we recently launched our Labor Automation Forecasting Hub, which provides forecast data on the impacts of AI automation on the US workforce through 2035 metaculus.com/labor-hub/
@ForeignAffairs @jleibenluft To this, we recently launched our Labor Automation Forecasting Hub, which provides forecast data on the impacts of AI automation on the US workforce through 2035 metaculus.com/labor-hub/
@FutureEconJacob @alexolegimas Would welcome any forecasts you have on these or any outcomes you see here, @FutureEconJacob: metaculus.com/tournament/lab…
Metaculus retweeted
Predictions from @metaculus regarding the workforce in 2035 are in line with @alexolegimas' predictions of a relational bottleneck
Our US Democracy Threat Index, developed in partnership with @BrightLineWatch, tracks questions on threats to US democracy & carries a $10,000 prize pool. Within that there’s a $2,500 spot scoring bonus prize. How that works: at the end of the tournament, every prediction that was standing at the time of a series of snapshots will be scored, and your scores across snapshots will be summed to determine your share of that bonus prize. Our next snapshot is July 15, so leave your predictions now! 👉 metaculus.com/index/us-democ…
7/ See all 15 occupations on the Labor Hub Jobs page: metaculus.com/labor-hub/jobs
6/ More context about each AI exposure metric: - Felten et al’s AI Occupational Exposure (AIOE) measures the overlap between AI capabilities and the abilities an occupation requires, aggregated from O*NET ability data. Higher exposure does not by itself mean a job will be automated; it can equally signal that AI augments the work. - M&A vulnerability is an academic measure combining exposure to AI with workers' adaptive capacity. Vulnerability scores are related both to the likelihood of displacement (through AI exposure) and its burden (through adaptive capacity). - Anthropic’s Observed Exposure (AOE) reflects Anthropic's estimate of what share of tasks in the role AI currently touches. Unlike purely theoretical measures, this is also grounded in real, anonymized Claude usage: what people are actually doing with AI right now, mapped to O*NET occupation tasks. AOE captures observed adoption, not potential, a low value may mean the work simply isn't being brought to Claude yet, not that AI couldn't do it.
1/ Which jobs are most vulnerable to AI automation? The Labor Automation Forecasting Hub now has individual pages for 15 US occupations, including: - Community forecasts at 2027, 2030, and 2035 - Pro Forecaster commentary - 3 distinct AI exposure metrics (Felten, M&A vulnerability, Anthropic). More details about each in the replies. Curious which jobs forecasters think will grow or contract, and the reasoning behind the forecasts? Read on 🧵
Full report here: cdn.prod.website-files.com/669550d38372f3…
👀 New @MITAIRisk x @MITFutureTech report: “Prioritization of Risks from Artificial Intelligence: A Delphi Study of 272 International Experts.” A Metaculus question makes an appearance on p. 17 (link to report in replies)
7/ Find the full report here: metaculus.com/files/Frontier… @coeff_giving works to direct funding to the most impactful global health opportunities. This forecasting project was designed to support their portfolio decisions. Want independent forecasts like this for your org? Check out our Services page: metaculus.com/services/
6/ Microneedle patch vaccines are closest to delivering real-world impact, with Pros forecasting first approval in June 2032. Manufacturing scale-up is the main hurdle, but unlike the other technologies here, forecasters don't foresee a multi-year commercial delay.
1/ What disease prevention technologies are most likely to deliver impact over the next two decades, and what are the factors that will determine timelines and implementation? 🧵
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