Online research in philosophy

Mainstream risk analysis deviates in at least two important respects from the rationality ideal of mainstream economics. First, expected utility maximization is not applied in a consistent way. It is applied to endodoxastic uncertainty, i.e. the uncertainty (or risk) expressed in a risk assessment, but in many cases not to metadoxastic uncertainty, i.e. uncertainty about which of several competing assessments is correct. Instead, a common approach to metadoxastic uncertainty is to only take the most plausible assessment into account. This will typically lead to risk-prone deviations from risk-neutrality. Secondly, risks and benefits for different persons are added to form a total value of risk. Such calculations are used to support the view that one should accept being exposed to a risk if it brings greater benefits for others. This is in stark contrast to modern Paretian welfare economics, that refrains from interindividual comparisons and does not require people to accept a disadvantage because it brings a larger advantage for others. (Published Online July 11 2006).

It is shown that the uncertainty connected with a `random in a broad sense' (not necessarily stochastic) event always has some `statistical regularity' (SR) in the form of a family of finite-additive probability distributions. The specific principle of guaranteed result in decision making is introduced. It is shown that observing this principle of guaranteed result leads to determine the one optimality criterion corresponding to a decision system with a given `statistical regularity'.

Winner of the 2000-2002 outstanding publication award of the Section on Environment and Technology of the American Sociological Association.Risk as we now know ...

An approach to describing risk analysis, risk perception and risk interpretation under a single umbrella starting with a general definition of risk as "adverse consequences under uncertainty." The idea of risk representation is introduced as an omnibus term for many different ways of conceptualizing risk and deploying risk messages in science, government or society.

: Bioethicists have articulated an ideal of shared decision making between physician and patient, but in doing so the role of clinical uncertainty has not been adequately confronted. In the face of uncertainty about the patient's prognosis and the best course of treatment, many physicians revert to a model of nondisclosure and nondiscussion, thus closing off opportunities for shared decision making. Empirical studies suggest that physicians find it more difficult to adhere to norms of disclosure in situations where there is substantial uncertainty. They may be concerned that acknowledging their own uncertainty will undermine patient trust and create additional confusion and anxiety for the patient. We argue, in contrast, that effective disclosure will protect patient trust in the long run and that patients can manage information about uncertainty. In situations where there is substantial uncertainty, extra vigilance is required to ensure that patients are given the tools and information they need to participate in cooperative decision making about their care.

Mainstream theories of decision making conceptualise uncertainty in terms of a well-defined probability distribution or weighting function. Following Knight, radical Keynesians consider subjective expected utility (SEU) theory and its variants as a restricted theory of decision-making applicable to situations of risk and, hence, of limited relevance to the understanding of crucial economic decisions under conditions of fundamental uncertainty in which probabilities are ill-defined, possibly non-existent. The objective of this paper is to outline a radical Keynesian theory of decision-making under uncertainty, arguing that Keynes's suggestion to a two-dimensional probability-credence framework provides the basis for determining the limitations of mainstream approaches and points the way forward to the construction of a more general encompassing theory relevant to psychologists and economists outside of the Keynesian tradition.

This article explores the question of how scientific uncertainty can be managed in medical decision making using the Advisory Committee on Immunization Practices as a case study. It concludes that where a high degree of technical consensus exists about the evidence and data, decision makers act according to a clear decision rule. If a high degree of technical consensus does not exist and uncertainty abounds, the decision will be based on a variety of criteria, including readily available resources, decision-process constraints, and the available knowledge base, among other things. Decision makers employ a variety of heuristic devices and techniques, thereby employing a pragmatic approach to uncertainty in medical decision making. The article concludes with recommendations for managing scientific uncertainty in medical decision making.

Building on work that we reported at ISIPTA 2005 we revisit claims made by Fox and Tversky concerning their "comparative ignorance" hypothesis for decision making under uncertainty.

This article is an attempt at a systematic account of decision making under greater uncertainty than what traditional, mathematically oriented decision theory can cope with. Four components of great uncertainty are distinguished: (1) the identity of the options is not well determined (uncertainty of demarcation) ; (2) the consequences of at least some option are unknown (uncertainty of consequences); (3) it is not clear whether information obtained from others, such as experts, can be relied on (uncertainty of reliance); and (4) the values relevant for the decision are not determined with sufficient precision (uncertainty of values). Some possible strategy types are proposed for each of these components. Decisions related to environmental issues are used to illustrate the proposals.

In (Hertwig et al. , 2003) Hertwig et al. draw a distinction between decisions from experience and decisions from description. In a decision from experience an agent does not have a summary description of the possible outcomes or their likelihoods. A career choice, deciding whether to back up a computer hard drive, cross a busy street, etc., are typical examples of decisions from experience. In such decisions agents can rely only of their encounters with the corresponding prospects. By contrast, an agent furnished with information sources such as drug-package inserts or mutual-fund brochures—all of which describe risky prospects—will often make decisions from description. In (Hertwig et al. , 2003) it is shown (empirically) that decisions from experience and decisions from description can lead to dramatically different choice behavior. Most of these results (summarized and analyzed in (Hertwig, 2009)) are concerned with the role of risk in decision making. This article presents some preliminary results concerning the role of uncertainty in decision-making. We focus on Ellsberg’s two-color problem and consider a chance setup based on double sampling. We report empirical results which indicate that decisions from description where subjects select between a clear urn, the chance setup based on double sampling and Ellsberg’s vague urn, are such that subjects perceive the chance setup at least as an intermediate option between clear and vague choices (and there is evidence indicating that the double sampling chance setup is seen as operationally indistinguishable from the vague urn). We then suggest how the iterated chance setup can be used in order to study decisions from experience in the case of uncertainty.