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Much of the controversy about methods for automated decision making hasfocused on specific calculi for combining beliefs or propagating uncertainty.We broaden the debate by (1) exploring the constellation of secondary taskssurrounding any primary decision problem, and (2) identifying knowledgeengineering concerns that present additional representational tradeoffs. Weargue on pragmatic grounds that the attempt to support all of these taskswithin a single calculus is misguided. In the process, we note severaluncertain reasoning objectives that conflict with the Bayesian ideal ofcomplete specification of probabilities and utilities. In response, we advocatetreating the uncertainty calculus as an object language for reasoningmechanisms that support the secondary tasks. Arguments against Bayesiandecision theory are weakened when the calculus is relegated to this role.Architectures for uncertainty handling that take statements in the calculus asobjects to be reasoned about offer the prospect of retaining normative statuswith respect to decision making while supporting the other tasks in uncertainreasoning.

The Role of Calculi in Uncertain Inference Systems