Decision-makers face severe uncertainty when they are not in a position to assign precise probabilities to all of the relevant possible outcomes of their actions. Such situations are common—novel medical treatments and policies addressing climate change are two examples. Many decision-makers respond to such uncertainty in a cautious manner and are willing to incur a cost to avoid it. There are good reasons for taking such an uncertainty-averse attitude to be permissible. However, little work has been (...) done to incorporate it into an egalitarian theory of distributive justice. We aim to remedy this lack. We put forward a novel, uncertainty-averse egalitarian view. We analyse when the aims of reducing inequality and limiting the burdens of severe uncertainty are congruent and when they conflict, and highlight practical implications of the proposed view. We also demonstrate that if uncertainty aversion is permissible, then utilitarians must relinquish a favourite argument against egalitarianism. (shrink)

This Special Issue titled "Severe Uncertainty in Science, Medicine and Technology" aims to shed new light on the understanding of severe uncertainty and its multifaceted implications. The main idea of the papers of this collection is that, despite possible sophisticated statistical judgments towards future risks in science, medicine, and technology, severe forms of uncertainty still exist.While ignorance is usually assumed to be a total absence of knowledge, uncertainty often refers to the incompleteness of (...) knowledge or information. In its extreme form, this is called "severe uncertainty" but is also known as "fundamental," "radical," "deep," "great," or "genuine" uncertainty. A common characteristic of these... (shrink)

In some severely uncertain situations, exemplified by climate change and novel pandemics, policymakers lack a reasoned basis for assigning probabilities to the possible outcomes of the policies they must choose between. I outline and defend an uncertainty averse, egalitarian approach to policy evaluation in these contexts. The upshot is a theory of distributive justice which offers especially strong reasons to guard against individual and collective misfortune.

This paper presents a case of severe uncertainty in the development of autonomous and intelligent systems in Artificial Intelligence and autonomous robotics. After discussing how uncertainty emerges from the complexity of the systems and their interaction with unknown environments, the paper describes the novel framework of explorative experiments. This framework presents a suitable context in which many of the issues relative to uncertainty, both at the epistemological level and at the ethical one, in this field should (...) be reframed. The case of autonomous robot systems for search and rescue is used to make the discussion more concrete. (shrink)

Journal of Political Philosophy, Volume 30, Issue 3, Page 370-394, September 2022.

As well as disagreeing about how much one should donate to charity, moral theories also disagree about where one should donate. In light of this disagreement, how should the morally uncertain philanthropist allocate her donations? In many cases, one intuitively attractive option is for the philanthropist to split her donations across all of the charities that are recommended by moral views in which she has positive credence, with each charity’s share being proportional to her credence in the moral theories that (...) recommend that particular charity. Despite the fact that something like this approach is already being used by real-world philanthropists to distribute billions of dollars of donations, it is not supported by any of the approaches to moral uncertainty that have been proposed thus-far in the philosophical literature. In this paper, we will develop a bargaining-based approach to moral uncertainty that honors the proportionality intuition in favor of splitting one’s donations. We also show how this bargaining-based approach has several further advantages over the best alternative proposals. (shrink)

Several philosophers have recently argued that decision-theoretic frameworks for rational choice under risk fail to provide prescriptions for choice in cases of moral uncertainty. They conclude that there are no rational norms that are “sensitive” to a decision maker’s moral uncertainty. But this chapter argues that one sometimes has a rational obligation to take one’s moral uncertainty into account in the course of moral deliberation. It first provides positive motivation for the view that one’s moral beliefs can (...) affect what it is rational for one to choose. It then addresses the problem of value comparison, according to which one cannot determine the expected moral value of one’s actions. The chapter argues that we should not infer from the problem of value comparison that there are no rational norms governing choice under moral uncertainty. (shrink)

Environmental risk assessment is often affected by severe uncertainty. The frequently invoked precautionary principle helps to guide risk assessment and decision-making in the face of scientific uncertainty. In many contexts, however, uncertainties play a role not only in the application of scientific models but also in their development. Building on recent literature in the philosophy of science, this paper argues that precaution should be exercised at the stage when tools for risk assessment are developed as well as (...) when they are used to inform decision-making. The relevance and consequences of this claim are discussed in the context of the threshold of the toxicological concern approach in food toxicology. I conclude that the approach does not meet the standards of an epistemic version of the precautionary principle. (shrink)

Several philosophers have recently argued that decision-theoretic frameworks for rational choice under risk fail to provide prescriptions for choice in cases of moral uncertainty. They conclude that there are no rational norms that are “sensitive” to a decision-maker's moral uncertainty. But in this paper, I argue that one sometimes has a rational obligation to take one's moral uncertainty into account in the course of moral deliberation. I first provide positive motivation for the view that one's moral beliefs (...) can affect what it's rational for one to choose. I then address the problem of value comparison, according to which one cannot determine the expected moral value of one's actions. I argue that we should not infer from the problem of value comparison that there are no rational norms governing choice under moral uncertainty. (shrink)

In their insightful article, Brent Kious and Margaret Battin (2019) correctly identify an inconsistency between an involuntary psychiatric commitment for suicide prevention and physician aid in dying (PAD). They declare that it may be possible to resolve the problem by articulating “objective standards for evaluating the severity of others’ suffering,” but ultimately they admit that this task is beyond the scope of their article since the solution depends on “a deep and difficult” question about comparing the worseness of two possible (...) scenarios: letting someone die (who could have been helped) with not letting someone die (whose suffering could only be alleviated by death). In our commentary, we argue that creating such standards is more difficult than the authors assume because of the many types of deep uncertainties we have to deal with: (1) diagnostic, (2) motivational, and (3) existential. (shrink)

According to ‘Excluders’, descriptive uncertainty – but not normative uncertainty – matters to what we ought to do. Recently, several authors have argued that those wishing to treat normative uncertainty differently from descriptive uncertainty face a dependence problem because one's descriptive uncertainty can depend on one's normative uncertainty. The aim of this paper is to determine whether the phenomenon of dependence poses a decisive problem for Excluders. I argue that existing arguments fail to show (...) this, and that, while stronger ones can be found, Excluders can escape them. (shrink)

This book explains the notational system NUSAP (Numeral, Unit, Spread, Assessment, Pedigree) and applies it to several examples from the environmental sciences.

In this paper we compare different models of vagueness viewed as a specific form of subjective uncertainty in situations of imperfect discrimination. Our focus is on the logic of the operator “clearly” and on the problem of higher-order vagueness. We first examine the consequences of the notion of intransitivity of indiscriminability for higher-order vagueness, and compare several accounts of vagueness as inexact or imprecise knowledge, namely Williamson’s margin for error semantics, Halpern’s two-dimensional semantics, and the system we call Centered (...) semantics. We then propose a semantics of degrees of clarity, inspired from the signal detection theory model, and outline a view of higher-order vagueness in which the notions of subjective clarity and unclarity are handled asymmetrically at higher orders, namely such that the clarity of clarity is compatible with the unclarity of unclarity. (shrink)

Prognosis after severe brain injury is highly uncertain, and decisions to withhold or withdraw life‐sustaining treatment are often made prematurely. These decisions are often driven by a desire to avoid a situation where the patient becomes ‘trapped’ in a condition they would find unacceptable. However, this means that a proportion of patients who would have gone on to make a good recovery, are allowed to die. I propose a shift in practice towards the routine provision of aggressive care, even (...) in cases where the probability of survival and acceptable recovery is thought to be low. In conjunction with this shift, I argue in favour of a presumption towards withdrawing life‐sustaining treatment, including artificial nutrition and hydration, when it becomes clear that a patient will not recover to a level that would be acceptable to them. I then respond to three potential objections to this proposal. (shrink)

Sometimes it’s not certain which of several mutually exclusive moral views is correct. Like almost everyone, I think that there’s some sense in which what one should do depends on which of these theories is correct, plus the way the world is non-morally. But I also think there’s an important sense in which what one should do depends upon the probabilities of each of these views being correct. Call this second claim “moral uncertaintism”. In this paper, I want to address (...) an argument against moral uncertaintism offered in the pages of this journal by Brian Weatherson, and seconded elsewhere by Brian Hedden, the crucial premises of which are: that acting on moral uncertaintist norms necessarily involves motivation by reasons or rightness as such, and that such motivation is bad. I will argue that and are false, and that at any rate, the quality of an agent’s motivation is not pertinent to the truth or falsity of moral uncertaintism in the way that Weatherson’s and Hedden’s arguments require. (shrink)

In ‘Normative Uncertainty as a Voting Problem’, William MacAskill argues that positive credence in ordinal-structured or intertheoretically incomparable normative theories does not prevent an agent from rationally accounting for her normative uncertainties in practical deliberation. Rather, such an agent can aggregate the theories in which she has positive credence by methods borrowed from voting theory—specifically, MacAskill suggests, by a kind of weighted Borda count. The appeal to voting methods opens up a promising new avenue for theories of rational choice (...) under normative uncertainty. The Borda rule, however, is open to at least two serious objections. First, it seems implicitly to ‘cardinalize’ ordinal theories, and so does not fully face up to the problem of merely ordinal theories. Second, the Borda rule faces a problem of option individuation. MacAskill attempts to solve this problem by invoking a measure on the set of practical options. But it is unclear that there is any natural way of defining such a measure that will not make the output of the Borda rule implausibly sensitive to irrelevant empirical features of decision-situations. After developing these objections, I suggest an alternative: the McKelvey uncovered set, a Condorcet method that selects all and only the maximal options under a strong pairwise defeat relation. This decision rule has several advantages over Borda and mostly avoids the force of MacAskill’s objection to Condorcet methods in general. (shrink)

Uncertainty and affect are fundamental and interrelated aspects of the human condition. Uncertainty is often associated with negative affect, but in some circumstances it is associated with positive affect. In this paper, we review different explanations for the varying relationship between uncertainty and affect. We identify “mental simulation” as a key process that links uncertainty to affective states. We suggest that people have a propensity to simulate negative outcomes, which results in a propensity towards negative affective (...) responses to uncertainty. We also propose the existence of several important moderators of this process, including context and individual differences such as uncertainty tolerance, as well as emotion regulation strategies. Finally, we highlight important knowledge gaps and promising areas for future research, both empirical and conceptual, to further elucidate the relationship between uncertainty and affect. (shrink)

It is important to have an adequate model of uncertainty, since decisions must be made before the uncertainty can be resolved. For instance, flood defenses must be designed before we know the future distribution of flood events. It is standardly assumed that probability theory offers the best model of uncertain information. I think there are reasons to be sceptical of this claim. I criticise some arguments for the claim that probability theory is the only adequate model of (...) class='Hi'>uncertainty. In particular I critique Dutch book arguments, representation theorems, and accuracy based arguments. Then I put forward my preferred model: imprecise probabilities. These are sets of probability measures. I offer several motivations for this model of uncertain belief, and suggest a number of interpretations of the framework. I also defend the model against some criticisms, including the so-called problem of dilation. I apply this framework to decision problems in the abstract. I discuss some decision rules from the literature including Levi’s E-admissibility and the more permissive rule favoured by Walley, among others. I then point towards some applications to climate decisions. My conclusions are largely negative: decision making under such severe uncertainty is inevitably difficult. I finish with a case study of scientific uncertainty. Climate modellers attempt to offer probabilistic forecasts of future climate change. There is reason to be sceptical that the model probabilities offered really do reflect the chances of future climate change, at least at regional scales and long lead times. Indeed, scientific uncertainty is multi-dimensional, and difficult to quantify. I argue that probability theory is not an adequate representation of the kinds of severe uncertainty that arise in some areas in science. I claim that this requires that we look for a better framework for modelling uncertainty. (shrink)

In the case that triggered this round-table discussion there are three separate factors that contribute to moral uncertainty.1 First, the infant, baby T, is extremely premature with suspected brain injury and potentially poor prognosis. Second, the gestational mother is critically unwell herself and her outlook is guarded. Third, as linked commentaries make clear, the legal status of the intended parents is complex and ambiguous.2 3 Any of these factors on their own would be enough to generate ethical complexity and (...) distress in the neonatal intensive care unit. The combination of the three is likely to be highly stressful for all concerned.4 Commentaries on the case emphasise the complex legal questions and the potential need to involve the court. One resource that is not mentioned is the potential value of clinical ethics input in such a case. This is complementary to the need for legal advice. Its aim would be to help think through the specifically ethical, rather than legal questions. There are several things that I would aim to clarify if chairing a clinical ethics discussion on the case. First, it may be useful to draw on the concept of the …. (shrink)

Many studies claim to measure decision-making under risk by employing the Domain-Specific Risk-Taking (DOSPERT) scale, a self-report measure, or the Balloon Analogue Risk Task (BART), a behavioural task. However, these tasks do not measure decision-making under risk but decision-making under uncertainty, a related but distinct concept. The present commentary discusses both the theoretical and empirical basis of the distinction between uncertainty and risk from the viewpoint of several scientific disciplines and reports how many studies wrongfully employ the DOSPERT (...) scale and BART as risk-taking measures. Importantly, we call for proper distinguishing between (tasks measuring) decision-making under uncertainty and decision-making under risk in psychology and related fields. We believe this is vital as research has shown that people’s attitudes, behaviour, and brain activity differ between both concepts, indicating that confusing the concepts may lead researchers to erroneous conclusions. (shrink)

What is uncertainty? There are of course several possible definitions, offered by different fields, from epistemology to statistics, but, in the background, one usually finds some kind of relation with the lack of information, in the following sense. Suppose we define semantic or factual information as the combination of a question plus the relevant, correct answer. If one has both the question and the correct answer, one is informed: “was Berlin the capital of Germany in 2010? Yes”. If one (...) has the question but the incorrect answer, one is insipient. If one has neither, one is ignorant. And if one has only the question but not the answer, then one is uncertain. Uncertainty is what a correct answer to a relevant question erases. This is why, in information theory, the value of information is often discussed in terms of the amount of uncertainty that it decreases. And this is also why there are many things in life that we value, but uncertainty is not usually one of them. At first sight, .. (shrink)

This book offers a philosophically-based, yet clinically-oriented perspective on current medical reasoning aiming at 1) identifying important forms of uncertainty permeating current clinical reasoning and practice 2) promoting the application of an abductive methodology in the health context in order to deal with those clinical uncertainties 3) bridging the gap between biomedical knowledge, clinical practice, and research and values in both clinical and philosophical literature. With a clear philosophical emphasis, the book investigates themes lying at the border between several (...) disciplines, such as medicine, nursing, logic, epistemology, and philosophy of science; but also ethics, epidemiology, and statistics. At the same time, it critically discusses and compares several professional approaches to clinical practice such as the one of medical doctors, nurses and other clinical practitioners, showing the need for developing a unified framework of reasoning, which merges methods and resources from many different clinical but also non-clinical disciplines. In particular, this book shows how to leverage nursing knowledge and practice, which has been considerably neglected so far, to further shape the interdisciplinary nature of clinical reasoning. Furthermore, a thorough philosophical investigation on the values involved in health care is provided, based on both the clinical and philosophical literature. The book concludes by proposing an integrative approach to health and disease going beyond the so-called “classical biomedical model of care”. (shrink)

A number of the men who would become the 9/11 hijackers were stopped for minor traffic violations. They were pulled over by police officers for speeding or caught by random inspection without a driver’s license. For United States government commissions and the press, these brushes with the law were missed opportunities. For some police officers though, they were of personal and professional significance. These officers replayed the incidents of contact with the 19 men, which lay bare the uncertainty of (...) every encounter, whether a traffic stop, or with someone taking photos of a landmark. Representatives from law enforcement began to design policies to include local police in national intelligence, with the idea of capitalizing on what patrol officers already do in dealing with the general public. Several initiatives were launched, among these, the Suspicious Activity Reporting Initiative. Routine reporting of suspicious activity was developed into steps for gathering, assessing and sharing terrorism-related information with a larger law enforcement and intelligence network. Through empirical analysis of counterterrorism efforts and recent scholarship on it, this chapter discusses prevention, preemption, and anticipation as three technologies of security, focusing on how each deals with uncertainty. The Suspicious Activity Reporting Initiative, this analysis suggests, is an anticipatory technology which constitutes police officers and intelligence analysts as subjects who work in a mode of uncertainty. (shrink)

Over the last several years, there has been an explosion of interest and attention devoted to the problem of Uncertainty Quantification (UQ) in climate science—that is, to giving quantitative estimates of the degree of uncertainty associated with the predictions of global and regional climate models. The technical challenges associated with this project are formidable, and so the statistical community has understandably devoted itself primarily to overcoming them. But even as these technical challenges are being met, a number of (...) persistent conceptual difficulties remain. So why is UQ so important in climate science? UQ, I would like to argue, is first and foremost a tool for communicating knowledge from experts to policy makers in a way that is meant to be free from the influence of social and ethical values. But the standard ways of using probabilities to separate ethical and social values from scientific practice cannot be applied in a great deal of climate modeling, because the roles of values in creating the models cannot be discerned after the fact—the models are too complex and the result of too much distributed epistemic labor. I argue, therefore, that typical approaches for handling ethical/social values in science do not work well here. (shrink)

We discuss several features of coherent choice functions—where the admissible options in a decision problem are exactly those that maximize expected utility for some probability/utility pair in fixed set S of probability/utility pairs. In this paper we consider, primarily, normal form decision problems under uncertainty—where only the probability component of S is indeterminate and utility for two privileged outcomes is determinate. Coherent choice distinguishes between each pair of sets of probabilities regardless the “shape” or “connectedness” of the sets of (...) probabilities. We axiomatize the theory of choice functions and show these axioms are necessary for coherence. The axioms are sufficient for coherence using a set of probability/almost-state-independent utility pairs. We give sufficient conditions when a choice function satisfying our axioms is represented by a set of probability/state-independent utility pairs with a common utility. (shrink)

This book is an extensive survey and critical examination of the literature on the use of expert opinion in scientific inquiry and policy making. The elicitation, representation, and use of expert opinion is increasingly important for two reasons: advancing technology leads to more and more complex decision problems, and technologists are turning in greater numbers to "expert systems" and other similar artifacts of artificial intelligence. Cooke here considers how expert opinion is being used today, how an expert's uncertainty is (...) or should be represented, how people do or should reason with uncertainty, how the quality and usefulness of expert opinion can be assessed, and how the views of several experts might be combined. He argues for the importance of developing practical models with a transparent mathematic foundation for the use of expert opinion in science, and presents three tested models, termed "classical," "Bayesian," and "psychological scaling." Detailed case studies illustrate how they can be applied to a diversity of real problems in engineering and planning. (shrink)

An important epistemic issue in climate modelling concerns structural uncertainty: uncertainty about whether the mathematical structure of a model accurately represents its target. How does structural uncertainty affect our knowledge and predictions about the climate? How can we identify sources of structural uncertainty? Can we manage the effect of structural uncertainty on our knowledge claims? These are some of the questions that an epistemology of structural uncertainty faces, and these questions are also important for (...) climate scientists and policymakers. I develop three desiderata for an epistemological account of structural uncertainty. In my view, an account of structural uncertainty should identify sources of structural uncertainty, explain how these sources limit the applicability of a model, and show how the severity of structural uncertainty depends on the questions that can be asked of a model. I argue that analyzing structural uncertainty by paying attention to the details of model building can satisfy these desiderata. I focus on parametrizations, which are representations of important processes occurring at scales that are not resolved by climate models. Parametrizations are often thought to be ad-hoc, but I show that some important parametrizations are theoretically justified by explicit or implicit scale separation assumptions. These assumptions can also be supported empirically. Analyzing these theoretical and empirical justificatory roles of the scale separation assumptions can provide insights into how parametrizations contribute to structural uncertainty. I conclude by sketching how my approach can satisfy the desiderata I set out at the beginning, highlighting its importance for policy-relevant scientific statements about the climate. (shrink)

To counter the pandemic caused by severe acute respiratory syndrome coronavirus 2, some have proposed accelerating SARS-CoV-2 vaccine development through controlled human infection trials. These trials would involve the deliberate exposure of relatively few young, healthy volunteers to SARS-CoV-2. We defend this proposal against the charge that there is still too much uncertainty surrounding the risks of COVID-19 to responsibly run such a trial.

The purpose of this paper is to clarify the role of value uncertainty and value instability in decision-making that concerns morally controversial issues. Value uncertainty and value instability are distinguished from moral uncertainty, and several types of value uncertainty and value instability are defined and discussed. The relations between value uncertainty and value instability are explored, and value uncertainty is illustrated with examples drawn from the social sciences, medicine and everyday life. Several types of (...) factor producing value uncertainty and/or value instability are then identified. They are grouped into three categories and discussed under the headings ‘value framing’, ‘ambivalence’ and ‘lack of self-knowledge’. The paper then discusses the role of value uncertainty in decision-making. The concluding remarks summarize what has been achieved and what remains to be done in this area. (shrink)

The aim of this thesis is to improve our understanding of how to assess and communicate uncertainty in areas of research deeply afflicted by it, the assessment and communication of which are made more fraught still by the studies’ immediate policy implications. The IPCC is my case study throughout the thesis, which consists of three parts. In Part 1, I offer a thorough diagnosis of conceptual problems faced by the IPCC uncertainty framework. The main problem I discuss is (...) the persistent ambiguity surrounding the concepts of ‘confidence’ and ‘likelihood’; I argue that the lack of a conceptually valid interpretation of these concepts compatible with the IPCC uncertainty guide’s recommendations has worrying implications for both the IPCC authors’ treatment of uncertainties and the interpretability of the information provided in the AR5. Finally, I show that an understanding of the reasons behind the IPCC’s decision to include two uncertainty scales can offer insights into the nature of this problem. In Part 2, I review what philosophers have said about model-based robustness analysis. I assess several arguments that have been offered for its epistemic import and relate this discussion to the context of climate model ensembles. I also discuss various measures of independence in the climate literature, and assess the extent to which these measures can help evaluate the epistemic import of model robustness. In Part 3, I explore the notion of the ‘weight of evidence’ typically associated with Keynes. I argue that the Bayesian is bound to struggle with this notion, and draw some lessons from this fact. Finally, I critically assess some recent proposals for a new IPCC uncertainty framework that significantly depart from the current one. (shrink)

The view from inside improves our understanding on market failure and regulation failure in financial market. The EMH fails to understand the causes of financial bubbles and crashes. Behavioral finance introduces insight from psychology. The heuristic and biases approach studied behavioral asymmetry in static environment that leads to market irrationality and information distortion. The fast and frugal thinking in decision-making further explore more complex situation under changing environment. They argue that soft-paternalistic regulation is needed under information overload. The most critical (...) issue is information uncertainty and complexity. Lacking information in frequency domain is the main barrier in managing business cycles. Data form inside reveals current limitations of financial data mainly in the short-term price changes. Microstructure studies show that pricing process is shaped by trading rules. Quantitative analysis reveals severe instability in high frequency trading and derivative market. Feasible regulation should aim to encourage new technology and sustainable growth, rather than protect obsolete technology and short-term speculation. The most fundamental challenge to sustainable economic order is the excessive size of the derivative markets that crowding out investment in real economy. This is a more severe issue than the climate change. (shrink)

In the traditional conception of science one assumes that science produces results which are certain and precise. It is argued that this picture is flawed and needs to be replaced with a view where uncertainty and imprecision are an integral part of the scientific enterprise. Uncertainty is still poorly understood by many practising scientists. However, several developments in science indicate that some epistemological uncertainty, e.g. due to processes of abstraction and idealization, will always follow advances in scientific (...) knowledge. There are also other developments that indicate some principal ontological uncertainties, i.e. uncertainties that are due to how the world is. Complexity is one such example. Remarks on post-normal science are thus included. This paper argues, therefore, that scientific uncertainty is a multi-dimensional concept, and that it is unavoidable because it is often the result as much as the cause of new knowledge. (shrink)

This paper presents a unifying diagnosis of a number of important problems facing existing models of rational choice under moral uncertainty and proposes a remedy. I argue that the problems of (i) severely limited scope, (ii) intertheoretic comparisons, and (iii) 'swamping’ all stem from the way in which values are assigned to options in decision rules such as Maximisation of Expected Choiceworthiness. By assigning values to options under a given moral theory by asking something like ‘how much do I (...) desire this option, supposing this theory is true?’ rather than ‘how much value does this theory assign to this option?’ these problems can be avoided, while the appealing features of these accounts can be preserved. This amendment provides a role for the preferences, desires, or goals of rational agents that is curiously absent from the existing discussion of what individuals rationally ought to do when they are uncertain about what they morally ought to do. (shrink)

This paper considers the relationship between quantum uncertainty and the problem of God. Among the issues considered are the existence and essence ofGod, divine action, human freedom, and personal identity. In recent discussions concerning the relative merits of science and religion, thinkers like Ian Barbourand John Haught have suggested several such credible, albeit tentative, connections between the two on the basis of the epistemological limit imposed upon human knowledge by the Heisenberg Uncertainty Principle.

Nanotechnology has been established as a priority research and policy focus, cutting across several R&D fields from pharmaceutics, food and electronics. The raise of nanotechnologies has been accompanied by an enduring uncertainty characterising the developments of the scientific knowledge related to this field, as well as the social trajectories of technological applications. Such a condition inevitably affects regulatory responses to such technologies, their development and their uses. This special issue addresses this junction between uncertainty and regulation. With no (...) ambition of providing a comprehensive assessment of such a complex issue, this collection of articles examines three relevant dimensions for understanding uncertainty in nanotechnology regulation, which can be useful entry points for further reflection and discussion: scientific uncertainty, regulatory fragmentation, social actors’ opinions about and attitudes to nanotechnology and regulation. (shrink)

Food uncertainty has the effect of invigorating food-related responses. Psychologists have noted that mammals and birds respond more to a conditioned stimulus that unreliably predicts food delivery, and ecologists have shown that animals consume and/or hoard more food and can get fatter when access to that resource is unpredictable. Are these phenomena related? We think they are. Psychologists have proposed several mechanistic interpretations, while ecologists have suggested a functional interpretation: The effect of unpredictability on fat reserves and hoarding behavior (...) is an evolutionary strategy acting against the risk of starvation when food is in short supply. Both perspectives are complementary, and we argue that the psychology of incentive motivational processes can shed some light on the causal mechanisms leading animals to seek and consume more food under uncertainty in the wild. Our theoretical approach is in agreement with neuroscientific data relating to the role of dopamine, a neurotransmitter strongly involved in incentive motivation, and its plausibility has received some explanatory and predictive value with respect to Pavlovian phenomena. Overall, we argue that the occasional and unavoidable absence of food rewards has motivational effects that facilitate foraging effort. We show that this hypothesis is computationally tenable, leading foragers in an unpredictable environment to consume more food items and to have higher long-term energy storage than foragers in a predictable environment. (shrink)

Information security governance has become an elusive goal and a murky concept. This paper problematizes both information security governance and the broader concept of governance. What does it mean to govern information security, or for that matter, anything? Why have information technologies proven difficult to govern? And what assurances can governance provide for the billions of people who rely on information technologies every day? Drawing together several distinct bodies of literature—including multiple strands of governance theory, actor–network theory, and scholarship on (...) sociotechnical regimes—this paper conceptualizes networked action on a spectrum from uncertain governance to governing uncertainty. I advance a twofold argument. First, I argue that networks can better govern uncertainty as they become more able not only to enroll actors in a collective agenda, but also to cut ties with those who seek to undermine that agenda. And second, I argue that the dominant conception of information security governance, which emphasizes governing uncertainty through risk management, in practice devolves to uncertain governance. This is largely because information technologies have evolved toward greater connectedness—and with it, greater vulnerability—creating a regime of insecurity. This evolution is illustrated using the history of the US government’s efforts to govern information security. (shrink)

Uncertainty is an intriguing aspect of social life. Uncertainty is epistemic, future-oriented, and implies that we can neither predict nor foresee what will happen when acting. In cases in which no institutionalized certainty about future states exists, or can be generated, judgment is needed. This article presents the forms by which uncertainty is reduced as a result of judgments made about different alternatives in a process involving several actors. This type of uncertainty may exist, for example, (...) about which artist is the best, which offer in the market is more valuable, which football team is better than all the rest, or which research proposal will get a grant. The result of different forms of uncertainty reduction is increased certainty concerning alternatives in relation to one another, such as good and bad, rank lists, scores, quality assessment, and “winner and losers.” Based on the result, uncertainty is reduced and action is facilitated. The forms are structural and comprise roles; may be legitimate in a smaller or larger domain; and may exist in all spheres of life, as exemplified in sports competitions, in labor markets, and in the ranking of universities. Three forms of uncertainty reduction based on judgment are identified in this article: (1) decision, made by an authority; (2) valuation, by means of which order arises as a result of actors ascribing values; and (3) contest, by which an order is the result of direct struggle. (shrink)

Robert Proctor has argued that ignorance or non-knowledge can be fruitfully divided into at least three categories: ignorance as native state or starting point; ignorance as lost realm or selective choice; and ignorance as strategic ploy or active construct. This chapter explores Proctor’s second category, ignorance as selective choice. When scientists investigate poorly understood phenomena, they have to make selective choices about what questions to ask, what research strategies and metrics to employ, and what language to use for describing the (...) phenomena. This chapter focuses especially on the selective choice of language for describing and categorizing phenomena in the face of uncertainty. Using several case studies from recent pollution research, I show that linguistic choices are especially significant when we have severely limited knowledge, because those choices can emphasize and highlight some aspects of our limited knowledge rather than others. These selective emphases can in turn influence societal decision making, and they can exacerbate the selectivity of our knowledge by further steering scientific research in some directions rather than others. I conclude with some suggestions for developing scientific language in socially responsible ways, even in the face of significant ignorance and uncertainty. (shrink)

We recast subjective probabilities by rejecting behaviourist accounts of belief by explicitly distinguishing between judgements of uncertainty and expressions of those judgements. We argue that this entails rejecting that orderings of uncertainty be complete. This in turn leads naturally to several generalizations of the probability calculus. We define probability-like functions over incomplete algebras that reflect a subject’s incomplete judgements of uncertainty. These functions can be further generalized to inner and outer measures that reflect approximate elicitations.

Although the concept of uncertainty is as old as Epicurus’s writings, and an excellent quantitative theory, with entropy as the measure of uncertainty having been developed in recent times, there has been little exploration of the qualitative theory. The purpose of the present paper is to give a qualitative axiomatization of uncertainty, in the spirit of the many studies of qualitative comparative probability. The qualitative axioms are fundamentally about the uncertainty of a partition of the probability (...) space of events. Of course, it is common to speak of the uncertainty, or randomness, of a random variable, but only the partition defined by the values of the random variable enter into the definition of uncertainty, not the actual values. It is straightforward to add axioms for decision making following the general line of Savage from the 1950s. Indeed, in the spirit of Epicurus, it is really our intuitive feeling about the uncertainty of the future that motivates much of our thinking about decisions. Here, the distinction between the concepts of probability and uncertainty can be made by citing many familiar examples. Without spelling out the technical details, the axiomatization of qualitative probability with uncertainty as the most important primitive concept, it is possible to raise a different kind of question about bounded rationality. This new question is whether or not one should bound the uncertainty in thinking and investigating any detailed framework of decision making. Discussion of this point is certainly different from the question of bounding rationality by not maximizing expected utility. In practice, we naturally bound uncertainty in our analysis of decision-making problems. As in the case of formulating an alternative for maximizing expected utility, so is the case of rational alternatives to maximizing uncertainty. There are several issues to consider. In the spirit of my other work in qualitative probability, I explore alternatives rather than attempt to give a definitive argument for one single solution. (shrink)

The precautionary principle may offer an appropriate framework for conducting in‐depth participatory technology assessment (PTA)‐type evaluations. It also holds considerable promise for responsible research and innovation (RRI). The precautionary principle is made up of several different elements and principles. This chapter considers these components, noting from the outset that they relate essentially to scientific evaluation. Probabilities are not particularly helpful in the context of the precautionary principle due to the levels of uncertainty with regard to knowledge of phenomena. In (...) this context, various forms of scenarios, narratives and unjustified inferences are particularly relevant. The chapter also considers more precise ways of identifying decision pathways in uncertain situations, where there is a risk of causing serious and/or irreversible damage, to use the terms given in various definitions of the precautionary principle. This decision can be made using: a utility‐based criterion, right‐based criteria, technology‐based criteria, and hybrid criteria. (shrink)

This paper discusses a novel problem at the intersection of ethics and epistemology: there can be cases in which moral considerations seem to "encroach'' upon belief from multiple directions at once, and possibly to varying degrees, thereby leaving their overall effect on belief unclear. We introduce these cases -- cases of moral encroachment under moral uncertainty -- and show that they pose a problem for all predominant accounts of moral encroachment. We then address the problem, by developing a modular (...) Bayesian framework that, we argue, is sufficiently flexible and scaleable to accommodate the multifaceted uncertainty we describe while still generating clear recommendations for an agent's beliefs. Our framework has several practical upshots, and we close by articulating them: we derive insights about the relationship between moral character and doxastic behavior and make suggestions for how to encourage people to revise their doxastic states in morally laudable ways, without deviating from core Bayesian norms. (shrink)

This paper considers the relationship between quantum uncertainty and the problem of God. Among the issues considered are the existence and essence ofGod, divine action, human freedom, and personal identity. In recent discussions concerning the relative merits of science and religion, thinkers like Ian Barbourand John Haught have suggested several such credible, albeit tentative, connections between the two on the basis of the epistemological limit imposed upon human knowledge by the Heisenberg Uncertainty Principle.

We distinguish three qualitatively different types of uncertainty—ethical, option and state space uncertainty—that are distinct from state uncertainty, the empirical uncertainty that is typically measured by a probability function on states of the world. Ethical uncertainty arises if the agent cannot assign precise utilities to consequences. Option uncertainty arises when the agent does not know what precise consequence an act has at every state. Finally, state space uncertainty exists when the agent is unsure (...) how to construct an exhaustive state space. These types of uncertainty are characterised along three dimensions—nature, object and severity—and the relationship between them is examined. We conclude that these different forms of uncertainty cannot be reduced to empirical uncertainty about the state of the world without inducing an increase in its severity. (shrink)

Much of the theoretical work on strategic voting makes strong assumptions about what voters know about the voting situation. A strategizing voter is typically assumed to know how other voters will vote and to know the rules of the voting method. A growing body of literature explores strategic voting when there is uncertainty about how others will vote. In this paper, we study strategic voting when there is uncertainty about the voting method. We introduce three notions of manipulability (...) for a set of voting methods: sure, safe, and expected manipulability. With the help of a computer program, we identify voting scenarios in which uncertainty about the voting method may reduce or even eliminate a voter's incentive to misrepresent her preferences. Thus, it may be in the interest of an election designer who wishes to reduce strategic voting to leave voters uncertain about which of several reasonable voting methods will be used to determine the winners of an election. (shrink)

The diversity of nanotechnologies and of the governance challenges that their applications raise calls for exploration and learning across different cases. We present an Upstream Oversight Assessment (UOA) of expected benefits and potential harms of nanoparticles made of a synthetic polymer (PLGA) to improve vaccines for farmed salmon. Suggested by Jennifer Kuzma and colleagues, an UOA may help identify and prioritise research needs, and it may support evaluations of the adequacy of relevant existing regulatory frameworks. In this work, the UOA (...) approach is modified and supported with elements from the uncertainty analysis framework developed by Warren Walker and colleagues. Empirically, we draw on relevant available published literature and insights generated in an ongoing nanoparticle salmon vaccine project, in which one of the authors participates. Nanotechnologies have not previously been encountered in the regulatory context of fish vaccines, which in part raises unique challenges due to prospective large scale vaccine use in semi-open aquatic systems. Strengthened through cooperation between ELSA and technology researchers we found the UOA useful for an early mapping of benefits and concerns, and for identifying areas in need of further research prior to a nanoparticle based salmon vaccine is developed and taken into use. We consider our approach to represent one among several complementing initiatives that seek to contribute to early stage evaluations of possible negative side effects, broadly conceived, in order to facilitate a more robust nanotechnology development. (shrink)