In an age where issues like climate change and the unintended consequences of technological innovation are high on the ethical and political agenda, questions about the nature and extent of our responsibilities to future generations have never been more important, yet simultaneously so difficult to answer. This book takes a unique approach to the problem by drawing on diverse traditions of thinking about care (including developmental psychology, phenomenology and feminist ethics) to explore the nature and meaning of our relationship with (...) the future. Demonstrating that many influential perspectives on intergenerational ethics, including positions advanced by John Rawls, Brian Barry, and Ulrich Beck are undermined by problems relating to uncertainty, it shows that an approach based on care ethics can confront the uncertain future successfully and give a viable account of the nature and scope of future-oriented responsibilities. (shrink)

How is it that thoroughly physical material beings such as ourselves can think, dream, feel, create and understand ideas, theories and concepts? How does mere matter give rise to all these non-material mental states, including consciousness itself? An answer to this central question of our existence is emerging at the busy intersection of neuroscience, psychology, artificial intelligence, and robotics.In this groundbreaking work, philosopher and cognitive scientist Andy Clark explores exciting new theories from these fields that reveal minds like ours to (...) be prediction machines - devices that have evolved to anticipate the incoming streams of sensory stimulation before they arrive. These predictions then initiate actions that structure our worlds and alter the very things we need to engage and predict. Clark takes us on a journey in discovering the circular causal flows and the self-structuring of the environment that define "the predictive brain." What emerges is a bold, new, cutting-edge vision that reveals the brain as our driving force in the daily surf through the waves of sensory stimulation. (shrink)

The new paradigm in the psychology of reasoning adopts a Bayesian, or prob- abilistic, model for studying human reasoning. Contrary to the traditional binary approach based on truth functional logic, with its binary values of truth and falsity, a third value that represents uncertainty can be introduced in the new paradigm. A variety of three-valued truth table systems are available in the formal literature, including one proposed by de Finetti. We examine the descriptive adequacy of these systems for natural language (...) indicative condi- tionals and bets on conditionals. Within our framework the so-called “defective” truth table, in which participants choose a third value when the antecedent of the indicative conditional is false, becomes a coherent response. We show that only de Finetti’s system has a good descriptive fit when uncer- tainty is the third value. (shrink)

In this essay, we explore an issue of moral uncertainty: what we are permitted to do when we are unsure about which moral principles are correct. We develop a novel approach to this issue that incorporates important insights from previous work on moral uncertainty, while avoiding some of the difficulties that beset existing alternative approaches. Our approach is based on evaluating and choosing between option sets rather than particular conduct options. We show how our approach is particularly well-suited to address (...) this issue of moral uncertainty with respect to agents that have credence in moral theories that are not fully consequentialist. (shrink)

In this paper, I enter the debate between those who hold that our normative uncertainty matters for what we ought to do, and those who hold that only our descriptive uncertainty matters. I argue that existing views in both camps have unacceptable implications in cases where our descriptive beliefs depend on our normative beliefs. I go on to propose a fix which is available only to those who hold that normative uncertainty matters, ultimately leaving the challenge as a threat to (...) recent skepticism about such views. (shrink)

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)

How should we make decisions when we're uncertain about what we ought, morally, to do? Decision-making in the face of fundamental moral uncertainty is underexplored terrain: MacAskill, Bykvist, and Ord argue that there are distinctive norms by which it is governed, and which depend on the nature of one's moral beliefs.

Defenders of deontological constraints in normative ethics face a challenge: how should an agent decide what to do when she is uncertain whether some course of action would violate a constraint? The most common response to this challenge has been to defend a threshold principle on which it is subjectively permissible to act iff the agent's credence that her action would be constraint-violating is below some threshold t. But the threshold approach seems arbitrary and unmotivated: what would possibly determine where (...) the threshold should be set, and why should there be any precise threshold at all? Threshold views also seem to violate ought agglomeration, since a pair of actions each of which is below the threshold for acceptable moral risk can, in combination, exceed that threshold. In this paper, I argue that stochastic dominance reasoning can vindicate and lend rigor to the threshold approach: given characteristically deontological assumptions about the moral value of acts, it turns out that morally safe options will stochastically dominate morally risky alternatives when and only when the likelihood that the risky option violates a moral constraint is greater than some precisely definable threshold (in the simplest case, .5). I also show how, in combination with the observation that deontological moral evaluation is relativized to particular choice situations, this approach can overcome the agglomeration problem. This allows the deontologist to give a precise and well-motivated response to the problem of uncertainty. (shrink)

We are sometimes unsure of the moral status of our relationships with other entities. Recent case studies in this uncertainty include our relationships with artificial agents (robots, assistant AI, etc.), animals, and patients with “locked-in” syndrome. Do these entities have basic moral standing? Could they count as true friends or lovers? What should we do when we do not know the answer to these questions? An influential line of reasoning suggests that, in such cases of moral uncertainty, we need meta-moral (...) decision rules that allow us to either minimize the risks of moral wrongdoing or improve the choice-worthiness of our actions. One particular argument adopted in this literature is the “risk asymmetry argument,” which claims that the risks associated with accepting or rejecting some moral facts may be sufficiently asymmetrical as to warrant favoring a particular practical resolution of this uncertainty. Focusing on the case study of artificial beings, this article argues that this is best understood as an ethical-epistemic challenge. The article argues that taking potential risk asymmetries seriously can help resolve disputes about the status of human–AI relationships, at least in practical terms (philosophical debates will, no doubt, continue); however, the resolution depends on a proper, empirically grounded assessment of the risks involved. Being skeptical about basic moral status, but more open to the possibility of meaningful relationships with such entities, may be the most sensible approach to take. (shrink)

This paper explores the role of moral uncertainty in explaining the morally disruptive character of new technologies. We argue that existing accounts of technomoral change do not fully explain its disruptiveness. This explanatory gap can be bridged by examining the epistemic dimensions of technomoral change, focusing on moral uncertainty and inquiry. To develop this account, we examine three historical cases: the introduction of the early pregnancy test, the contraception pill, and brain death. The resulting account highlights what we call “differential (...) disruption” and provides a resource for fields such as technology assessment, ethics of technology, and responsible innovation. (shrink)

In this paper we introduce the nascent literature on Moral Uncertainty Theory and explore its application to the criminal law. Moral Uncertainty Theory seeks to address the question of what we ought to do when we are uncertain about what to do because we are torn between rival moral theories. For instance, we may have some credence in one theory that tells us to do A but also in another that tells us to do B. We examine how we might (...) decide whether or not to criminalize some conduct when we are unsure as to whether or not the conduct is morally permitted, and whether or not it is permissible to criminalize the conduct. We also look at how we might make sentencing decisions under moral uncertainty. We argue that Moral Uncertainty Theory can be an illuminating way to address these questions, but find that doing so is a lot more complicated than applying Moral Uncertainty Theory to individual conduct. (shrink)

The article deals with some implications of radical uncertainty for participatory democracy, and more precisely for Participatory Technology Assessment. Two main forms of PTA are discussed. One is aimed at involving lay citizens and highlighting public opinion. The other is addressed to stakeholder groups and organisations, not only in terms of interest mediation but also of inclusion of their insight into a problem. Radical uncertainty makes 'intractable' many environmental and technological issues and brings into question traditional and new approaches to (...) policymaking. Its consequences are explored from the viewpoint of new science, deliberative democracy, and network governance. Radical uncertainty calls for a rethinking of the aims of public deliberation, and a reinterpretation of the divide between opinion- and position-oriented PTA. To look for a public opinion, understood as a shared principled view, can prove misleading, as can thinking of stakeholder participatory arrangements in the usual way. When facts and values overlap, and are deeply controversial, the only opportunity for mutual understanding may be to look for practical, 'local' answers, based on different positional insights. Moreover, radical uncertainty also affects interest determination and pursuit, and may enhance the opportunity of joint, inclusive, non-strategic issue definition and solution-devising. This vision of public deliberation is consistent with the idea of network governance. However, fragmentation can affect the effectiveness and legitimacy of participatory policies. Trying to handle fragmentation from the top, as many suggest, is unlikely to be successful. A more promising endeavour is to foster deliberative settings which, although positioned at the level of 'local' and often contingent networks and commonalities, are open to include 'Otherness' – other contexts, other problem definitions, other concerns. (shrink)

Jennifer Rose Carr’s (2020) article “Normative Uncertainty Without Theories” proposes a method to maximize expected value under normative uncertainty without Intertheoretic Value Comparison (hereafter IVC). Carr argues that this method avoids IVC because it avoids theories: the agent’s credence is distributed among normative hypotheses of a particular type, which don’t constitute theories. However, I argue that Carr’s method doesn’t avoid or help to solve what I consider as the justificatory problem of IVC, which isn’t specific to comparing theories as such. (...) This threatens the implementability of Carr’s method. Fortunately, I also show how Carr’s method can nevertheless be implemented. I identify a type of epistemic states where the justificatory problem of IVC is not a necessary obstacle to maximizing expected value. In such states, the uncertainty stems from indecisive normative intuitions, and the agent justifiably constructs each normative hypothesis on the basis of a consistent subset of her intuitions by reference to the same unit of value. This part of my argument complements not only Carr’s (2020) argument, but also some moderate defenses of IVC. The combination of Carr’s paper and mine helps to illuminate the conditions for maximizing expected value under normative uncertainty without unjustified value comparison. (shrink)

In this chapter I show how challenges to our ability to tame the uncertainty of a pandemic leaves us vulnerable to uncertainty phobia. This is because not all the uncertainty that matters can be tamed by our knowledge of the relevant probabilities, contrary to what many believe. We are vulnerable because unrelievable wild uncertainty is a hard burden to bear, especially so when we must act in the face of it. -/- The source of unrelievable wild uncertainty is that the (...) nature of probability distributions matters for whether knowledge of them tames uncertainty. It matters because a warrant for the taming is provided by two theorems, but this warrant applies only to some kinds of probability distribution. Essentially, this is because the theorems are about what happens at a mathematical limit but real life never reaches the limit. Consequently, the warrant depends on how quickly the random processes producing the uncertainty converge towards their limit. If they are governed by one class of probability distributions, they converge quickly enough to possess the warrant. If they are governed by another class of probability distributions, they converge towards their limit too slowly and so do not possess that warrant. The random processes of pandemics involve the slow kind . -/- Faced with such a burden, as we are in a pandemic, we are tempted to retreat into uncertainty phobia, leading to fixed definite opinions, precisely when the exercise of sound judgement to determine our responses requires our opinions to be hedged and mobile. Coping with a pandemic requires us to bear the burden of unrelievable wild uncertainty rather than give in to the temptation of uncertainty phobia. Pandemics require the virtue of epistemic forbearance. (shrink)

ABSTRACTIntellectual historians often make empirical claims, but can never know for certain if these claims are right. Uncertainty is thus inevitable for intellectual historians. But accepting uncertainty is not enough: we should also act on it, by trying to reduce and report it. We can reduce uncertainty by amassing valid data from different sources to weigh the strengths and weaknesses of competing explanations, rather than trying to “prove” an empirical claim by looking for evidence that fits it. Then we should (...) report our degree of certainty in our claims. When we answer empirical questions in intellectual history, we are not telling our readers what happened: we are telling them how strong we think our evidence is—a crucial shift of emphasis. For intellectual historians, then, uncertainty is subjective, as discussed by Keynes and Collingwood; the paper thus explores three differences between subjective and objective uncertainty. Having outlined the theoretical basis of uncertainty, the paper then offers examples from actual research: Noel Malcolm's work shows how to reduce and report uncertainty about composition, and David Wootton's work shows how to reduce and report uncertainty about beliefs. (shrink)

This book demonstrates that the state-contingent approach provides the best way to think about all problems in the economics of uncertainty, including problems...

This paper explores the role of moral uncertainty in explaining the morally disruptive character of new technologies. We argue that existing accounts of technomoral change do not fully explain its disruptiveness. This explanatory gap can be bridged by examining the epistemic dimensions of technomoral change, focusing on moral uncertainty and inquiry. To develop this account, we examine three historical cases: the introduction of the early pregnancy test, the contraception pill, and brain death. The resulting account highlights what we call “differential (...) disruption” and provides a resource for fields such as technology assessment, ethics of technology, and responsible innovation. (shrink)

We sometimes seem to face fundamental moral uncertainty, i.e., uncertainty about what is morally good or morally right that cannot be reduced to ordinary descriptive uncertainty. This phenomenon raises a puzzle for noncognitivism, according to which moral judgments are desire-like attitudes as opposed to belief-like attitudes. Can a state of moral uncertainty really be a noncognitive state? So far, noncognitivists have not been able to offer a completely satisfactory account. Here, we argue that noncognitivists should exploit the formal analogy between (...) moral uncertainty and moral multi-objective decision problems. Our ‘multi-objective story’ enables noncognitivists to save our moral uncertainty thought and talk by explaining how the underlying phenomenon could be noncognitive. (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)

We are often unsure about what we ought to do. This can be because we lack empirical knowledge, such as the extent to which future generations will be harmed by climate change. It can also be because we lack normative knowledge, such as the relative moral importance of the interests of present people and the interests of future people. However, though the question of how one ought to act under empirical uncertainty has been addressed extensively by both economists and philosophers---with (...) expected utility theory providing the standard formal framework---the question of how one ought to act under normative uncertainty is comparatively neglected. My thesis attempts to address this gap. -/- In my thesis I develop a view that I call metanormativism: that there are second-order norms that govern action that are relative to a decision-maker's uncertainty about first-order norms. -/- In the first part of the thesis, I defend one specific metanormative view: that under normative uncertainty decision-makers should maximise expected choice-worthiness, treating normative uncertainty analogously with empirical uncertainty. Drawing on the analogy between decision-making under normative uncertainty and social choice theory, I defend this view at length in response to the problem of merely ordinal theories and the problem of intertheoretic value comparisons. -/- In the second part of the thesis, I explore the implications of metanormativism for other philosophical issues. I argue that it has important consequences regarding the theory of rational action in the face of incomparable values, the causal/evidential debate in decision-theory, and our assessment of the value of moral philosophy. (shrink)

Moral dilemmas can arise from uncertainty, including uncertainty of the real values involved. One interesting example of this is that of experimentation on human embryos and foetuses, If these have a moral stauts similar to that of human persons then there will be server constraitns on what may be done to them. If embryous have a moral status similar to that of other small clusters of cells, then constraints will be motivated largely by consideration for the persons into whom the (...) embryos may develop. If the truth lies somewhere between these two extremes, the embryo having neither the full moral weight of persons, nor a completely negligible moral weight, then different kinds of constraints will be appropriate. On the face of it, in order to know what kinds of experiements, if any, we are morally justified in performing on embryos we have to know what the moral weight of the embryo is. But then an impasse threatens, for it seems implausible that we can settle with certainty the exact moral status of the human embryo. It is the purpose of this paper to show that moral uncertainty need not make rational moral justification impossible. I develop a framework which distinguishes between what is morally right/wrong, and what is morally justified/unjustified, and applies standard decision theoretic tools to the case of moral uncertainties. (This was the first published account of what has subsequently become known as Expected Moral Value Theory. An earlier version of the paper, "A decision theoretic argument against human embryo experimentation", was published in M. Fricke (ed.), Essays in honor of Bob Durrant. (University of Otago Press, 1986) 111-27.). (shrink)

Scientific knowledge is the most solid and robust kind of knowledge that humans have because of its inherent self-correcting character. Nevertheless, anti-evolutionists, climate denialists, and anti-vaxxers, among others, question some of the best-established scientific findings, making claims unsupported by empirical evidence. A common aspect of these claims is reference to the uncertainties of science concerning evolution, climate change, vaccination, and so on. This is inaccurate: whereas the broad picture is clear, there will always exist uncertainties about the details of the (...) respective phenomena. This book shows that uncertainty is an inherent feature of science that does not devalue it. In contrast, uncertainty advances science because it motivates further research. This is the first book on this topic that draws on philosophy of science to explain what uncertainty in science is and how it makes science advance. It contrasts evolution, climate change, and vaccination, where the uncertainties are exaggerated, and genetic testing and forensic science, where the uncertainties are usually overlooked. The goal is to discuss the scientific, psychological, and philosophical aspects of uncertainty in order to explain what it really is, what kinds of problems it actually poses, and why in the end it makes science advance. Contrary to public representations of scientific findings and conclusions that produce an intuitive but distorted view of science as certain, people need to understand and learn to live with uncertainty in science. This book is intended for anyone who wants to get a clear view of the nature of science. (shrink)

Some philosophers have recently argued that decision-makers ought to take normative uncertainty into account in their decisionmaking. These philosophers argue that, just as it is plausible that we should maximize expected value under empirical uncertainty, it is plausible that we should maximize expected choice-worthiness under normative uncertainty. However, such an approach faces two serious problems: how to deal with merely ordinal theories, which do not give sense to the idea of magnitudes of choice-worthiness; and how, even when theories do give (...) sense to magnitudes of choice-worthiness, to compare magnitudes of choice-worthiness across different theories. Some critics have suggested that these problems are fatal to the project of developing a normative account of decision-making under normative uncertainty. The primary purpose of this article is to show that this is not the case. To this end, I develop an analogy between decision-making under normative uncertainty and the problem of social choice, and then argue that the Borda Rule provides the best way of making decisions in the face of merely ordinal theories and intertheoretic incomparability. (shrink)

We are often uncertain how to behave morally in complex situations. In this controversial study, Ted Lockhart contends that moral philosophy has failed to address how we make such moral decisions. Adapting decision theory to the task of decision-making under moral uncertainly, he proposes that we should not always act how we feel we ought to act, and that sometimes we should act against what we feel to be morally right. Lockhart also discusses abortion extensively and proposes new ways to (...) deal with the ethical and moral issues which surround it. (shrink)

There is now considerable evidence that human sentence processing is expectation based: As people read a sentence, they use their statistical experience with their language to generate predictions about upcoming syntactic structure. This study examines how sentence processing is affected by readers' uncertainty about those expectations. In a self-paced reading study, we use lexical subcategorization distributions to factorially manipulate both the strength of expectations and the uncertainty about them. We compare two types of uncertainty: uncertainty about the verb's complement, reflecting (...) the next prediction step; and uncertainty about the full sentence, reflecting an unbounded number of prediction steps. We find that uncertainty about the full structure, but not about the next step, was a significant predictor of processing difficulty: Greater reduction in uncertainty was correlated with increased reading times. We additionally replicated previously observed effects of expectation violation, orthogonal to the effect of uncertainty. This suggests that both surprisal and uncertainty affect human RTs. We discuss the consequences for theories of sentence comprehension. (shrink)

Role of the entrepreneur in a distinct role of profit.

At a previous conference (CONTEXT’99), the author described the ATT-Meta context-based AI system for (a) reasoning uncertainly about agents’ beliefs and (b) performing some of the uncertain reasoning needed for the understanding of metaphorical language. ATT-Meta’s handling of uncertainty is qualitative, and includes provisions for adjudicating conflicts between different lines of reasoning. But most of the detail on conflict-handling given in the earlier paper concerned conflicts arising for the special requirements of (a). Furthermore, there have been major recent changes in (...) the conflict-handling approach. The present paper provides a detailed account of major parts of the current approach, stressing how it operates in metaphorical reasoning. In concentrating on uncertainty-handling, this paper does not seek to repeat the justifications given elsewhere for ATT-Meta’s approach to metaphor. (shrink)

What should we do when we are not certain about what we morally should do? There is a long history of theorizing about decision-making under empirical uncertainty, but surprisingly little has been written about the moral uncertainty expressed by this question. Only very recently have philosophers started to systematically address the nature of such uncertainty and its impacts on decision-making. This paper addresses the main problems raised by moral uncertainty and critically examines some proposed solutions.

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)

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

Model evaluation for long term climate predictions must be done on quantities other than the actual prediction, and a comprehensive uncertainty quantification is impossible. An ad hoc alternative is provided by coordinated model intercomparisons which typically use a “one model one vote” approach. The problem with such an approach is that it treats all models as independent and equally plausible. Reweighting all models of the ensemble for performance and dependence seems like an obvious way to improve on model democracy, yet (...) there are open questions on what constitutes a “good” model, how to define dependency, how to interpret robustness, and how to incorporate background knowledge. Under¬standing those issues has the potential to increase confidence in model predictions in modeling efforts outside of climate science where similar challenges exist. (shrink)

The main aim of this book is to introduce the topic of limited awareness, and changes in awareness, to those interested in the philosophy of decision-making and uncertain reasoning.

Replications are often taken to play both epistemic and demarcating roles in science: they provide evidence about the reliability of fields’ methods and, by extension, about which fields “count” as scientific. I argue that, in a field characterized by a high degree of theoretical openness and uncertainty, like comparative cognition, replications do not sit well in these roles. Like other experiments conducted under conditions of uncertainty, replications are often equivocal and open to interpretation. As a result, they are poorly placed (...) to deliver clear judgments about the reliability of comparative cognition’s methods or its scientific bona fides. I suggest that this should encourage us to take a broader view of both the nature of scientific progress and the role of replication in comparative cognition. (shrink)

We study uncertainty relations for a general class of canonically conjugate observables. It is known that such variables can be approached within a limiting procedure of the Pegg–Barnett type. We show that uncertainty relations for conjugate observables in terms of generalized entropies can be obtained on the base of genuine finite-dimensional consideration. Due to the Riesz theorem, there exists an inequality between norm-like functionals of two probability distributions in finite dimensions. Using a limiting procedure of the Pegg–Barnett type, we take (...) the infinite-dimensional limit right for this inequality. Hence, uncertainty relations are derived in terms of generalized entropies. In particular, the case of measurements with a finite precision is addressed. It takes into account that in any experiment an accuracy of performed measurements is always limited. (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 this article, I present a new interpretation of the pro-life view on the status of early human embryos. In my understanding, this position is based not on presumptions about the ontological status of embryos and their developmental capabilities but on the specific criteria of rational decisions under uncertainty and on a cautious response to the ambiguous status of embryos. This view, which uses the decision theory model of moral reasoning, promises to reconcile the uncertainty about the ontological status of (...) embryos with the certainty about normative obligations. I will demonstrate that my interpretation of the pro-life view, although seeming to be stronger than the standard one, has limited scope and cannot be used to limit destructive research on human embryos. (shrink)

While uncertainty can never be totally eliminated from clinical practice, physicians can at least come to terms with it. In interviews with Canadian physicians in a variety of clinical settings, three sources of uncertainty affecting the allocation of medical resources were identified. Technical uncertainty arises from inadequate scientific data. Personal uncertainty arises from not knowing patients' wishes. Conceptual uncertainty arises from the problem of applying abstract criteria to concrete situations.

Given the deep disagreement surrounding population axiology, one should remain uncertain about which theory is best. However, this uncertainty need not leave one neutral about which acts are better or worse. We show that as the number of lives at stake grows, the Expected Moral Value approach to axiological uncertainty systematically pushes one towards choosing the option preferred by the Total and Critical Level views, even if one’s credence in those theories is low.

This paper explores the intertwining of uncertainty and values. We consider an important but underexplored field of fundamental uncertainty and values in decision-making. Some proposed methodologies to deal with fundamental uncertainty have included potential surprise theory, scenario planning and hypothetical retrospection. We focus on the principle of uncertainty transduction in hypothetical retrospection as an illustrative case of how values interact with fundamental uncertainty. We show that while uncertainty transduction appears intuitive in decision contexts it nevertheless fails in important ranges of (...) strategic game-theoretic cases. The methodological reasons behind the failure are then examined. (shrink)

In this article we examine obsessive compulsive disorder (OCD). We examine and reject two existing models of this disorder: the Dysfunctional Belief Model and the Inference‐Based Approach. Instead, we propose that the main distinctive characteristic of OCD is a hyperactive sub‐personal signal of being in error, experienced by the individual as uncertainty about his or her intentional actions (including mental actions). This signalling interacts with the anxiety sensitivities of the individual to trigger conscious checking processes, including speculations about possible harms. (...) We examine the implications of this model for the individual's capacity to control his or her thoughts. (shrink)

The aim of this paper is to examine whether it would be advantageous to introduce knowledge norms instead of the currently assumed rational credence norms into the debate about decision making under normative uncertainty. There is reason to think that this could help us better accommodate cases in which agents are rationally highly confident in false moral views. I show how Moss’ view of probabilistic knowledge can be fruitfully employed to develop a decision theory that delivers plausible verdicts in these (...) cases. I also argue that, for this new view to be better than existing alternatives, it must adopt a particular solution to the new evil demon problem, which asks whether agents and their BIV-counterparts are equally justified. In order to get an attractive decision theory for cases of moral uncertainty, we must reject the claim that agents and their BIV-counterparts are equally justified. Moreover, the resulting view must be supplemented with a moral epistemology that explains how it is possible to be rationally morally uncertain. This is especially challenging if we assume that moral truths are knowable a priori. (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 plays an important role in The General Theory, particularly in the theory of interest rates. Keynes did not provide a theory of uncertainty, but he did make some enlightening remarks about the direction he thought such a theory should take. I argue that some modern innovations in the theory of probability allow us to build a theory which captures these Keynesian insights. If this is the right theory, however, uncertainty cannot carry its weight in Keynes’s arguments. This does not (...) mean that the conclusions of these arguments are necessarily mistaken; in their best formulation they may succeed with merely an appeal to risk. (shrink)

. Decision-making under uncertainty is sometimes investigated as a homogeneous problem, independently of the type of decision-maker and the level and nature of the decision itself. However, when the decision-maker is a public authority, there immediately arise problems additional to those that concern any other decision-maker. This is not always clearly recognised in orthodox discussions on decisions under conditions of uncertainty. This article investigates the methodological, strategic and procedural challenges of taking public decisions in such conditions. It focuses mainly on (...) decisions involving urban contexts, such as planning decisions regarding land use and building transformations, by trying to develop some pioneering research studies in this field. (shrink)

Model evaluation for long-term climate predictions must be done on quantities other than the actual prediction, and a comprehensive uncertainty quantificationUncertainty quantification is impossible. An ad hoc alternative is provided by coordinated model intercomparisonsModel intercomparisons which typically use a “one model one vote” approach. The problem with such an approach is that it treats all models as independent and equally plausible. Reweighting all models of the ensemble for performance and dependence seems like an obvious way to improve on model democracy, (...) yet there are open questions on what constitutes a “good” model, how to define dependency, how to interpret robustnessRobustness, and how to incorporate background knowledgeBackground knowledge. UnderstandingUnderstanding those issues have the potential to increase confidence in model predictions in modeling efforts outside of climate scienceClimate science where similar challenges exist. (shrink)

In this chapter we introduce the nascent literature on Moral Uncertainty Theory and explore its application to the criminal law. Moral Uncertainty Theory seeks to address the question of what we ought to do when we are uncertain about what to do because we are torn between rival moral theories. For instance, we may have some credence in one theory that tells us to do A but also in another that tells us to do B. We examine how we might (...) decide whether or not to criminalize some conduct when we are unsure as to whether or not the conduct is morally permitted and whether or not it is permissible to criminalize the conduct. We also look at how we might make sentencing decisions under moral uncertainty. We argue that Moral Uncertainty Theory can be an illuminating way to address these questions but find that doing so is a lot more complicated than applying Moral Uncertainty Theory to individual conduct. (shrink)