Risk and Uncertainty in decision-making

In the last decade, the notion of uncertainty has gained prominence in anthropological debates. So has the debate on future. Yet, the conceptualisation of uncertainty has barely been linked to the future(s) and its temporal relations. This lack of linkage seems astonishing in so far as uncertainty relates closely to the unpredictability of the future. Uncertain situations engender ambivalent experiences and affects towards an unknown future embracing hope, desire and opportunity as well as fear, despair and suffering. Theoretically, the future is always unknown and unpredictable, but usually people are able to anticipate the future as it is more conversant than in uncertain situations, which challenge future outlooks and knowledge practices. Anthropologists have dedicated atten- tion to uncertain situations ranging from everyday uncertainties under precarious conditions to crises and critical events of individual or collective existential uncertainty.

About a decade ago, the Netherlands Environmental Assessment Agency (PBL) unwittingly embarked on a transition from a technocratic model of science advising to the paradigm of ‘‘post-normal science’’ (PNS). In response to a scandal around uncertainty management in 1999, a Guidance for ‘‘Uncertainty Assessment and Communication’’ was developed with advice from the initiators of the PNS concept and was introduced in
2003. This was followed in 2007 by a ‘‘Stakeholder Participation’’ Guidance.
In this article, the authors provide a combined insider/outsider perspective on the transition process. The authors assess the extent to which the PNS paradigm has delivered new approaches in the agency’s practice and analyze two projects—on long-term options for Dutch sustainable development
policy and for urban development policy—the latter in somewhat more detail. The authors identify several paradoxes PBL encounters when putting the PNS concept into practice. It is concluded that an openness to other styles of work than the technocratic model has become visible, but that the introduction of the PNS paradigm is still in its early stage.

This half-day tutorial on Belief function (random sets) for the working scientist was presented on July 9th 2016 at the latest International Joint Conference on Artificial Intelligence (IJCAI-16).

The tutorial is very comprehensive (468 slides), covering:

(i) a review of mathematical probability and its interpretations (Bayesian and frequentist);

(ii) the rational for going beyond standard probability: it's all about the data!

(iii) the basis notions of the theory of belief functions;

(iv) reasoning with belief functions: inference, combination/conditioning, graphical models, decision making;

(v) using belief functions for classification, regression, estimation, etc;

(vi) dealing with computational issues and extending belief measures to real numbers;

(vii) the main frameworks derived from belief theory, and its relationship with other theories of uncertainty;

(viii) a number of example applications;

(ix) new horizons, from the formulation of limit theorems for random sets, generalising the notion of likelihood and logistic regression for rare event estimation, climatic change modelling and new foundations for machine learning based on random set theory, a geometry of uncertainty.

Tutorial slides are downloadable at http://cms.brookes.ac.uk/staff/FabioCuzzolin/files/IJCAI2016.pdf

The principal aim of this book is to introduce to the widest possible audience an original view of belief calculus and uncertainty theory. In this geometric approach to uncertainty, uncertainty measures can be seen as points of a suitably complex geometric space, and manipulated in that space, for example, combined or conditioned.

In the chapters in Part I, Theories of Uncertainty, the author offers an extensive recapitulation of the state of the art in the mathematics of uncertainty. This part of the book contains the most comprehensive summary to date of the whole of belief theory, with Chap. 4 outlining for the first time, and in a logical order, all the steps of the reasoning chain associated with modelling uncertainty using belief functions, in an attempt to provide a self-contained manual for the working scientist. In addition, the book proposes in Chap. 5 what is possibly the most detailed compendium available of all theories of uncertainty. Part II, The Geometry of Uncertainty, is the core of this book, as it introduces the author’s own geometric approach to uncertainty theory, starting with the geometry of belief functions: Chap. 7 studies the geometry of the space of belief functions, or belief space, both in terms of a simplex and in terms of its recursive bundle structure; Chap. 8 extends the analysis to Dempster’s rule of combination, introducing the notion of a conditional subspace and outlining a simple geometric construction for Dempster’s sum; Chap. 9 delves into the combinatorial properties of plausibility and commonality functions, as equivalent representations of the evidence carried by a belief function; then Chap. 10 starts extending the applicability of the geometric approach to other uncertainty measures, focusing in particular on possibility measures (consonant belief functions) and the related notion of a consistent belief function. The chapters in Part III, Geometric Interplays, are concerned with the interplay of uncertainty measures of different kinds, and the geometry of their relationship, with a particular focus on the approximation problem. Part IV, Geometric Reasoning, examines the application of the geometric approach to the various elements of the reasoning chain illustrated in Chap. 4, in particular conditioning and decision making. Part V concludes the book by outlining a future, complete statistical theory of random sets, future extensions of the geometric approach, and identifying high-impact applications to climate change, machine learning and artificial intelligence.

The book is suitable for researchers in artificial intelligence, statistics, and applied science engaged with theories of uncertainty. The book is supported with the most comprehensive bibliography on belief and uncertainty theory.

Risk shapes , and is shaped by, migration: although widely acknowledged, this is unevenly, and mostly only implicitly, theorised and analysed. Starting from the distinction between risk and uncertainty, the paper contrasts the different approaches of economics and sociology to theorising risk, in terms of scale, social construction ism, and being informed by risk as opposed to being at risk. It reviews the extent to which six theoretical approaches have been, and could be, applied to migration, risk, and uncertainty: human capital, risk tolerance , new economics of migration, risk and culture, risk society, and governmentality.

Computer vision is an ever growing discipline whose ambitious goal is to enable machines with the intelligent
visual skills humans and animals are provided by Nature, allowing them to interact effortlessly
with complex, dynamic environments. Designing automated visual recognition and sensing systems
typically involves tackling a number of challenging tasks, and requires an impressive variety of sophisticated
mathematical tools. In most cases, the knowledge a machine has of its surroundings is at best
incomplete – missing data is a common problem, and visual cues are affected by imprecision. The need
for a coherent mathematical ‘language’ for the description of uncertain models and measurements then
naturally arises from the solution of computer vision problems.

The theory of evidence (sometimes referred to as ‘evidential reasoning’, ‘belief theory’ or ‘Dempster-
Shafer theory’) is, perhaps, one of the most successful approaches to uncertainty modelling, as arguably
the most straightforward and intuitive approaches to a generalized probability theory. Emerging in the
last Sixties from a profound criticism of the more classical Bayesian theory of inference and modelling
of uncertainty, it stimulated in the last decades an extensive discussion of the epistemic nature of both
subjective ‘degrees of beliefs’ and frequentist ‘chances’ or relative frequencies. More recently, a renewed
interest in belief functions, the mathematical generalization of probabilities which are the object of study
of the theory of evidence, has seen a blossoming of applications to a variety of fields of applied science.

In this Book we are going to show how, indeed, the fruitful interaction of computer vision and evidential
reasoning is able stimulate a number of advances in both fields. From a methodological point of
view, novel theoretical advances concerning the geometric and algebraic properties of belief functions as
mathematical objects will be illustrated in some detail in Part II, with a focus on a perspective ‘geometric
approach’ to uncertainty and an algebraic solution of the issue of conflicting evidence. In Part III we will
illustrate how these new perspectives on the theory of belief functions arise from important computer vision
problems, such as articulated object tracking, data association and object pose estimation, to which
in turn the evidential formalism can give interesting new solutions. Finally, some initial steps towards
a generalization of the notion of total probability to belief functions will be taken, in the perspective of
endowing the theory of evidence with a complete battery of estimation and inference tools to the benefit
of scientists and practitioners.

Research on how individual tourists respond to risk has largely focussed on risk perceptions. This paper draws on behavioural economics to analyse the influence of risk tolerance and risk-related competence on how tourists organize their tourism travel, and the importance that they ascribe to specific types of tourism hazards. Whereas most tourism research on risk has been based on small, or highly age-specific surveys, or particular market segments, this paper utilises an innovative, large-scale survey drawn from the range of the UK population. There were significant differences between package tourists and individual ‘drifter’ tourists in terms of their socio-demographic characteristics, general and tourism specific risk tolerance, and competence e both real and illusory e to manage risk. Age, and tolerance of both general and tourism-specific risks, were associated with the importance of hazards as deterrents to tourist behaviour, but the evidence for competences was mixed.

This intervention contributes to recent work in urban geography that integrates the conceptual frameworks of assemblages and actor-network theory by highlighting two additional directions that require a more rigorous and detailed theorization. The first direction concerns the relationship between contingency and necessity in urban assemblages and actor-networks and this paper delineates four specific propositions as a starting point for further reflection. The second direction suggests that urban assemblages and actor-networks require a more explicit vocabulary for thinking about competition and cooperation within and between cities. To this end, the paper introduces a new concept – delayed asymmetric counterforces – that can foster a better understanding of competition-induced urban change and destabilization. The novel concept is developed in conjunction with a typology of delays in competitive urban dynamics, which helps illuminate how delayed asymmetric counterforces are both a cause and an effect of the complexity inherent in the urban realm.

Ambivalence (as in practical conflicts, moral dilemmas, conflicting beliefs, and mixed feelings) is a central phenomenon of human life. Yet ambivalence is incompatible with entrenched philosophical conceptions of personhood, judgement, and action, and is denied or marginalised by thinkers of diverse concerns. This book takes a radical new stance, bringing the study of core philosophical issues together with that of ambivalence. The book proposes new accounts in several areas – including subjectivity, consciousness, rationality, and value – while elucidating a wide range of phenomena expressive of ambivalence, from emotional ambivalence to self-deception. The book rejects the view that ambivalence makes a person divided, showing that our tension-fraught attitudes are profoundly unitary. Ambivalence is not tantamount to confusion or to paralysis: it is always basically rational, and often creative, active, and perceptive as well. The book develops themes from Wittgenstein, Davidson, Sartre, and Freud. It engages with contemporary debates in Analytic Philosophy in addition to work ranging from Aristotle to Cultural Studies and Empirical Psychology, and considers a rich set of examples from daily life and literature.

While academic researchers have proposed various theories for managing risk and uncertainty in construction projects, most of the propositions are conceptual in nature and based on analytical modelling approaches rarely used in practice. This research was triggered by an observation in which a R1.5billion (~$100 million) fast track New Universities Project was successfully delivered within budget despite up to 74% of the project scope not being capable of being priced by the contractor at the start of construction. The aim of this paper was to examine the client's delivery management approach used to successfully manage the uncertainty and deliver within budget. The evidence from document analyses and interviews with the client delivery management team members shows that setting a rigorous control budget, designing to the budget, working collaboratively, disciplined management of the control budget, and continuous value engineering were the key client management techniques used to successfully manage the high degree of uncertainty and deliver the project within budget. Given that these are client-led delivery management issues, the findings fill an important gap in our knowledge and understanding of how infrastructure projects outcomes can be significantly improved upon should the client function as the leader of the delivery process.

Abstract Two important challenges in policy design are better understanding of the design space and consideration of the temporal factors. Moreover, in recent years it has been demonstrated that understanding the complex interactions of policy measures can play an important role in policy design and analysis. In this paper, the advances made in conceptualization and application of networks to policy design in the past decade are highlighted. Specifically, the use of a network-centric policy design approach in better understanding the design space and temporal consequences of design choices are presented. Network-centric policy design approach has been used in classification, visualization, and analysis of the relations among policy measures as well as ranking of policy measures using their internal properties and interactions, and conducting sensitivity analysis using Monte Carlo simulations. Furthermore, through use of a decision support system, network-centric approach facilitates ranking, visualization, and selection of policies using different sets of criteria, and exploring the potential for compromise in policy formulation. The advantage of the network-centric approach is providing the ability to go beyond visualizations and analysis of policies and piecemeal use of network concepts as a
tool for different policy design tasks to moving to a more integrated bottom–up approach to design. Furthermore, the computational advantages of the network-centric policy design in considering temporal factors such as policy sequencing and addressing issues such as layering, drift, policy failure, and delay are presented. Finally, some of the current challenges of network-centric design are discussed, and some potential avenues of exploration in policy design through use of computational methodologies, as well as possible integration with approaches from other disciplines, are highlighted.

Divine Command Theories (DCTs) comes in several different forms but at their core all of these theories claims that certain moral statuses (most typically the status of being obligatory) exist in virtue of the fact that God has commanded them to exist. Several authors argue that this core version of the DCT is vulnerable to an epistemological objection. According to this objection, DCT is deficient because certain groups of moral agents lack epistemic access to God's commands. But there is confusion as to the precise nature and significance of this objection, and critiques of its key premises. In this article I try to clear up this confusion and address these critiques. I do so in three ways. First, I offer a simplified general version of the objection. Second, I address the leading criticisms of the premises of this objection, focusing in particular on the role of moral risk/uncertainty in our understanding of God's commands. And third, I outline four possible interpretations of the argument, each with a differing degree of significance for the proponent of the DCT.

Actors in competitive environments are bound to decide and act under conditions of uncertainty because they rarely have accurate foreknowledge of how their opponents will respond and when they will respond. Just as a competitor makes a move to improve their standing on a given variable relative to a target competitor, she should expect the latter to counteract with an iterative lagged asymmetric response, that is, with a sequence of countermoves (iteration) that is very different in kind from its trigger (asymmetry) and that will be launched at some unknown point in the future (time lag). The paper explicates the broad relevance of the newly proposed concept of " iterative lagged asymmetric responses " to the social study of temporality and to fields as diverse as intelligence and counterintelligence studies, strategic management, futures studies, military theory, and long-range planning. By bringing out in the foreground and substantiating the observation that competitive environments place a strategic premium on surprise, the concept of iterative lagged asymmetric responses makes a contribution to the never-ending and many-pronged debate about the extent to which the future can be predicted.
DOI: https://doi.org/10.1177/0961463X17752652

The connection between climate scepticism and climate denial and what has become known as post-truth culture has become the subject of much interest in recent years, leading to intense debates among scientists and activists about how to respond to this changed cultural context and the ways in which it is held to obstruct wider acceptance of climate science. Drawing on research in the sociology of scientific knowledge, science and technology studies, social psychology and philosophical reflections on evidential reasoning, it is argued that these debates are focused on the wrong topic. The idea of post-truth implies that a once-straightforward linear relationship between scientific evidence and decisions on what to do has been eroded. But such an idealised relationship never existed. The proper role of scientific evidence in informing belief and action in response to the prospect of anthropogenic climate change needs reconsideration. A key part of this is to make uncertainties related to processes within the climate system and their potential outcomes into the main focus of public discussion around climate change. Instead of keeping the focus of debate on how to 'get the science right', such a reframing makes precautionary questions about the prospect of unacceptable losses into the main focus, bringing a variety of ethical and political values into the debate, and perhaps creating better conditions for a minimal consensus about what to do.

Previous studies have led to hypothesizing that right DLPFC activity is related to risk propensity, but the generality of this relationship remains unclear. Here, we experimentally modulated DLPFC activity in 47 healthy, female volunteers during a risky decision-making task, where monetary gambles defined by potential win, loss, and outcome probability were evaluated in the absence of feedback and uncertainty. Three participant groups, receiving left anodal/right cathodal, right anodal/left cathodal, and sham tDCS, were compared. Overall, participants performed the task well above chance level and were significantly risk averse, but tDCS did not affect task performance or risk propensity. However, right anodal/left cathodal tDCS significantly elevated response confidence, independently of accept/reject response. Our results suggest that the relationship between DLPFC activity and risk propensity may not be universally valid for all task types and requires further characterization. Enhancing right and attenuating left DLPFC activity boosts subjective confidence, with potential implications for understanding pathological gambling.

This paper argues that historical analysis, necessarily written with hindsight, often underestimates the uncertainties of the past. We call this tendency explanation bias. This bias leads individuals-including professional historians-to imply greater certainty in causal analyses than the evidence justifies. Their analyses will treat what is plausible to be probable. We offer a few intuitions about why explanation bias exists, its relation to other well-established psychological biases, what it leads to, and how it might be combatted. Appreciating the depth of uncertainty and ignorance in our world is critical for accurately understanding, interpreting, and drawing from the past to illuminate the present and the near future.

Conceptualising risk and uncertainty in transport policy
Hossen, A. and Hine, j.
Ulster University, Built Environment Research Institute, Shore Road, Newtownabbey, Co. Antrim BT37 0QB Northern Ireland.
A theoretical review of the literature on concepts of risk and uncertainty in transport policy has shown that policy makers have become increasingly aware of the importance of risk and uncertainty associated with climate change and extreme weather conditions poses for the transport sector and transport policy. The aim of this review paper is to investigate the literature on risk and uncertainty in transport policy and appraisal and also explore how these issues are handled by policy and decision-makers. The paper examines how risk and uncertainty are approached within transport policy and the transport appraisal process. Indeed, risk is now often handled with uncertainty as concepts that are similar in scope and nature.  There is currently however little research to suggest how these two concepts are handled and also indeed how they impact on decision-making.  To date research on risk and uncertainty has been descriptive approach rather than empirical. This paper indicates that in order to address the complex nature of risk and uncertainty research is required to explore how these concepts are defined and operationalised in transport and decision-making practice.

Key words: risk; Uncertainty; Transport policy; decision-making; Transport appraisal.

It is uncontroversial that poor public policy undermines entrepreneurial behavior and reduces public welfare. However, the exact mechanisms by which policy interventions affect entrepreneurial behavior are often unclear. This paper contrasts two competing theories of the relation between public policy and entrepreneurship: the theory of entrepreneurial incentives suggested by Israel Kirzner, and the theory of economic calculation and judgment proposed by Ludwig von Mises and Joseph T. Salerno. I argue that the alertness theory provides inadequate grounding for policy analysis because it rests on a paradoxical approach to opportunity discovery. The calculation view, on the other hand, is well-suited for application to policy problems, as it rests on a realistic view of entrepreneurial decision-making.

While academic researchers have proposed various theories for managing risk and uncertainty in construction projects, most of the propositions are conceptual in nature and based on analytical modelling approaches rarely used in practice. This research was triggered by an observation in which a R1.5billion (~$100 million) fast track New Universities Project was successfully delivered within budget despite up to 74% of the project scope not being capable of being priced by the contractor at the start of construction. The aim of this paper was to examine the client's delivery management approach used to successfully manage the uncertainty and deliver within budget. The evidence from document analyses and interviews with the client delivery management team members shows that setting a rigorous control budget, designing to the budget, working collaboratively, disciplined management of the control budget, and continuous value engineering were the key client management techniques used to successfully manage the high degree of uncertainty and deliver the project within budget. Given that these are client-led delivery management issues, the findings fill an important gap in our knowledge and understanding of how infrastructure projects outcomes can be significantly improved upon should the client function as the leader of the delivery process.

This paper is devoted to make a framework for studying a class of uncertain differential equations called Z-differential equations. In order to achieve the purpose, we first introduce four basic operations on Z +-numbers based on semi-granular function. Then, the limit and continuity concepts of a Z-number-valued function are given, under a definition of a metric on the space of Z +-numbers. Moreover, the concepts of Z-differentiability, Z-integral, and Z-Laplace transform of a Z-number-valued function are introduced. In addition, by giving some theories proved in this paper, a basis for calculus-Z-calculus-is established. We further give theories based on which existence and uniqueness of Z-differential equations are investigated. A conceptual unity between Z-differential equations and Z +-numbers is also shown. The conceptual unity demonstrates that a Z-differential equation may be expressed as a bimodal differential equation combining a fuzzy differential equation and a random differential equation. Moreover, the concept of a bimodal cut called (s, µ)-cut is introduced and its relation to other new concepts such as acceptable time and acceptable information area is explained. Using an example, the application of Z-differential equations in medicine is clarified. It is demonstrated that Z-differential equations outperform fuzzy differential equations in making a decision under uncertainty.

In the presence of crisis, such as global COVID-19 pandemic crisis, governments have more and more take critical decisions to cope with consequential environmental threats in the presence of highly restricted time. This chapter provides a simple description of techniques of decision making in different environments/conditionsof crisis management and how that process is influenced by manifold social, economic and/or technical factors; ultimately it is presented how the approach of improvisation can support the process of decision-makingto cope with unforeseen and new events, rapid changes, turbulent environment and/or specific situations of emergency.

Epidemiology and quantitative microbiological risk assessment are disciplines in which the same public health measures are estimated, but results differ frequently. If large, these differences can confuse public health policymakers. This article aims to identify uncertainty sources that explain apparent differences in estimates for Campylobacter spp. incidence and attribution in the Netherlands, based on four previous studies (two for each discipline). An uncertainty typology was used to identify uncertainty sources and the NUSAP method was applied to characterize the uncertainty and its influence on estimates. Model outcomes were subsequently calculated for alternative scenarios that simulated very different but realistic alternatives in parameter estimates, modeling, data handling, or analysis to obtain impressions of the total uncertainty. For the epidemiological assessment, 32 uncertainty sources were identified and for QMRA 67. Definitions (e.g., of a case) and study boundaries (e.g., of the studied pathogen) were identified as important drivers for the differences between the estimates of the original studies. The range in alternatively calculated estimates usually overlapped between disciplines, showing that proper appreciation of uncertainty can explain apparent differences between the initial estimates from both disciplines. Uncertainty was not estimated in the original QMRA studies and underestimated in the epidemiological studies. We advise to give appropriate attention to uncertainty in QMRA and epidemiological studies, even if only qualitatively, so that scientists and policymakers can interpret reported outcomes more correctly. Ideally, both disciplines are joined by merging their strong respective properties, leading to unified public health measures.

Present day complex environmental problems exhibit a number of characteristics that make them hard to tackle with normal scientific procedures. Funtowicz and Ravetz (1993) have called this class of problems post-normal. Typically, political decisions on these problems will need to be made before conclusive scientific evidence is available. Decision stakes are high: the impacts of "wrong" decisions based on the available limited knowledge can be huge. Actors disagree on the values that should guide the decision-making. The available knowledge bases are typically characterized by imperfect understanding (and imperfect reduction into models) of the complex systems involved. Models, scenarios, and assumptions dominate assessment of these problems, and many (hidden) value loadings reside in problem frames, indicators chosen, and assumptions made.

A review of "Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263. https://doi.org/10.2307/1914185", as part of a weekly assignment for Harvard's MCB 145: Neurobiology of Perception and Decision Making.

We make decisions every day without realizing that an intricate algorithm inside our heads is at play, helping us choose the best possible outcomes for our interests. Some of these decisions are made under risk, making the process more complicated and of higher significance. Several theories have been developed to assess how humans make decisions under risk, one of which is the expected utility theory. This theory has been deemed an accurate normative model for rational choices and a fine descriptive model of economic behavior. The expected utility theory comes with certain axioms, sub-rules that are considered to be true. In the paper that forms the basis of this report, authors Daniel Kahneman and Amos Tversky suggest that there are certain choice problems whose respondents systematically violate the axioms of the expected utility theory by making choices that go against the rules and predictions of the expected utility theory. This inaccuracy of the expected utility theory leads the authors to propose a new model to explain decision under risk, called the prospect theory.

To investigate the influence of the sense of psychological power on decision making under risk, we conducted an experiment with 60 participants and found evidence which suggests that a heightened sense of power results in excessive risk-taking. We primed the experimental group with a high-power mindset and the control group with a neutral mindset and asked participants to answer a series of hypothetical questions on expected value. The results of a chi-square test suggest that participants who were primed with a heightened sense of power focus on high but unlikely rewards. When the potential reward was greater than the loss, power-primed people were swayed towards the rewards despite the unfavorable probabilities. We propose that there is a link between a heightened sense of power and suboptimal economic decision making, and model this in the Prospect Theory framework.

Health and social care services have experienced a decade or more of messages to become more person-centred, to listen more to people and deliver on the priorities they want for themselves. This requires a fundamentally positive mindset from professionals and care workers, and a willingness to take some risks. How will this apply to delivering dementia services, where almost all of the initial impressions are of deficits, disability and disadvantage? This paper explores the well-intentioned policy framework established through the Mental Capacity Act 2005, current trends in safeguarding vulnerable people, and the focus on well-being in the Care Act 2014. Practitioners also face a range of challenges when it comes to supporting people living with dementia to exercise personal choices and take risks through their own decisions. We share practical tips on how to deliver positive risk-taking with people living with dementia.

The standard approach to the problem of banks' loan-making behavior under uncertainty considers the screening activity as a "black box" which transforms information into decisions. Relevant issues such as the organization of the loan function, and the nature and sources of uncertainty are usually neglected. Both issues are investigated in this paper. Following the Sah/Stiglitz's (1985, 1986) approach to the architecture of economic systems, we check which of the architectures, when applied to the organization of the bank, brings to an effective management of the risk arising from the loan-making activity. Unfortunately, the Sah/Stiglitz's solution is too weak. A more robust one is developed in this paper, where we apply the Heiner's (1983) approach to true uncertainty to derive a model for banks' loan procedures. Our main result is the formalization of realistic features of ordinary banking life (such as the limit of autonomy, the multiple-stage evaluation procedure, the reservation of the more refined screening techniques just to big loans and to highly specialized staff) in a model of limited-hierarchy organization of the credit function.

This study suggests that, despite the decisive function of scientific risk assessment in the regulation of potentially hazardous technologies, conventional political de-cision-making prevails if in protracted risk controversies scientific consensus can-not be achieved. An examination of Austria’s policy on agricultural biotechnology is presented to illustrate this point: For a number of years Austria has been up-holding national bans on various Genetically Modified Organisms (GMOs) even though these bans were deemed illegal by the European Commission as well as a WTO Dispute Settlement Jury. Since European and international regulations re-quire restrictions on biotech-products to be based on scientific evidence, for the longest time the dispute between Austria and the European Commission, seeking to lift the Austrian ban, consisted in the exchange of scientific opinions. When in-ternational pressure against the Austrian ban rose after a WTO judgment censuring the Austrian measure, only a political solution could bring about a (still provi-sional) settlement. The process is discussed against the backdrop of sociological debates questioning the pivotal status of science in government.