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Recent studies on the construction and use of “small world representations” in strategic decision-making under Knightian uncertainty say little about how such representations should be updated over the implementation phase. This paper draws on the psychology of reasoning to take a step towards answering this question. We begin by theorizing small world representations and how the scenario spaces they contain are constructed and may be updated over time. We then introduce two well-known heuristic methods of inquiry, disconfirmation and counterfactual reasoning, translate them into practical procedures for updating scenario spaces, and compare the relative performance of these procedures in strategic situations of Knightian uncertainty. Our principal findings are that the procedure based on counterfactual reasoning is superior to the one based on disconfirmation with respect to (1) counteracting the confirmation bias, (2) promoting the exploration of the set of imaginable scenarios, and (3) facilitating action to mitigate or exploit the consequences of what would otherwise have been Black Swans. We close with some broader implications for the study of strategic decision-making under Knightian uncertainty.

“Unknowns” and “Black Swans” have become familiar terms in the public administration literature but tend to be used in different and often conflicting ways. This article provides a typology of the two terms, develops a framework for thinking about how their elements relate, and distinguishes four varieties of the Black Swan. Using the Challenger Space Shuttle disaster, 9/11, the recent international withdrawal from Afghanistan, and the trade boycott associated with the Danish cartoon controversy as examples, we examine how these four varieties may arise in public sector organizations. We offer recommendations on how such organizations might reduce psychological and organizational barriers to uncovering unknowns before they can go on to become Black Swans.

© The Author 2017. Published by Oxford University Press on behalf of the Cambridge Political Economy Society. All rights reserved. Tony Lawson's work on probability and uncertainty is both an important contribution to the heterodox canon as well as a notable early strand of his ongoing enquiry into the nature of social reality. In keeping with most mainstream and heterodox discussions of uncertainty in economics, however, Lawson focuses on situations in which the objects of uncertainty are imagined and can be stated in a way that, potentially at least, allows them to be the subject of probability judgments. This focus results in a relative neglect of the kind of uncertainties that flow from the existence of possibilities that do not even enter the imagination and which are therefore ruled out as the subject of probability judgments. This paper explores uncertainties of the latter kind, starting with and building on Donald Rumsfeld's famous observations about known unknowns and unknown unknowns. Various connections are developed, first with Nassim Taleb's Black Swan, and then with Lawson's Keynesinspired interpretation of uncertainty.

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 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 organisations are blindsided by Black Swans, and how it ameliorates various well-known cognitive biases.

The management literature recognizes that uncertainty is a precondition for innovation but has little to say about situations where organizations create uncertainty, by design, to foster innovative...

The well-known Knightian distinction between quantifiable risk and unquantifiable uncertainty is at odds with the dominant subjectivist conception of probability associated with de Finetti, Ramsey and Savage. Risk and uncertainty are rendered indistinguishable on the subjectivist approach insofar as an individual’s subjective estimate of the probability of any event can be elicited from the odds at which she would be prepared to bet for or against that event. The risk/uncertainty distinction has however never quite gone away and is currently under renewed theoretical scrutiny. The purpose of this article is to show that de Finetti’s understanding of the distinction is more nuanced than is usually admitted. Relying on usually overlooked excerpts of de Finetti’s works commenting on Keynes, Knight and interval valued probabilities, we argue that de Finetti suggested a relevant theoretical case for uncertainty to hold even when individuals are endowed with subjective probabilities. Indeed, de Finetti admitted that the distinction between risk and uncertainty is relevant when different individuals sensibly disagree about the probability of the occurrence of an event. We conclude that the received interpretation of de Finetti’s understanding of subjective probability needs to be qualified on this front.

The welfare state is often portrayed as provider of insurance against ‘uncertainties’, in Knight's (1921) sense of the term, which would be refused or underinsured on private markets. This image conflicts with the standard economic model of risk exchange founded on the subjective interpretation of probability, which predicts that all individual uncertainties will be insured by private markets. Our aim in this paper is to explain why this prediction fails and, building on contributions to decision theory that take seriously the idea of Knightian uncertainty, to show why social insurance may be justified.

The behavioral strategy literature investigates how decision makers might use Small World Representations (SWRs) to guide their actions in situations of extreme uncertainty, but says little about how such representations should be updated during the implementation phase. In this paper, we provide a framework to capture the relationship between SWRs, unknowns and Black Swans, and, drawing on the psychology of reasoning literature, explore different heuristic methods of inquiry that decision makers might use to update their SWRs. We compare the performance of two such methods⎯disconfirmation and counterfactual reasoning⎯in highly uncertain situations characterized by ambiguous and non-definite information. We find that counterfactual reasoning is superior to disconfirmation with respect to (1) counteracting the confirmation bias, (2) promoting the exploration of the scenario space, and (3) favoring the adoption of actions able to mitigate or exploit the consequences of Black Swans.

A number of scholars have noted that Ellsberg’s seminal 1961QJE critique of the subjective expected utility model bears certain resemblances to ideas expressed in J. M. Keynes’s 1921 A Treatise on Probability. Ellsberg did not mention Keynes’s work in his article and referred instead to F. Knight’s distinction between ‘risk’ and ‘uncertainty’, thus inspiring a literature on various aspects of ‘Knightian uncertainty’. Nevertheless, the recent publication of Ellsberg’s PhD dissertation [Ellsberg, D. (2001). Risk, ambiguity and decision. New York: Garland Publishing], submitted to the University of Harvard in 1962, reveals that Ellsberg was actually aware of Keynes’s work. This gives rise to a number of interesting questions concerning the relation between the two authors’ works. The present paper, drawing in part on a conversation with Ellsberg, attempts to answer these questions. It turns out that the ‘mystery’ of why Ellsberg did not mention Keynes in his QJE article has a simple solution, namely that his dissertation was only completed after he had written the QJE article and that he had only come across Keynes after writing the QJE article. However, it is argued that although Ellsberg recognised the link between his notion of ambiguity and Keynes’s conception of the weight of argument in his PhD dissertation, he did not fully appreciate the fact that Keynes was more concerned with ‘practical’ rather than ‘conventionalised’ choice situations. To this extent, therefore, it is fair to say that ‘Knightian uncertainty’ is in many ways closer to the ideas expressed by Keynes than by Knight, and Keynes’s actual contribution to modern decision theory has been underestimated.

We propose a descriptive model of decision making under risk, inspired by the “half-full, half-empty” glass metaphor, that explains well-known paradoxes identified by Allais (1953), Kahneman and Tversky (1979), and Birnbaum (2008). The model is intuitive in that it is closely related to the expected value criterion and its parameters have a clear behavioral interpretation, and parsimonious in that it provides an approach to modeling behavior based on only two parameters.

We propose a simple model of decision making under risk inspired by the "half-full, half-empty" glass metaphor. The model is intuitive in that it is closely related to the expected value criterion and its parameters have a clear behavioral interpretation, and parsimonious in that it provides an approach to modeling behavior based on only two parameters. It explains well-known paradoxes identified by Allais (1953), Kahneman and Tversky (1979), and Birnbaum (2008).

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 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 organisations are blindsided by Black Swans, and how it ameliorates various well-known cognitive biases.

In the insurance literature, it is often argued that private markets can provide insurance against ‘risks’ but not against ‘uncertainties’ in the sense of Knight ([1921]) or Keynes ([1921]). This claim is at odds with the standard economic model of risk exchange which, in assuming that decision-makers are always guided by point-valued subjective probabilities, predicts that all uncertainties can, in theory, be insured. Supporters of the standard model argue that the insuring of highly idiosyncratic risks by Lloyd's of London proves that this is so even in practice. The purpose of this article is to show that Bruno de Finetti, famous as one of the three founding fathers of the subjective approach to probability assumed by the standard model, actually made a theoretical case for uncertainty within the subjectivist approach. We draw on empirical evidence from the practice of underwriters to show how this case may help explain the reluctance of insurers to cover highly uncertain contingencies.

Various modern decision theories seek to capture the intuition behind Keynes's conception of evidential weight. Keynes was nevertheless hesitant about the practical relevance of weight in the process of rational decision making because of the ‘stopping problem’ of finding a rational principle to decide where to stop the process of acquiring information in forming a probability judgment before making a decision. This paper discusses the relevance of the stopping problem by way of an inquiry into the nature, properties and implications for rational decision making of Keynes's conception of evidential weight. It is argued that in practical choice situations the decision maker often decides where to stop the process of acquiring information by following Keynes's advice to consider the degree of completeness of the available information before making a decision. This method implies that the decision maker is able to arrive at an assessment of the dimension of what may be called her ‘relevant ignorance’. By considering some examples of how the acquisition of new evidence may affect the decision maker's behaviour, it is argued that it is in fact possible to talk reasonably about relevant ignorance, or what are sometimes called ‘unknown unknowns’, and that this concept might explain a range of human behaviours. While this concept does not provide a rational principle to solve the stopping problem, it does provide a method of inquiry for dealing with a number of paradoxes not solvable within the Bayesian approach.

One of the open questions in the strategic decision-making process literature is how best to promote decision comprehensiveness in turbulent environments characterized by rapid, discontinuous and u...

A number of scholars have noted that Ellsberg’s seminal 1961QJE critique of the subjective expected utility model bears certain resemblances to ideas expressed in J. M. Keynes’s earlier 1921 A Treatise on Probability. Ellsberg did not mention Keynes’s work in his article, but did do so in his doctoral dissertation submitted in 1962 and recently published in 2001. This gives rise to a number of interesting questions concerning the relationship between the contributions of the two authors. The present paper, drawing in part on a conversation with Ellsberg, attempts to answer these questions. The main conclusions that emerge are that Ellsberg formulated the ideas advanced in the QJE article before having read, and thus independently of, Keynes’s work, and that, even though he later recognised the importance and originality of Keynes’s work in his PhD dissertation, he did not fully appreciate the constructive part of Keynes’s analysis. 1. Introduction The last twenty years have seen a revival of

Existing approaches to monitoring projects in the face of unknown unknowns recommend collecting progress-relevant information until contradictions, or disconfirming evidence, have accumulated to di...