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In Chapter 12 of the General Theory, on “The State of Long-Term Expectation,” Keynes writes: “It would be foolish, in forming our expectations, to attach great weight to matters which are very uncertain” (CW VII, p. 148). In a footnote to this sentence, Keynes points out that by “very uncertain” he does not mean the same as “very improbable” and refers to the chapter on “The Weight of Arguments” in his earlier Treatise on Probability (CW VIII, pp. 77–85). The purpose of this article, in the first place, is to provide an account of, and to sort out the relations between, Keynes's views on probability, uncertainty, and the weight of arguments.

Bayesian decision theory and inference have left a deep and indelible mark on the literature on management decision-making. There is however an important issue that the machinery of classical Bayesianism is ill equipped to deal with, that of "unknown unknowns" or, in the cases in which they are actualised, what are sometimes called "Black Swans". This issue is closely related to the problems of constructing an appropriate state space under conditions of deficient foresight about what the future might hold, and our aim is to develop a theory and some of the practicalities of state space elaboration that addresses these problems. Building on ideas originally put forward by Francis Bacon (1620), we show how our approach can be used to build and explore the state space, how it may reduce the extent to which organizations are blindsided by Black Swans, and how it ameliorates various well-known cognitive biases.