A theoretical structure for multiattribute decision making is presented, based on a dynamical system for interactions in a neural network incorporating affective and rational variables. This enables modeling of problems that elude two prevailing economic decision theories: subjective expected utility theory and prospect theory. The network is unlike some that fit economic data by choosing optimal weights or coefficients within a predetermined mathematical framework. Rather, the framework itself is based on principles used elsewhere to model many other cognitive and behavioral (...) data, in a manner approximating how humans perform behavioral functions. Different, interconnected modules within the network encode (a) attributes of objects among which choices are made, (b) object categories, (c) and goals of the decision maker. An example is utilized to simulate the actual consumer choice between old and new versions of Coca-Cola. Potential applications are also discussed to market decisions involving negotiations between participants, such as international petroleum traders. (shrink)

Novel technological devices, applications, and algorithms can provide us with a vast amount of personal information about ourselves. Given that we have ethical and practical reasons to pursue self-knowledge, should we use technology to increase our self-knowledge? And which ethical issues arise from the pursuit of technologically sourced self-knowledge? In this paper, I explore these questions in relation to bioinformation technologies (health and activity trackers, DTC genetic testing, and DTC neurotechnologies) and algorithmic profiling used for recommender systems, targeted advertising, and (...) technologically supported decision-making. First, I distinguish between impersonal, critical, and relational self-knowledge. Relational self-knowledge is a so far neglected dimension of self-knowledge which is introduced in this paper. Next, I investigate the contribution of these technologies to the three types of self-knowledge and uncover the connected ethical concerns. Technology can provide a lot of impersonal self-knowledge, but we should focus on the quality of the information which tends to be particularly insufficient for marginalized groups. In terms of critical self-knowledge, the nature of technologically sourced personal information typically impedes critical engagement. The value of relational self-knowledge speaks in favour of transparency of information technology, notably for algorithms that are involved in decision-making about individuals. Moreover, bioinformation technologies and digital profiling shape the concepts and norms that define us. We should ensure they not only serve commercial interests but our identity and self-knowledge interests. (shrink)

A diagnostic judgment of a teacher can be seen as an inference from manifest observable evidence on a student’s behavior to his or her latent traits. This can be described by a Bayesian model of in-ference: The teacher starts from a set of assumptions on the student (hypotheses), with subjective probabilities for each hypothesis (priors). Subsequently, he or she uses observed evidence (stu-dents’ responses to tasks) and knowledge on conditional probabilities of this evidence (likelihoods) to revise these assumptions. Many systematic (...) deviations from this model (biases, e.g. base-rate neglect, inverse fallacy) are reported in literature on Bayesian reasoning. In a teacher’s situation the information (hypotheses, priors, likelihoods) is usually not explicitly represented numerically (as in most research on Bayesian reasoning), but only by qualitative esti-mations in the mind of the teacher. In our study, we ask to which extent individuals (approximately) apply a rational Bayesian strategy or resort on other biased strategies of processing information for their diagnostic judgments. We explicitly pose this question with respect to non-numerical settings. To investigate this question, we developed a scenario that visually displays all relevant information (hypotheses, priors, likelihoods) in a graphically displayed hypothesis space (called “hypothegon”) – without recurring to numerical representations or mathematical procedures. 42 pre-service teach-ers were asked to judge the plausibility of different misconceptions of six students based on their responses to decimal comparison tasks (e.g. 3.39 > 3.4). Applying a Bayesian classification proce-dure, we identified three updating strategies: A Bayesian update strategy (BUS, processing all probabilities), a combined evidence strategy (CES, ignoring the prior probabilities but including all likelihoods), and a single evidence strategy (SES, only using the likelihood of the most probable hypothesis). In study 1, an instruction on the relevance of using all probabilities (priors and likelihoods) only weakly increased the processing of more information. In study 2, we found strong evidence that a visual explication of the prior-likelihood interaction led to an increase of processing the interaction of all relevant information. These results show that the phenomena found in general research on Bayesian reasoning in numerical settings extend to diagnostic judgments in non-numerical settings. (shrink)

In this article we argue that a widespread adoption of nudging can alter legal and political institutions. Debates on nudges thus far have largely revolved around a set of philosophical theories that we call individualistic approaches. Our analysis concerns the ways in which adherents of nudging make use of the newest findings in the behavioral sciences for the purposes of policy-making. We emphasize the fact that most nudges proposed so far are not a part of the legal system and are (...) also non-normative. We propose two ideal types: “law-as-normative” and “law-as-instrumental”, that allow us to understand and evaluate the relation of nudges and the law. We stress the importance of law as a safeguard for the possible negative consequences of nudges and conclude with proposals that could complement nudging policies. (shrink)

The combination of increased availability of large amounts of fine-grained human behavioral data and advances in machine learning is presiding over a growing reliance on algorithms to address complex societal problems. Algorithmic decision-making processes might lead to more objective and thus potentially fairer decisions than those made by humans who may be influenced by greed, prejudice, fatigue, or hunger. However, algorithmic decision-making has been criticized for its potential to enhance discrimination, information and power asymmetry, and opacity. In this paper, we (...) provide an overview of available technical solutions to enhance fairness, accountability, and transparency in algorithmic decision-making. We also highlight the criticality and urgency to engage multi-disciplinary teams of researchers, practitioners, policy-makers, and citizens to co-develop, deploy, and evaluate in the real-world algorithmic decision-making processes designed to maximize fairness and transparency. In doing so, we describe the Open Algortihms project as a step towards realizing the vision of a world where data and algorithms are used as lenses and levers in support of democracy and development. (shrink)

A search for the terms ‘acceptability judgment tasks’ & ‘language’ and ‘grammaticality judgment tasks’ & ‘language’ produces results which report findings that are based on the exact same elicitation technique. Although certain scholars have argued that acceptability and grammaticality are two separable notions that refer to different concepts, there are contexts in which the two terms are used interchangeably. The present work shows that these two notions and their scales do not coincide: there are sentences that are acceptable, even though (...) they are ungrammatical, and sentences that are unacceptable, despite being grammatical. First we adduce a number of examples for both cases, including grammatical illusions, violations of Identity Avoidance, and sentences that involve a level of processing complexity that overloads the cognitive parser and tricks it into (un)acceptability. We then discuss whether the acceptability of grammatically ill-formed sentences entails that we actually assign a meaning to them. Last, it is shown that there are n ways of unacceptability, and two ways of ungrammaticality, in the absolute and the relative sense. Since the use of the terms ‘acceptable’ and ‘grammatical’ is often found in experiments that constitute the core of the evidential base of linguistics, disentangling their various uses is likely to aid the field reach a better level of terminological clarity. (shrink)

In his early experimental work with Suppes, Davidson adopted rationality assumptions, not as necessary constraints on interpretation, but as practical conceits in addressing methodological problems faced by experimenters studying decision making under uncertainty. Although the content of their theory has since been undermined, their methodological approach—a Galilean form of methodological rationalism—lives on in contemporary psychological research. This article draws on Max Weber’s verstehen to articulate an account of Galilean methodological rationalism; explains how anomalies faced by Davidson’s early experimental work gave (...) rise to his later, canonical claims about rationality and interpretation; and reclaims this Galilean framework for use in contemporary psychological research. (shrink)

I defend the thesis that legal standards of proof are reducible to thresholds of probability. Many have rejected this thesis because it seems to entail that defendants can be found liable solely on the basis of statistical evidence. I argue that this inference is invalid. I do so by developing a view, called Legal Causalism, that combines Thomson's (1986) causal analysis of evidence with recent work in formal theories of causal inference. On this view, legal standards of proof can be (...) reduced to probabilities, but deriving these probabilities involves more than just statistics. (shrink)

Experimental work has revealed causal links between physical cleansing and various psychological variables. Empirically, how robust are they? Theoretically, how do they operate? Major prevailing accounts focus on morality or disgust, capturing a subset of cleansing effects, but cannot easily handle cleansing effects in non-moral, non-disgusting contexts. Building on grounded views on cognitive processes and known properties of mental procedures, we proposegrounded proceduresof separation as a proximate mechanism underlying cleansing effects. This account differs from prevailing accounts in terms of explanatory (...) kind, interpretive parsimony, and predictive scope. Its unique and falsifiable predictions have received empirical support: Cleansing attenuates or eliminates otherwise observed influences of prior events (1) across domains and (2) across valences. (3) Cleansing manipulations produce stronger effects the more strongly they engage sensorimotor capacities. (4) Reversing the causal arrow, motivation for cleansing is triggered more readily by negative than positive entities. (5) Conceptually similar effects extend to other physical actions of separation. On the flipside, grounded procedures ofconnectionare also observed. Together, separation and connection organize prior findings relevant to multiple perspectives (e.g., conceptual metaphor, sympathetic magic) and open up new questions. Their predictions are more generalizable than the specific mappings in conceptual metaphors, but more fine-grained than the broad assumptions of grounded cognition. This intermediate level of analysis sheds light on the interplay between mental and physical processes. (shrink)

We compare the predictions of two important proposals made by De Neys to findings in the anchoring effect literature. Evidence for an anchoring-and-adjustment heuristic supports his proposal that system 1 and system 2 are non-exclusive. The relationship between psychophysical noise and anchoring effects, however, challenges his proposal that epistemic uncertainty determines the involvement of system 2 corrective processes in judgment.

As scientific and engineering efforts become increasingly global in nature, the need to understand differences in perceptions of research ethics issues across countries and cultures is imperative. However, investigations into the connection between nationality and ethical decision-making in the sciences have largely generated mixed results. In Study 1 of this paper, a measure of biases and compensatory strategies that could influence ethical decisions was administered. Results from this study indicated that graduate students from the United States and international graduate students (...) studying in the US are prone to different biases. Based on these findings, recommendations are made for developing ethics education interventions to target these decision-making biases. In Study 2, we employed an ethics training intervention based on ethical sensemaking and used a well-established measure of ethical decision-making that more fully captures the content of ethical judgment. Similar to Study 1, the results obtained in this study suggest differences do exist between graduate students from the US and international graduate students in ethical decision-making prior to taking the research ethics training. However, similar effects were observed for both groups following the completion of the ethics training intervention. (shrink)

is normative in the sense that it aims to make recommendations for improving human judgment; it aims to have a practical impact on morally and politically significant human decisions and actions; and it studies normative, rational judgment qua rational judgment. These nonstandard ways of understanding ACP as normative collectively suggest a new interpretation of the strong replacement thesis that does not call for replacing normative epistemic concepts, relations, and inquiries with descriptive, causal ones. Rather, it calls for recognizing that the (...) aims and normative inquiries of epistemology and normative psychology have become intermutual in nature. Key Words: Heuristics and biases • applied cognitive psychology • normative psychology • rationality • naturalized epistemology • Epistemics • Applied Naturalized Epistemology • strong replacement • strategic reliabilism • ameliorative psychology. (shrink)

Le présent texte a pour objet de discuter les prétentions de l’économie comportementale, notamment la nature des résultats qu’elle revendique. Cette nouvelle branche du savoir s’affiche souvent comme un nouveau paradigme, mais il est aisé de montrer qu’elle ne peut rompre entièrement avec les ambitions interprétatives qui sont traditionnellement celles des sciences sociales. En conséquence, il est faux de penser que l’expérimentation est destinée à remplacer la compréhension, et une mise en perspective historique nous aidera à voir pourquoi.

We propose a vision of the structure of knowledge and processes of learning based upon the particularity of experience. Highly specific cognitive structures are constructed through activities in limited domains of experience. For new domains, new cognitive structures develop from and can call upon the knowledge of prior structures. Applying this vision of disparate cognitive structures to a detailed case study, we present an interpretation of addition‐related matter from the corpus and trace the interplay of specific experiences with the interactions (...) of ascribed, disparate structures. The interpretive focus is on learning processes through which a broadly applicable skill emerges from the interaction and integration of knowledge based on specific, particular experiences. (shrink)

Intractability and optimality are two sides of one coin: Optimal models are often intractable, that is, they tend to be excessively complex, or NP-hard. We explain the meaning of NP-hardness in detail and discuss how modem computer science circumvents intractability by introducing heuristics and shortcuts to optimality, often replacing optimality by means of sufficient sub-optimality. Since the principles of decision theory dictate balancing the cost of computation against gain in accuracy, statistical inference is currently being reshaped by a vigorous new (...) trend: the science of simplicity. Simple models, as we show for specific cases, are not just tractable, they also tend to be robust. Robustness is the ability of a model to extract relevant information from data, disregarding noise.Recently, Gigerenzer, Todd and the ABC Research Group (1999) have put forward a collection of fast and frugal heuristics as simple, boundedly rational inference strategies used by the unaided mind in real world inference problems. This collection of heuristics has suggestively been called the adaptive toolbox. In this paper we will focus on a comparison task in order to illustrate the simplicity and robustness of some of the heuristics in the adaptive toolbox in contrast to the intractability and the fragility of optimal solutions. We will concentrate on three important classes of models for comparison-based inference and, in each of these classes, search for that to be used as benchmarks to evaluate the performance of fast and frugal heuristics: lexicographic trees, linear modes and Bayesian networks. Lexicographic trees are interesting because they are particularly simple models that have been used by humans throughout the centuries. Linear models have been traditionally used by cognitive psychologists as models for human inference, while Bayesian networks have only recently been introduced in statistics and computer science. Yet it is the Bayesian networks that are the best possible benchmarks for evaluating the fast and frugal heuristics, as we will show in this paper. (shrink)

The basic Bayesian model of credence states, where each individual’s belief state is represented by a single probability measure, has been criticized as psychologically implausible, unable to represent the intuitive distinction between precise and imprecise probabilities, and normatively unjustifiable due to a need to adopt arbitrary, unmotivated priors. These arguments are often used to motivate a model on which imprecise credal states are represented by sets of probability measures. I connect this debate with recent work in Bayesian cognitive science, where (...) probabilistic models are typically provided with explicit hierarchical structure. Hierarchical Bayesian models are immune to many classic arguments against single-measure models. They represent grades of imprecision in probability assignments automatically, have strong psychological motivation, and can be normatively justified even when certain arbitrary decisions are required. In addition, hierarchical models show much more plausible learning behavior than flat representations in terms of sets of measures, which—on standard assumptions about update—rule out simple cases of learning from a starting point of total ignorance. (shrink)

In “The Pecking Order,” Dalton Conley argues that inequalities between siblings are larger than inequalities at the level of the overall society. Our article discusses the normative implications for institutions of this observation. We show that the question of state intervention for curbing intra-family inequality reveals an internal tension within liberalism between autonomy and toleration, which bears on the forms that the intervention of institutions may take. Despite the pros and cons of both commitments, autonomy-based liberalism appears more compatible with (...) the involvement of the state for egalitarian reasons within the family than toleration-based liberalism.Export citation Request permission. (shrink)

Insurance is pervasive in many social settings. As a cooperative device based on risk pooling, it serves to attenuate the adverse consequences of various risks by offering policyholders coverage against the losses implied by adverse events in exchange for the payment of premiums. In the insurance industry, the concept of actuarial fairness serves to establish what could be adequate, fair premiums. Accordingly, premiums paid by policyholders should match as closely as possible their risk exposure. Such premiums are the product of (...) the probabilities of losses and the expected losses. This article presents a discussion of the fairness of actuarial fairness through three steps: defining the concept based on its formulation within the insurance industry; determining in which sense it may be about fairness; and raising some objections to the actual fairness of actuarial fairness. The necessity of a normative evaluation of actuarial fairness is justified by the influence of the concept on the current reforms of public insurance systems and the fact that it highlights the question of the repartition of the gains and burdens of social cooperation. (shrink)

Notre travail se donne pour objectif de montrer que le point de rupture entre l’économie néoclassique et l’économie comportementale réside dans la manière dont chacune définit la rationalité. Cette dernière était parfaitement unifiée par la maximisation. Mais Simon pose les fondements de l’économie comportementale en critiquant précisément le concept néoclassique de rationalité et en suggérant que l’agent suit des modes de raisonnement alternatifs. Bien que Kahneman et Tversky proposent une typologie de ces modes de raisonnements, ils les réunifient ultimement dans (...) la théorie des perspectives cumulative. La réunification de la rationalité constitue ainsi la pierre angulaire de la distinction entre ancienne et nouvelle économie comportementale et permet de rendre compte des débats contemporains entre Kahneman et Tversky, d’une part, et Gigerenzer, d’autre part, au sein de cette dernière. Codes JEL : A12, B13, B40, D01, D91. (shrink)

Most agree that, if all else is equal, patients should be provided with enough information about proposed medical therapies to allow them to make an informed decision about what, if anything, they wish to receive. This is the principle of informed choice; it is closely related to the notion of informed consent. Contemporary clinical trials are analysed according to classical statistics. This paper puts forward the argument that classical statistics does not provide the right sort of information for informing choice. (...) The notion of probability used by classical statistics is complex and difficult to communicate. Therapeutic decisions are best informed by statistical approaches that assign probabilities to hypotheses about the benefits and harms of therapies. Bayesian approaches to statistical inference provide such probabilities. (shrink)

Ideally, governing institutions would be designed so that they would produce and implement with certainty ‘human rights-compatible budgets’, i.e. budgets that adequately reflect the obligations enshrined in human rights. However, there are various reasons why a government may ultimately fail to produce such budgets. This article focuses on under-examined challenges for budgeting for human rights: epistemically oriented challenges. More specifically, the article engages in ‘horizon scanning’, and it maps key underlying factors that can be conducive to epistemically oriented challenges to (...) produce and implement human rights-compatible budgets. In addition, the article considers the road ahead from the perspective of institutional design. (shrink)

Dark patterns have received significant attention in literature as interface design practices which undermine users’ autonomy by coercing, misleading or manipulating their decision making and behavior. Individual autonomy has been argued to be one of the normative lenses for the evaluation of dark patterns. However, theoretical perspectives on autonomy have not been sufficiently adapted in literature to identify the ethical concerns raised by dark patterns. The aim of this paper is to conceptualize user autonomy within the context of dark patterns. (...) In this paper, we systematically review 151 dark patterns from 16 taxonomies to understand how dark patterns threaten users’ autonomy. We demonstrate through this analysis that implications for autonomy arise along four dimensions, because autonomy itself can be understood as subsuming several distinguishable concepts. These are agency, freedom of choice, control and independence. We argue that an assessment of whether a design pattern qualifies as ‘dark’ should account for the sense in which autonomy is threatened, as individuals’ rights and expectations of autonomy vary in various contexts and depend upon the interpretation of autonomy. This paper aims to contribute to the development of the normative lens of individual autonomy for the evaluation of dark patterns, as well as for persuasive design more broadly. (shrink)

Need for closure is a construct that describes a motivational tendency to quickly select and prioritize information in the environment. Such tendencies can affect the process of negotiations, and so the quality of their outcome. The rigidity that accompanies high need for closure can lead to less openness to proposals that benefit one’s partner, and to solutions that are less optimal. We conducted a study in which 34 pairs of individuals negotiated. Pairs were matched in terms of need for closure (...) and gender. We found that need for closure affected subjective evaluations of certain aspects of the negotiation process. Participants with low need for closure were more likely to indicate that they and their partners sought win-win solutions during the negotiation. This led to a greater sense of process fairness for the negotiation. These results can be taken into consideration when teaching negotiations, and when planning real-life negotiations. (shrink)

How do people make difficult decisions in situations involving substantial risk and uncertainty? In this study, we presented a difficult medical decision to three expert physicians in a combined “thinking aloud” and “cross examination” experiment. Verbatim transcripts were analyzed using script analysis to observe the process of constructing and making the decision, and using referring phrase analysis to determine the representation of knowledge of likelihoods. These analyses are compared with a formal decision analysis of the same problem to highlight similarities (...) and differences. The process of making the decision resembles an incremental, sequential‐refinement planning algorithm, where a complex decision is broken into a sequence of choices to be made with a simplified description of the alternatives. This strategy results in certain kinds of relevant information being underweighted in the final decision. Knowledge of likelihood appears to be represented as symbolic descriptions capturing categorical and ordinal relations with “landrhark” likelihoods, only some of which are described numerically. Numerical probabilities, capable of being combined and compared arithmetically, were not observed. These observations suggest an explanation for the heuristics and biases in human decision making under uncertainty in terms of the processes that manipulate symbolic descriptions of likelihoods and construct plans of action for situations involving risk and uncertainty. (shrink)

Charles Taber and Milton Lodge provide compelling evidence that people's minds may be closed to information that is inconsistent with their prior beliefs. This type of inconsistency has often been termed ?irrational.? However, recent research suggests that being open or closed minded is not an unchanging variable but depends on one's goals, including one's need for closure, which vary from person to person and situation to situation. In this vein, as Taber and Lodge suggest, those who have more political information (...) may, after having been open minded enough to acquire the information, become closed minded by virtue of having acquired it. At the same time, being more open minded to inaccurate information might lead one in the wrong direction; hence, open mindedness does not necessarily enhance the accuracy of one's judgments or the quality of one's decisions. We may need to rethink the concept of an enlightened, well-informed electorate, to the extent that it assumes the unqualified benefits of open mindedness. (shrink)

Despite the ubiquity of uncertainty, scientific attention has focused primarily on probabilistic approaches, which predominantly rely on the assumption that uncertainty can be measured and expressed numerically. At the same time, the increasing amount of research from a range of areas including psychology, economics, and sociology testify that in the real world, people’s understanding of risky and uncertain situations cannot be satisfactorily explained in probabilistic and decision-theoretical terms. In this article, we offer a theoretical overview of an alternative approach to (...) uncertainty developed in the framework of the ecological rationality research program. We first trace the origins of the ecological approach to uncertainty in Simon’s bounded rationality and Brunswik’s lens model framework and then proceed by outlining a theoretical view of uncertainty that ensues from the ecological rationality approach. We argue that the ecological concept of uncertainty relies on a systemic view of uncertainty that features it as a property of the organism–environment system. We also show how simple heuristics can deal with unmeasurable uncertainty and in what cases ignoring probabilities emerges as a proper response to uncertainty. (shrink)