False dichotomy alert: Improving subjective-probability estimates vs. raising awareness of systemic risk

Lu, Yunzi; Mellers, Barbara A.

doi:10.1016/j.ijforecast.2022.02.008

Cited by 3 publications

(4 citation statements)

References 30 publications

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“…But all else is rarely equal. They worry more about quixotic research programs that offer false reassurance that the unknowable is knowable (Kay & King, 2020) than they do about missing chances to enhance foresight (Tetlock et al, 2022). Counterfactual adjustments to accuracy scores remind us that top forecasters are one ill-timed war from being knocked off their pedestal.…”

Section: Cumulative Conversationsmentioning

confidence: 99%

Long‐range subjective‐probability forecasts of slow‐motion variables in world politics: Exploring limits on expert judgment

TETLOCK

Karvetski²,

Satopää

et al. 2023

Futures & Foresight Science

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Skeptics see long‐range geopolitical forecasting as quixotic. A more nuanced view is that although predictability tends to decline over time, its rate of descent is variable. The current study gives geopolitical forecasters a sporting chance by focusing on slow‐motion variables with low base rates of change. Analyses of 5, 10, and 25‐year cumulative‐risk judgments made in 1988 and 1997 revealed: (a) specialists beat generalists at predicting nuclear proliferation but not shifting nation‐state boundaries; (b) some counterfactual interventions—for example, Iran gets the bomb before 2022—boosted experts’ edge but others—for example, nuclear war before 2022—eliminated it; (c) accuracy fell faster on topics where expertise conferred no edge in shorter‐range forecasts. To accelerate scientific progress, we propose adversarial collaborations in which clashing schools of thought negotiate Bayesian reputational bets on divisive issues and use Lakatosian scorecards to incentivize the honoring of bets.

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Section: Cumulative Conversationsmentioning

confidence: 99%

Long‐range subjective‐probability forecasts of slow‐motion variables in world politics: Exploring limits on expert judgment

TETLOCK

Karvetski²,

Satopää

et al. 2023

Futures & Foresight Science

View full text Add to dashboard Cite

show abstract

“…

We respond to Tetlock et al (2022) showing 1) how expert judgment fails to reflect tail risk, 2) the lack of compatibility between forecasting tournaments and tail risk assessment methods (such as extreme value theory).More importantly, we communicate a new result showing a greater gap between the properties of tail expectation and those of the corresponding probability.

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mentioning

confidence: 92%

“…I. THE FAT TAILS PROBLEM Tetlock et al (2022) [1], in their criticism of claims by a paper titled "On single point forecasts for fat-tailed variables" in this journal (Taleb et al, 2022 [2]) insist that discriminating between a binary probability and a continuous distribution is a false dichotomy, that binary probabilities derived from expert forecasting tournaments can provide information on tail risk, in addition to some claims about a collaboration with the first author and a "challenge".…”

mentioning

confidence: 99%