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)

Value and uncertainty are the critical components of decision and action. To think of the affective system as at the core of action is to draw attention to the role of affect in representing and combining these two dimensions, and orchestrating a wide range of mental capacities—attention, perception, memory, inference, motivation, and monitoring—in light of these evaluative representations. The commentators have helpfully enriched our appreciation of the various ways in which affect can contribute to the attunement, cuing, motivation, (...) control, and ongoing assessment of decision and action. (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)

How ought you to evaluate your options if you're uncertain about what's fundamentally valuable? A prominent response is Expected Value Maximisation (EVM)—the view that under axiological uncertainty, an option is better than another if and only if it has the greater expected value across axiologies. But the expected value of an option depends on quantitative probability and value facts, and in particular on value comparisons across axiologies. We need to explain what it is for (...) such facts to hold. Also, EVM is by no means self-evident. We need an argument to defend that it’s true. This book introduces an axiomatic approach to answer these worries. It provides an explication of what EVM means by use of representation theorems: intertheoretic comparisons can be understood in terms of facts about which options are better than which, and mutatis mutandis for intratheoretic comparisons and axiological probabilities. And it provides a systematic argument to the effect that EVM is true: the theory can be vindicated through simple axioms. The result is a formally cogent and philosophically compelling extension of standard decision theory, and original take on the problem of axiological or normative uncertainty. (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)

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)

In this paper I argue for a distinction between subjective and value laden aspects of judgements showing why equating the former with the latter has the potential to confuse matters when the goal is uncovering the influence of political influences on scientific practice. I will focus on three separate but interrelated issues. The first concerns the issue of ‘verification’ in computational modelling. This is a practice that involves a number of formal techniques but as I show, even these allegedly (...) objective methods ultimately rely on subjective estimation and evaluation of different types of parameters. This has implications for my second point which relates to uncertainty quantification—an assessment of the degree of uncertainty present in a particular modelling scenario. I argue that while this practice also involves subjective elements, in no way does that detract from its status as an epistemic exercise. Finally I discuss the relation between accuracy and uncertainty and how each relates to judgements that embody social/ethical/political concerns, in particular those associated with high consequence systems. (shrink)

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)

Expected value maximization gives plausible guidance for moral decision‐making under uncertainty in many situations. But it has unappetizing implications in ‘Pascalian’ situations involving tiny probabilities of extreme outcomes. This paper shows, first, that under realistic levels of ‘background uncertainty’ about sources of value independent of one's present choice, a widely accepted and apparently innocuous principle—stochastic dominance—requires that prospects be ranked by the expected value of their consequences in most ordinary choice situations. But second, this implication (...) does not hold when differences in expected value are driven by tiny probabilities of extreme outcomes. Stochastic dominance therefore lets us draw a surprisingly principled line between ‘ordinary’ and ‘Pascalian’ situations, providing a powerful justification for de facto expected value maximization in the former context while permitting deviations in the latter. Drawing this distinction is incompatible with an in‐principle commitment to maximizing expected value, but does not require too much departure from decision‐theoretic orthodoxy: it is compatible, for instance, with the view that moral agents must maximize the expectation of a utility function that is an increasing function of moral value. (shrink)

The present research attempts to understand the importance of altruistic and egoistic values in determining consumers’ motives and intention to purchase organic foods. Using the face-to-face survey approach, a total of 1,067 responses were collected from consumers in China. Data analysis was performed using a two-step structural equation modeling approach, i.e., measurement and structural models. The findings indicated that both values influence the intention to purchase organic foods through the mediation of motives. Specifically, the altruistic value influences the environmental (...) concern, and the egoistic value influences the health concern. Moreover, the perceived uncertainty negatively moderates a relationship between consumer HC and organic purchase intention while positively moderating a relationship between consumer EC and organic purchase intention. Several implications and suggestions are also discussed. (shrink)

Philosophers continue to debate both the actual and the ideal roles of values in science. Recently, Eric Winsberg has offered a novel, model-based challenge to those who argue that the internal workings of science can and should be kept free from the influence of social values. He contends that model-based assignments of probability to hypotheses about future climate change are unavoidably influenced by social values. I raise two objections to Winsberg’s argument, neither of which can wholly undermine its conclusion but (...) each of which suggests that his argument exaggerates the influence of social values on estimates of uncertainty in climate prediction. I then show how a more traditional challenge to the value-free ideal seems tailor-made for the climate context. (shrink)

Climate science evaluates hypotheses about the climate using computer simulations and complex models. The models that drive these simulations, moreover, represent the efforts of many different agents, and they arise from a compounding set of methodological choices whose effects are epistemically inscrutable. These facts, I argue in this chapter, make it extremely difficult for climate scientists to estimate the degrees of uncertainty associated with these hypotheses that are free from the influences of past preferences—preferences both with regard to importance (...) of one prediction over another and with regard to avoidance of false positive over false negatives and vice versa. This leaves an imprint of non-epistemic values in the nooks and crannies of climate science. (shrink)

Regulatory science, which generates knowledge relevant for regulatory decision?making, is different from standard academic science in that it is oriented mainly towards the attainment of non?epistemic (practical) aims. The role of uncertainty and the limits to the relevance of academic science are being recognized more and more explicitly in regulatory decision?making. This has led to the introduction of regulation?specific scientific methodologies in order to generate decision?relevant data. However, recent practical experience with such non?standard methodologies indicates that they, too, may (...) be subject to important limitations. We argue that the attainment of non?epistemic values and aims (like the protection of human health and the environment) requires not only control of the quality of the data and the methodologies, but also the selection of the level of regulation deemed adequate in each specific case (including a decision about which of the two, under?regulation or over?regulation, would be more acceptable). (shrink)

The topic of this thesis is axiological uncertainty – the question of how you should evaluate your options if you are uncertain about which axiology is true. As an answer, I defend Expected Value Maximisation (EVM), the view that one option is better than another if and only if it has the greater expected value across axiologies. More precisely, I explore the axiomatic foundations of this view. I employ results from state-dependent utility theory, extend them in various (...) ways and interpret them accordingly, and thus provide axiomatisations of EVM as a theory of axiological uncertainty. (shrink)

According to Richard Jeffrey’s value-free ideal, scientists should avoid making value judgments about inductive risks by offering explicit representations of scientific uncertainty to decision-makers, who can use these to make decisions according to their own values. Some philosophers have responded by arguing that higher-order inductive risks arise in the process of producing representations of uncertainty. This chapter explores this line of argument and its limits, arguing that the Jeffreyan value-free ideal is achievable in contexts where (...) methodological decisions introduce minimal higher-order uncertainty and where communications of uncertainty are unlikely to be manipulated or misunderstood by scientists or decision-makers. This chapter illustrates the limits of the Jeffreyan ideal with reference to climate science and argues that the context of climate science is not conducive to the Jeffreyan ideal, so the argument that climate modeling is value-laden due to higher-order inductive risks withstands recent criticisms. (shrink)

Like all human activities, scientific research is infused with values. Scientific discovery can, for example, be valued as an end in itself. The phrase ethical values is an umbrella term for much of what people care about aside from knowledge for its own sake. Ethical values encompass reasons for caring about the harms caused by climate impacts or the injustice of how those harms are distributed. The closer that research gets to informing real-world actions, the more the design of that (...) research can be examined from the perspective of ethical values. Which societal challenges does the research aim to inform? From whose perspective does a policy analysis view potential outcomes? In this chapter we use a series of examples to illustrate how researchers’ choices regarding the treatment of uncertainties can have important consequences from the perspective of ethical values. Our aims in this chapter are: to familiarize readers with the key concept of coupled ethical–epistemic choices; to build capacity for recognizing such choices within the treatment of uncertainties; to encourage engagement with ethical values as a part of climate change research; and to offer some guidance on how to start doing so. (shrink)

Psychological research on people’s understanding of natural language connectives has traditionally used truth table tasks, in which participants evaluate the truth or falsity of a compound sentence given the truth or falsity of its components in the framework of propositional logic. One perplexing result concerned the indicative conditional if A then C which was often evaluated as true when A and C are true, false when A is true and C is false but irrelevant“ (devoid of value) when A (...) is false (whatever the value of C). This was called the “psychological defective table of the conditional.” Here we show that far from being anomalous the “defective” table pattern reveals a coherent semantics for the basic connectives of natural language in a trivalent framework. This was done by establishing participants’ truth tables for negation, conjunction, disjunction, conditional, and biconditional, when they were presented with statements that could be certainly true, certainly false, or neither. We review systems of three-valued tables from logic, linguistics, foundations of quantum mechanics, philosophical logic, and artificial intelligence, to see whether one of these systems adequately describes people’s interpretations of natural language connectives. We find that de Finetti’s (1936/1995) three-valued system is the best approximation to participants’ truth tables. (shrink)

ABSTRACTThis paper examines how decisions to limit treatment to critically ill patients under uncertainty can be made rationally. Expected utility theory offers one way of making rational decisions under uncertainty. One problem with using this approach is that we may not know the value of each option. One rational course open is to treat until further information becomes available. However, treatment can limit the range of options open. With treatment, a patient may recover such that he no (...) longer requires life‐supporting treatment. However, his life may be not worth living. If active euthanasia of %on‐terminal’conditions is prohibited, the option of dying will no longer be available. Taking a rational‘wait and see’course may result in being trapped within an unbearable life. On the other hand, sometimes present practice‘lets nature takes its course'. Critically ill patients are allowed to die because it is believed that their lives will be not worth living. It is likely that some patients are allowed to die when there is some objective chance of worthwhile future life. This paper argues that a policy of treating critically ill patients until the nature of future options can be better evaluated, in company with an offer of subsequent euthanasia where appropriate, allows a more rational and humane approach to treatment limitation decisions under uncertainty. (shrink)

Using climate policy debates as a case study, I argue that a certain response to the argument from inductive risk, the hedging defense, runs afoul of a reasonable ethical principle: the no-passing-...

A probabilistic explication is offered of equipoise and uncertainty in clinical trials. In order to be useful in the justification of clinical trials, equipoise has to be interpreted in terms of overlapping probability distributions of possible treatment outcomes, rather than point estimates representing expectation values. Uncertainty about treatment outcomes is shown to be a necessary but insufficient condition for the ethical defensibility of clinical trials. Additional requirements are proposed for the nature of that uncertainty. The indecisiveness of (...) our criteria for cautious decision-making under uncertainty creates the leeway that makes clinical trials defensible. (shrink)

I argue that the overly simplistic scenarios discussed by Pothos & Busemeyer (P&B) establish at best that quantum probability theory (QPT) is a logical possibility allowing distinct predictions from classical probability theory (CPT). The article fails, however, to provide convincing evidence for the proposal that QPT offers unique insights regarding cognition and the nature of human rationality.

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)

People can be uncertain in their moral judgments. Philosophers have argued that such uncertainty can either refer to the underlying empirical facts (empirical uncertainty) or to the normative evaluation of these facts itself (normative uncertainty). Psychological investigations of this distinction, however, are rare. In this paper, we combined factor-analytical and experimental approaches to show that empirical and normative uncertainty describe two related but different psychological states. In Study 1, we asked N = 265 participants to describe (...) a case of moral uncertainty and to rate different aspects of their uncertainty about this case. Across this wide range of moral scenarios, our items loaded onto three reliable factors: lack of information, unclear consequences, and normative uncertainty. In Study 2, we confirmed this factor structure using predefined stimulus material. N = 402 participants each rated eight scenarios that systematically varied in their degree of uncertainty regarding the consequences of the described actions and in the value conflict that was inherent to them. The empirical uncertainty factors were mainly affected by the introduction of uncertainty regarding consequences, and the normative uncertainty factor was mainly affected by the introduction of value conflict. Our studies provide evidence that the distinction between empirical and normative uncertainty accurately describes a psychological reality. We discuss the relevance of our findings for research on moral judgments and decision-making, and folk metaethics. (shrink)

In the following, I will discuss the current social reaction to the ecological crisis and the ways in which society reacts to technological risks, which can be understood primarily as a reaction to scientific and moral or ethical uncertainty. In the first section, I will clarify what is meant by scientific and moral or ethical uncertainty. In the second section, I will contrast Max Weber's differentiation of science, law [Recht) and morality in the modern world with the process (...) of de-differentiation of these value spheres, a trend which can be observed in the present-day context of the ecological crisis and technological risks. We shall see that social contradictions emerge in the functional relationships between these value spheres, and that such contradictions go hand in hand with these value spheres or contexts of discourse either losing their original function or becoming transformed. Science forfeits its role as a functional authority and becomes a strategic resource for politics. Law becomes a basic constituent of an amoral form of negotiation, which can no longer be properly grasped in terms of legal categories. Morality is transformed into fear, and economics yields unprofitable practices. In the third section, I will in attempt to open up the moral and ethical dimension of how to deal with uncertainty with the help of discourse theory, as well as outline a possible solution. (shrink)

Value analysis establishes a way to practice functional analysis which enables to think all matter as sets of functions. The study of the correlations between the phases of activation of these functions leads to consider the aggregation of correlated activation functions as an attractor in a configuration space. This point of view allows figuring out general behaviors reducing the conceptual gap between microeconomics and macroeconomics. Then, based on a characterization of complex adaptive systems in terms of functional attractors, the (...) theory links together value and physical magnitudes, like work or energy and action. The evolution of these systems is studied from the viewpoints of learning or of voluntary and involuntary interactions with others described in the ultimate way by the strategies, or operators, of which they make use. Three kinds of uncertainties are emphasized among which the uncertainty between the structure and the business outlook of a system is recreated through an analogy between physics and economics. The rationality of the complex functional systems economics is based on value and on market or environment awareness. Equilibria establish potential of agents or players whose profiles are built through the equivalence between a time-dependent payoff at equilibrium and the regular value of the corresponding attractor. The law of supply and demand is naturally founded on unbiased profiles of agents and can be a means of uncertainty reduction and of growth. Freedoms are opportunities to grow, when they result in confidence, and to bear risks in decision-making through an innovative process. (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)

This thesis is about making decisions when we are uncertain about what will happen, how valuable it will be, and even how to make decisions. Even the most sure-footed amongst us are sometimes uncertain about all three, but surprisingly little attention has been given to the latter two. The three essays that constitute my thesis hope to do a small part in rectifying this problem. The first essay is about the value of finding out how to make decisions. Society (...) spends considerable resources funding people (like me) to research decision-making, so it is natural to wonder whether society is getting a good deal. This question is so shockingly underresearched that bedrock facts are readily discoverable, such as when this kind of information is valuable. My second essay concerns whether we can compare value when we are uncertain about value. Many people are in fact uncertain about value, and how we deal with this uncertainty hinges on these comparisons. I argue that value comparisons are only sometimes possible; I call this weak comparability. This essay is largely a synthesis of the literature, but I also present an argument which begins with a peculiar view of the self: it is as if each of us is a crowd of different people separated by time (but connected by continuity of experience). I’m not the first to endorse this peculiar view of the self, but I am the first to show how it supports the benign view that value is sometimes comparable. We may be uncertain of any decision rules, even those that would tell us how to act when we face uncertainty in decision rules. We may be uncertain of how to decide how to decide how to... And so on. If so, we might have to accept infinitely many decision rules just to make any mundane decision, such as whether to pick up a five-cent piece from the gutter. My third essay addresses this problem of regress. I think all of our decisions are forced: we must decide now or continue to deliberate. Surprisingly, this allows us to avoid the original problem. I call this solution “when forced, do your best”. (shrink)

This study investigates how uncertainty works in science policy debates by considering an unusual case: one in which uncertainty-based arguments for delay come from the scientific community, rather than industry actors. The case I present is the central use of value-added modeling in the evaluation of individual teachers, a controversial trend in education reform. In order to understand how policy actors might counter inconvenient statements of uncertainty from experts, I analyze speeches from Education Secretary Arne Duncan, (...) a committed and influential advocate of VAM. I identify a three-part rhetorical tactic, the “Overcaution Allegation,” and describe its persuasive potential to legitimize policies that elicit caution from the scientific community because they are built on uncertain science. (shrink)

We consider future cash flows that are contingent both on dates in time and on uncertain states. The decision maker (DM) values the cash flows according to its decision criterion: Here, the payoffs’ expectation with respect to a capacity measure. The subjective measure grasps the DM’s behaviour in front of the future, in the spirit of de Finetti’s (1930) and of Yaari’s (1987) Dual Theory in the case of risk. Decomposition of the criterion into two criteria that represent the DM’s (...) preferences on uncertain payoffs and time contingent payoffs are derived from Ghirardato’s (1997) results. Conditional Choquet integrals are defined by dynamic consistency (DC) requirements and conditional capacities are derived, under some conditions on information. In contrast with other models referring to DC, ours does not collapse into a linear one because it violates a weak version of consequentialism. (shrink)

This deliberately wide-ranging book addresses issues related to trust, compassion, well-being, grace, dignity and integrity. It explores these within the context of higher education, giving existential and empirical accounts of how these moral duties can be expressed within the academy and why they ought to be. The chapters range from values used in the marketing and management of institutions to their realisation in therapeutic and teacher training spaces. The book opens with a specific introduction which positions the work and outlines (...) the context of duties and obligations at play. This is followed by two distinct but related sections including chapters on theoretical issues, organisational practices and personal praxis. The first part is more abstract and theoretical, the second locates the values discussed within the practices of the university. In doing so the book encompasses a wide range of issues from multi-disciplinary and geo-political regions. The authors are a mixture of world-leading authorities on values in higher education and earlier career researchers, who are nonetheless equally passionate contributors. This mix gives the book vibrancy and offers insight which appeals to both an academic and managerial readership. (shrink)

An approach to the treatment of inference in the presence of uncertain truth values is described, based on representing uncertainties by sets of ordinary (certain) truth values. Both the algebraic and the logical aspects are studied for a variety of lattices used as truth value spaces in the domain of many-valued logic.

Economic forecasting is famously unreliable. While this problem has traditionally been blamed on theories such as the efficient market hypothesis or even the butterfly effect, an alternative explanation is the role of money – something which is typically downplayed or excluded altogether from economic models. Instead, models tend to treat the economy as a kind of barter system in which money's only role is as an inert medium of exchange. Prices are assumed to almost perfectly reflect the 'intrinsic value' (...) of an asset. This paper argues, however, that money is better seen as an inherently dualistic phenomenon, which merges precise number with the fuzzy concept of value. Prices are not the optimal result of a mechanical, Newtonian process, but are an emergent property of the money system. And just as quantum physics has its uncertainty principle, so the economy is an uncertain process which can only be approximated by mathematical models. Acknowledging the dynamic and paradoxical qualities of money changes our ontological framework for economic modelling, and for making decisions under uncertainty. Applications to areas of risk analysis, forecasting and modelling are discussed, and it is proposed that a greater appreciation of the fundamental causes of uncertainty will help to make the economy a less uncertain place. (shrink)

In this article, I discuss the implications of generative AI in future of creative work in the music industries through an ethnographic study of music technologists in Melbourne, Australia. Drawing on visual ethnography methods, I explore how researchers, developers, as well as professional and aspiring artists, across sectors in Melbourne’s ecosystem, value the role of mistakes, glitches and uncertainty in the creative process with music technology. This stands in opposition to the controlled processes within generative AI models, based (...) on the management of uncertainty as an input value. Thus, I reframe the concept of creative uncertainty which emerges as a shaping force in the creative process, and in opposition to the controlled outputs of generative AI. Furthermore, this article shows the limitations and misalignment of dominant visions about the impact of generative AI, on creative workflows and practices, by highlighting the experiences, motivations and expectations of the research participants in this multi-sited ethnography. (shrink)

In this paper, we argue that the characteristics of digital platforms challenge the fundamental assumptions of value sensitive design (VSD). Traditionally, VSD methods assume that we can identify relevant values during the design phase of new technologies. The underlying assumption is that there is onlyepistemic uncertaintyabout which values will be impacted by a technology. VSD methods suggest that one can predict which values will be affected by new technologies by increasing knowledge about how values are interpreted or understood in (...) context. In contrast, digital platforms exhibit a novel form of uncertainty, namely,ontological uncertainty: even with full information and overview, it cannot be foreseen what users or developers will do with digital platforms. Hence, predictions about which values are affected might not hold. In this paper, we suggest expanding VSD methods to account for value dynamism resulting from ontological uncertainty. Our expansions involve (1) extending VSD to the entire lifecycle of a platform, (2) broadening VSD through the addition of reflexivity, i.e. second-order learning about what values to aim at, and (3) adding specific tools of moral sandboxing and moral prototyping to enhance such reflexivity. While we illustrate our approach with a short case study about ride-sharing platforms such as Uber, our approach is relevant for other technologies exhibiting ontological uncertainty as well, such as machine learning, robotics and artificial intelligence. (shrink)

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)

In this paper, dynamic behavior analysis has been discussed for a class of switched complex-valued neural networks with interval parameter uncertainties and impulse disturbance. Sufficient conditions for guaranteeing the existence, uniqueness, and global robust exponential stability of the equilibrium point have been obtained by using the homomorphism mapping theorem, the scalar Lyapunov function method, the average dwell time method, and M-matrix theory. Since there is no result concerning the stability problem of switched neural networks defined in complex number domain, the (...) stability results we describe in this paper generalize the existing ones. The effectiveness of the proposed results is illustrated by a numerical example. (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)

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)

Disorders of Consciousness (DoCs) raise difficult and complex questions about the value of life for persons with impaired consciousness, the rights of persons unable to make medical decisions, and our social, medical, and ethical obligations to patients whose personhood has frequently been challenged and neglected. Recent neuroscientific discoveries have led to enhanced understanding of the heterogeneity of these disorders, and focused renewed attention on the medical and ethical problem of misdiagnosis. -/- This book examines the entanglement of epistemic and (...) ethical uncertainty in DoCs and other medical contexts, and how they interact to create both epistemic and ethical risks. Philosopher and bioethicist L. Syd M Johnson pulls together multiple threads in this work: the ontological mysteries of consciousness, medical uncertainty about unconsciousness, ableist bias, withdrawal of treatment in neurointensive care, and the rarely questioned view that consciousness is essential to personhood and moral status. Johnson challenges longstanding bioethical dogmas about DoC patients, and argues for an ethics of uncertainty for contexts where there is a need for decisive action in the presence of unavoidable uncertainty. The ethics of uncertainty refocuses ethical inquiry concerning persons with DoCs, placing less emphasis on their contested personhood, and more on inductive risk and uncertainty, on respect for autonomy, and especially on epistemic justice. With applications to various decisional contexts where uncertainty and ethical risk interact, this ethical approach enables surrogate decision makers facing fraught and risky choices to fulfill their obligations as moral and epistemic agents. (shrink)

While ordinary decision theory focuses on empirical uncertainty, real decision-makers also face normative uncertainty: uncertainty about value itself. From a purely formal perspective, normative uncertainty is comparable to (Harsanyian or Rawlsian) identity uncertainty in the 'original position', where one's future values are unknown. A comprehensive decision theory must address twofold uncertainty -- normative and empirical. We present a simple model of twofold uncertainty, and show that the most popular decision principle -- maximising (...) expected value (`Expectationalism') -- has different formulations, namely Ex-Ante Expectationalism, Ex-Post Expectationalism, and hybrid theories. These alternative theories recommend different decisions, reasoning modes, and attitudes to risk. But they converge under an interesting (necessary and sufficient) condition. (shrink)

This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant (...) value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)