Generally, rational decision-making is conceived as arriving at a decision by a correct application of the rules of logic and statistics. If not, the conclusions are called biased. After an impressive series of experiments and tests carried out in the last few decades, the view arose that rationality is tough for all, skilled field experts not excluded. A new type of planner's counsellor is called for: the normative statistician, the expert in reasoning with uncertainty par excellence. To unravel this view, (...) the paper explores a specific practice of clinical decision-making, namely Evidence-Based Medicine. This practice is chosen, because it is very explicit about how to rationalize practice. The paper shows that whether a decision-making process is rational cannot be assessed without taking into account the environment in which the decisions have to be taken. To be more specific, the decision to call for new evidence should be rational too. This decision and the way in which this evidence is obtained are crucial to validate the base rates. Rationality should be model-based, which means that not only the isolated decision-making process should take a Bayesian updating process as its norm, but should also model the acquisition of evidence (priors and tests results) as a rational process. (shrink)

Climate change adaptation is largely a local matter, and adaptation planning can benefit from local climate change projections. Such projections are typically generated by accepting climate model outputs in a relatively uncritical way. We argue, based on the IPCC’s treatment of model outputs from the CMIP5 ensemble, that this approach is unwarranted and that subjective expert judgment should play a central role in the provision of local climate change projections intended to support decision-making.

Group decisions raise a number of substantial philosophical and methodological issues. We focus on the goal of the group decision exercise itself. We ask: What should be counted as a good group decision-making result? The right decision might not be accessible to, or please, any of the group members. Conversely, a popular decision can fail to be the correct decision. In this paper we discuss what it means for a decision to be "right" and what components are required in a (...) decision process to produce happy decision-makers. Importantly, we discuss how "right" decisions can produce happy decision-makers, or rather, the conditions under which happy decision-makers and right decisions coincide. In a large range of contexts, we argue for the adoption of formal consensus models to assist in the group decision-making process. In particular, we advocate the formal consensus convergence model of Lehrer and Wagner (1981), because a strong case can be made as to why the underlying algorithm produces a result that should make each of the experts in a group happy. Arguably, this model facilitates true consensus, where the group choice is effectively each person's individual choice. We analyse Lehrer and Wagner's algorithm for reaching consensus on group probabilities/utilities in the context of complex decision-making for conservation biology. While many conservation decisions are driven by a search for objective utility/probability distributions (regarding extinction risks of species and the like), other components of conservation management primarily concern the interests of stakeholders. We conclude with cautionary notes on mandating consensus in decision scenarios for which no fact of the matter exists. For such decision settings alternative types of social choice methods are more appropriate. (shrink)

Is subjective expert judgment a source of evidence in economics? In this paper, I will argue that it is, on a par with other sources like modeling, statistics, experimental, etc. I will also argue that it is not derivative, that is, reducible to the previous ones. But what is exactly the role of experts in economics? The contribution to the current methodological debate that I propose not only takes the role of expertise in economics as indispensable, but also suggests a (...) need for a methodology associated with that role. I defend an indispensability argument, and indirectly David Colander's plea for refocusing the methodological debate on the lost art of economics. Finally, I indicate where to look for guidelines in formulating a methodology of economic expertise. (shrink)

This paper explores the scope and limits of rational consensus through mutual respect, with the primary focus on the best known formal model of consensus: the Lehrer–Wagner model. We consider various arguments against the rationality of the Lehrer–Wagner model as a model of consensus about factual matters. We conclude that models such as this face problems in achieving rational consensus on disagreements about unknown factual matters, but that they hold considerable promise as models of how to rationally resolve non-factual disagreements.

In this paper I analyze four so-called “principles of expertise”; that is, good epistemic practices that are normatively motivated by the epistemological literature on expert judgment. I highlight some of the problems that the four principles of expertise run into, when we try to implement them in concrete contexts of application (e.g. in science committees). I suggest some possible alternatives and adjustments to the principles, arguing in general that the epistemology of expertise should be informed both by case studies and (...) by the literature on the use of experts in science practice. (shrink)

The problem of how to rationally aggregate probability measures occurs in particular when a group of agents, each holding probabilistic beliefs, needs to rationalise a collective decision on the basis of a single ‘aggregate belief system’ and when an individual whose belief system is compatible with several probability measures wishes to evaluate her options on the basis of a single aggregate prior via classical expected utility theory. We investigate this problem by first recalling some negative results from preference and judgment (...) aggregation theory which show that the aggregate of several probability measures should not be conceived as the probability measure induced by the aggregate of the corresponding expected utility preferences. We describe how McConway’s :410–414, 1981) theory of probabilistic opinion pooling can be generalised to cover the case of the aggregation of infinite profiles of finitely additive probability measures, too; we prove the existence of aggregation functionals satisfying responsiveness axioms à la McConway plus additional desiderata even for infinite electorates. On the basis of the theory of propositional-attitude aggregation, we argue that this is the most natural aggregation theory for probability measures. Our aggregation functionals for the case of infinite electorates are neither oligarchic nor integral-based and satisfy a weak anonymity condition. The delicate set-theoretic status of integral-based aggregation functionals for infinite electorates is discussed. (shrink)

There is good reason to believe that, if it can be decided at all, the realism debate must be decided on a posteriori grounds. But at least prima facie the prospects for an a posteriori resolution of the debate seem bleak, given that realists and antirealists disagree over two of the most fundamental questions pertaining to any kind of empirical research, to wit, what the range of accessible evidence is and what the methodological status of explanatory considerations is. The present (...) paper aims to show that, while the difficulties that face an empirical approach to the realism debate are not to be discounted, they are not insurmountable either. Specifically, it presents a broadly Bayesian strategy for resolving the debate that is capable of solving those difficulties. The strategy crucially involves answers to the aforementioned questions that diverge from both the standard realist and the standard antirealist answers, but that should appear more natural and plausible than those to realists and antirealists alike. (shrink)

Local and global dependencies and interactions between individuals, groups and institutions are becoming increasingly opaque and risky. This is due to increased importance of highly complex abstract systems created and supported in order to maintain of transport, communications, finance, energy, media, security infrastructure, as well as social and cultural institutions. These systems require the knowledge and skills of experts. Professionals that not only satisfy identified needs, but also create new thereby contribute the development of cultural narcissism phenomenon. The aim of (...) the book is to discuss relations of experts and mass narcissism, on the background of shaping the knowledge societies and knowledge-based economies, and moreover their transformations towards the societies and economies based on creativity and wisdom. Undertaken analysis is contribute to sociology of expertise and intervention by indicating four selected contemporary issues: dilemmas of the knowledge society development; selection between trust substitutes and its reconstruction methods; transformations of social stratification; and the choice of pathways to socio-economic development. (shrink)

Scientists are often asked to advise political institutions on pressing risk-related questions, like climate change or the authorization of medical drugs. Given that deliberation will often not eliminate all disagreements between scientists, how should their risk assessments be aggregated? I argue that this problem is distinct from two familiar and well-studied problems in the literature: judgment aggregation and probability aggregation. I introduce a novel decision-theoretic model where risk assessments are compared with acceptability thresholds. Majority voting is then defended by means (...) of robustness considerations. (shrink)