Conditional forecasts can be split by specialty and recombined mechanically. In Malone's example, purchasing staff estimate costs with and without a recession, marketers estimate sales the same way, economists give the recession's probability, and a Bayesian network joins them into one prediction no single expert could make. A conditional market does that decomposition with prices; the network does it with a model.

Evidence 2 passages

• groundsSuperminds (audiobook machine transcript), Thomas W. Malone

  The results would thus be an integrated prediction that draws upon expertise from economists, purchasing specialists, and marketers, all automatically combined by computers.

• groundsSuperminds (audiobook machine transcript), Thomas W. Malone

  But if purchasing specialists separately estimate whether materials costs would be acceptable with a recession and without one, and if marketers do the same for sales volume, then a Bayesian network could automatically combine all these estimates with separate projections by economists about the probability of a recession.

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