While the existence of human cognitive and behavioral diversity is now widely recognized, it is not yet well established how to explain this diversity. In particular, it is still unclear how to determine whether any given instance of human cognitive and behavioral diversity is due to a common psychology that is merely “triggered” differently in different bio-cultural environments, or whether it is due to deeply and fundamentally different psychologies. This paper suggests that, to answer this question, we need to employ (...) subtle theoretical considerations of theory choice—especially the consideration of the complexity-weighted differential predictive successes of the two accounts. To make this clearer, the paper develops a novel analysis of the observed differences in human sharing dispositions. (shrink)

Humans are standouts in their propensity to trade. More specially, the kind of trading found in humans—featuring the exchange of many different goods and services with many different others, for the mutual benefit of all the involved parties—far exceeds anything that is found in any other creature. However, a number of important questions about this propensity remain open. First, it is not clear exactly what makes this propensity so different in the human case from that of other animals. Second, it (...) is not clear why other animals did not acquire this propensity to the extent that humans did. Third, it is not clear what explains the fact that the extent to which humans engage in trade is culturally highly variable. The paper argues that at the heart of the human-animal divergence in this propensity is the particular socio-cultural environment in which humans evolved. This has led them to sometimes, but not always, acquire the cognitive technology (writing, algebra, tallying devices, money, etc.) to support a sophisticated disposition and capacity for reciprocal cooperation, and deep and wide concepts of property and exchange value. (shrink)

It has been argued that the fundamental laws of physics do not face a ‘problem of provisos’ equivalent to that found in other scientific disciplines (Earman, Roberts and Smith 2002) and there is only the appearance of exceptions to physical laws if they are confused with differential equations of evolution type (Smith 2002). In this paper I argue that even if this is true, fundamental laws in physics still pose a major challenge to standard Humean approaches to lawhood, as they (...) are not in any obvious sense about regularities in behaviour. A Humean approach to physical laws with exceptions is possible, however, if we adopt a view of laws that takes them to be the algorithms in the algorithmic compressions of empirical data. When this is supplemented with a distinction between lossy and lossless compression, we can explain exceptions in terms of compression artefacts present in the application of the lossy laws. (shrink)

How can we use models to understand real phenomena if models misrepresent the very phenomena we seek to understand? Some accounts suggest that models may afford understanding by providing causal knowledge about phenomena via how-possibly explanations. However, general equilibrium models, for example, pose a challenge to this solution since their contribution appears to be purely mathematical results. Despite this, practitioners widely acknowledge that it improves our understanding of the world. I argue that the Arrow–Debreu model provides a mathematical how-possibly explanation (...) which establishes claims of mathematical dependence. The account developed reveals how mathematical knowledge can inform claims about the world, allow ‘what-if-things-had-been-different’ inferences, and thus improve our understanding. (shrink)

One puzzle concerning highly idealized models is whether they explain. Some suggest they provide so-called ‘how-possibly explanations’. However, this raises an important question about the nature of how-possibly explanations, namely what distinguishes them from ‘normal’, or how-actually, explanations? I provide an account of how-possibly explanations that clarifies their nature in the context of solving the puzzle of model-based explanation. I argue that the modal notions of actuality and possibility provide the relevant dividing lines between how-possibly and how-actually explanations. Whereas how-possibly (...) explanations establish claims of possible explanations, how-actually explanations establish claims of actual ones. Models, in turn, simply provide evidence for these claims. (shrink)

This paper introduces and defends an account of model-based science that I dub model pluralism. I argue that despite a growing awareness in the philosophy of science literature of the multiplicity, diversity, and richness of models and modeling practices, more radical conclusions follow from this recognition than have previously been inferred. Going against the tendency within the literature to generalize from single models, I explicate and defend the following two core theses: any successful analysis of models must target sets of (...) models, their multiplicity of functions within science, and their scientific context and history and for almost any aspect x of phenomenon y, scientists require multiple models to achieve scientific goal z. (shrink)

This commentary focuses on the parts of psychological game theory dealing with preference, as illustrated by team reasoning, and supports the conclusion that these theoretical notions do not contribute above and beyond existing theory in understanding social interaction. In particular, psychology and games are already bridged by a comprehensive, formal, and inherently psychological theory, interdependence theory (Kelley & Thibaut 1978; Kelley et al. 2003), which has been demonstrated to account for a wide variety of social interaction phenomena.

Most papers in theoretical economics contain thought experiments. They take the form of more informal bits of reasoning that precede the presentation of the formal, mathematical models these papers are known for. These thought experiments differ from the formal models in various ways. In particular, they do not invoke the same idealized assumptions about the rationality, knowledge, and preferences of agents. The presence of thought experiments in papers that present formal models, and the fact that they differ from the formal (...) models in this way, is often ignored in debates on what, if anything, we can learn from formal models in theoretical economics. I show that paying due attention to thought experiments in theoretical economics has serious implications for this debate. Differences between thought experiments and formal models are especially problematic for Robert Sugden’s “credible worlds” account. (shrink)

According to Margaret Gilbert’s collective epistemology, we should take attributions of beliefs to groups seriously, rather than metaphorically or as reducible to individual belief. I argue that, similarly, attributions of belief to markets ought to be taken seriously and not merely as reports of the average beliefs of market participants. While many of Gilbert’s purported examples of group belief are better thought of as instances of acceptance, some collectives, such as courts and markets, genuinely believe. Such collectives enact truth-aimed processes (...) that are beyond the control of any single individual. These processes produce beliefs that are distinct from any individual belief and do not merely report the “average” or “majority” view of the group. In the case of markets, beliefs are indicated by prices, though it is often difficult to infer beliefs from prices and those inferences are almost always uncertain. Reliabilism is the best available standard of justification for market beliefs. In some cases market beliefs are reliable and prove to be true. Thus, in some cases markets can know. (shrink)

This paper presents an account of how to evaluate formal models of science: models and simulations in social epistemology designed to draw normative conclusions about the social structure of scientific research. I argue that such models should be evaluated according to their representational and predictive accuracy. Using these criteria and comparisons with familiar models from science, I argue that most formal models of science are incapable of supporting normative conclusions.

In a broad brush, biological models are often constructed in two general types: as a concrete model; as an abstract model. A concrete model is a material model such as model organisms, while an abstract model is a mathematical or computational model consists of equations or algorithms. Though there are types of biological models that cannot be strictly categorized as either concrete or abstract, they are falling somewhere in between this spectrum. In view of the fact that biological phenomena are (...) sui generis and distinct from physical phenomena in many respects, using the concepts in standard modeling fails to account for the differences between biological sciences and physical sciences. Drawing from the resources of a credible-world account of models in economic modeling, I propose to reinterpret abstract models and concrete models in the light of the credible world account of models. (shrink)

Is there a unique way to de-idealize models? If not, how might the possible ways of reducing the distortion between models and reality differ from each other? Based on an empirical case study conducted in financial markets, this paper discusses how a popular valuation model (the Discounted Cash Flow model) idealizes reality and how the market participants de-idealize it in concrete market situations. In contrast to Cartwright's view that economic models are generally over-constrained, this paper suggests that valuation models are (...) under-constrained. This serves as the reason why the relaxation of simplifying assumptions and concretization do not work as methods of de-idealization. The paper finds that financial market participants de-idealize models using commentary that takes the form of judgment. As a conclusion, a hypothesis is formulated that proposes that the more underdetermined the model is the bigger role narrative and other pragmatic elements play in the process of model application. (shrink)

This paper considers the debate between economists and philosophers about the role of values in economic analysis by examining the recent debate between Hilary Putnam and Sir Partha Dasgupta. It argues that although there has been a failure to communicate there is much more agreement than it seems. If Dasgupta's work is seen as part of the methodological tradition expounded by John Stuart Mill and John Neville Keynes, economists and philosophers will have a better basis for understanding each other. Unlike (...) the logical-positivist tradition, which treats facts and values as two mutually exclusive concepts, the Mill- Keynes tradition recognizes that facts and values are intertwined. Unlike the Smithian tradition, which blends the study of facts and normative rules, it divides economics into a science that studies "what is" and an art which considers "what ought to be done". (shrink)

Why are causal generalizations in the higher-level sciences “inexact”? That is, why do they have apparent exceptions? This paper offers one explanation: many causal generalizations cite as their antecedent—the \(F\) in \(Fs\,\, {\textit{are}}\,\, G\) —a property that is not causally relevant to the consequent, but which is rather “entangled” with a causally relevant property. Entanglement is a relation that may exist for many reasons, and that allows of exceptions. Causal generalizations that specify entangled but causally irrelevant antecedents therefore tolerate exceptions.

What do the words "ceteris paribus" add to a causal hypothesis, that is, to a generalization that is intended to articulate the consequences of a causal mechanism? One answer, which looks almost too good to be true, is that a ceteris paribus hedge restricts the scope of the hypothesis to those cases where nothing undermines, interferes with, or undoes the effect of the mechanism in question, even if the hypothesis's own formulator is otherwise unable to specify fully what might constitute (...) such undermining or interference. I will propose a semantics for causal generalizations according to which ceteris paribus hedges deliver on this promise, because the truth conditions for a causal generalization depend in part on the—perhaps unknown—nature of the mechanism whose consequences it is intended to describe. It follows that the truth conditions for causal hypotheses are typically opaque to the very scientists who formulate and test them. (shrink)

This essay examines the issue of false assumptions in models via a case study of a prominent economic model of sustainable development, wherein the assumption of an infinite future plays a central role. Two proposals are found to be helpful for this case, one based on the concept of derivational robustness and the other on understanding. Both suggest that the assumption of an infinite future, while arguably legitimate in some applications of the model, is problematic with respect to what I (...) call “Parfitian” welfare functions. This result is relevant to debates about discounting the future in economics and environmental ethics. (shrink)

This article examines methodological individualism in terms of the theory that invariance under intervention is the signal feature of generalizations that serve as a basis for causal explanation. This theory supports the holist contention that macro-level generalizations can explain, but it also suggests a defense of methodological individualism on the grounds that greater range of invariance under intervention entails deeper explanation. Although this individualist position is not threatened by multiple-realizability, an argument for it based on rational choice theory is called (...) into question by experimental results concerning preference reversals. Key Words: methodological individualism • mechanisms • explanation • invariance • preference reversal. (shrink)

Imagine asking a typical, well informed, contemporary philosopher whether or not she considered biology to be a science. Our informant, being a philosopher, would not necessarily respond with the straightforward “of course” that would be expected from anyone else. She might first reason through a complicated and heavily qualified definition of science, or she might distinguish certain parts of biology that she held to be more clearly scientific than others. If she were partial to a certain sort of critical stance, (...) she might question the political basis for wishing to dignify certain parts of our inquisitive practice with the honorific ‘scientific’ in the first place. But there is at least one thing that she would almost certainly not do. She would not simultaneously embrace a version of the conventional philosophical view of science and deny that biology is a science. This is despite the fact that, as she will acknowledge, biology exploits a range of methodologies and explanatory strategies that have not yet admitted of systematic, consensual philosophical explication. (shrink)

To what use can causal claims established in good policy studies be put? We isolate two reasons inferences from study to target fail. First, policy variables do not produce results on their own; they need helping factors. The distribution of helping factors is likely to be unique or local for each study, so one cannot expect external validity to be all that common. Second, researchers often give too concrete a description of the cause in the study for it to carry (...) over to the target. Abstraction is necessary to get causes that travel. There is no sure-fire way to guard against these problems. But the unavailability of one perfect tool does not imply there are no second best contrivances. Two general pointers for Good Practice in policy advice follow from our diagnosis: focus on the concrete details in the target and use cross discipline heuristics that diversify background knowledge.¿Qué uso podemos hacer de las tesis causales que encontramos en los buenos estudios sobre política aplicada? Distinguimos dos razones por las que pueden fallar las inferencias desde la población en el estudio a la población general. En primer lugar, las variables que usamos en política no generan resultados por sí solas. Necesitan factores coadyuvantes. La distribución de estos factores es probablemente única o local en cada estudio, así que no hay motivos para esperar su validez externa. En segundo lugar, los investigadores a menudo dan descripciones demasiado concretas de la causalidad en el estudio como para poder generalizarlas. La abstracción es necesaria para obtener causas que viajen. No hay ningún modo absolutamente seguro de evitar semejantes fallos. Pero esto no implica que no haya arreglos subóptimos. De nuestro diagnóstico se siguen dos orientaciones generales sobre las buenas prácticas en la asesoría política: concentrémonos en los detalles concretos de la población en la que pretendemos intervenir y usemos heurísticas transdisciplinares que diversifiquen nuestro conocimiento de fondo. (shrink)

To what use can causal claims established in good studies be put? We give examples of studies from which inaccurate inferences were made about target policy situations. The usual diagnosis is that the studies in question lack external validity, which means that the same results do not hold in the target as in study. That’s a label that just repeats what we already knew. We offer a deeper analysis. Our analysis points to the need for interdisciplinarity and to the demand (...) to focus not on the study – as the expression ‘external validity’ invites you to do – but on the target. The call for interdisciplinary approaches to real life problems is common since it is widely acknowledged that what happens in the real world seldom falls under the auspices of any single research domain. Our focus is on one specific real life problem: how to use causal claims from good studies to help predict whether the policies tested will work in a new situation. Our analysis of what it takes to back up these predictions points up very specific stages in the process of prediction where we are bound to get it wrong if we do not diversify our concepts, our knowledge and our methods. We isolate two reasons inferences from study to target fail. First, policy variables do not produce results on their own; they need helping factors. The distribution of helping factors is likely to be unique or local for each study, so one cannot expect external validity to be all that common. Second, researchers often give too concrete a description of the cause in the study for it to carry over to the target.ion is necessary to get causes that travel. There is no sure-fire way to guard against these problems. But the unavailability of one perfect tool does not imply there are no second best contrivances. Two general pointers for Good Practice in policy advice follow from our diagnosis: focus on the concrete details in the target and use cross discipline heuristics that diversify background knowledge. (shrink)

Laws in the special sciences are usually regarded to be non-universal. A theory of laws in the special sciences faces two challenges. (I) According to Lange's dilemma, laws in the special sciences are either false or trivially true. (II) They have to meet the ?requirement of relevance?, which is a way to require the non-accidentality of special science laws. I argue that both challenges can be met if one distinguishes four dimensions of (non-) universality. The upshot is that I argue (...) for the following explication of special science laws: L is a special science law just if (1) L is a system law, (2) L is quasi-Newtonian, and (3) L is minimally invariant. (shrink)

Despite the conclusions from the contemporary philosophy of science, many economists cherish the ideal of positive science. Therefore, value-free economics is still the central paradigm in economics. The first aim of the paper is to investigate economics' axiomatic assumptions from an epistemological perspective. The critical analysis of the literature shows that the positive-normative dichotomy is exaggerated. Moreover, value-free economics is based on normative foundations that have a negative impact on individuals and society. The paper's second aim is to show that (...) economics' normativity is not a problem because the discussion concerning values is possible and unavoidable. In this context, Weber and other methodologists are investigated. The conclusion of the paper is that science can thrive without strict methodological rules thanks to institutional mechanisms. Therefore, economists could learn from artists who accept the world without absolute rules. This perspective opens the possibility for methodological pluralism and normative approaches. (shrink)

In this essay, I first consider a popular view of models and modeling, the similarity view. Second, I contend that arguments for it fail and it suffers from what I call “Hughes’ worry.” Third, I offer a deflationary approach to models and modeling that avoids Hughes’ worry and shows how scientific representations are of apiece with other types of representations. Finally, I consider an objection that the similarity view can deal with approximations better than the deflationary view and show that (...) this is not so. (shrink)

Theoretical biology and economics are remarkably similar in their reliance on mathematical models, which attempt to represent real world systems using many idealized assumptions. They are also similar in placing a great emphasis on derivational robustness of modeling results. Recently philosophers of biology and economics have argued that robustness analysis can be a method for confirmation of claims about causal mechanisms, despite the significant reliance of these models on patently false assumptions. We argue that the power of robustness analysis has (...) been greatly exaggerated. It is best regarded as a method of discovery rather than confirmation. (shrink)

This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.

This article shows how the MISS account of models—as isolations and surrogate systems—accommodates and elaborates Sugden’s account of models as credible worlds and Hausman’s account of models as explorations. Theoretical models typically isolate by means of idealization, and they are representatives of some target system, which prompts issues of resemblance between the two to arise. Models as representations are constrained both ontologically (by their targets) and pragmatically (by the purposes and audiences of the modeller), and these relations are coordinated by (...) a model commentary. Surrogate models are often about single mechanisms. They are distinguishable from substitute models, which are examined without any concern about their connections with the target. Models as credible worlds are surrogate models that are believed to provide access to their targets on account of their credibility (of which a few senses are distinguished). (shrink)

Consider how your consumption would change if you were stranded on a deserted island. Isolation would eliminate all social influences on your consumption decisions, even for the same choice set. You might decide not to consume cosmetics, curtains, or neckties, and pay less attention to the style or color of your clothes, car, or furniture. These choices might not matter as much to you anymore, for you would not have to consider the reactions of other individuals to your consumption. Similarly, (...) isolation would also eliminate social influences on your speech. Absent an audience, your choice of words would not be subject to the judgments of others. (shrink)

Like other mathematically intensive sciences, economics is becoming increasingly computerized. Despite the extent of the computation, however, there is very little true simulation. Simple computation is a form of theory articulation, whereas true simulation is analogous to an experimental procedure. Successful computation is faithful to an underlying mathematical model, whereas successful simulation directly mimics a process or a system. The computer is seen as a legitimate tool in economics only when traditional analytical solutions cannot be derived, i.e., only as a (...) purely computational aid. We argue that true simulation is seldom practiced because it does not fit the conception of understanding inherent in mainstream economics. According to this conception, understanding is constituted by analytical derivation from a set of fundamental economic axioms. We articulate this conception using the concept of economists' perfect model. Since the deductive links between the assumptions and the consequences are not transparent in ‘bottom‐up’ generative microsimulations, microsimulations cannot correspond to the perfect model and economists do not therefore consider them viable candidates for generating theories that enhance economic understanding. (shrink)

Ceteris-paribus clauses are nothing to worry about; aceteris-paribus qualifier is not poisonously indeterminate in meaning. Ceteris-paribus laws teach us that a law need not be associated straightforwardly with a regularity in the manner demanded by regularity analyses of law and analyses of laws as relations among universals. This lesson enables us to understand the sense in which the laws of nature would have been no different under various counterfactual suppositions — a feature even of those laws that involve no ceteris-paribus (...) qualification and are actually associated with exceptionless regularities. Ceteris-paribus generalizations of an‘inexact science’ qualify as laws of that science in virtue of their distinctive relation to counterfactuals: they form a set that is stable for the purposes of that field. (Though an accident may possess tremendous resilience under counterfactual suppositions, the laws are sharply distinguished from the accidents in that the laws are collectively as resilient as they could logically possibly be.) The stability of an inexact science's laws may involve their remaining reliable even under certain counterfactual suppositions violating fundamental laws of physics. The ceteris-paribus laws of an inexact science may thus possess a kind of necessity lacking in the fundamental laws of physics. A nomological explanation supplied by an inexact science would then be irreducible to an explanation of the same phenomenon at the level of fundamental physics. Island biogeography is used to illustrate how a special science could be autonomous in this manner. (shrink)

The paper aims to assess whether the ideas developed by Don Ross in his recent book Economic theory and cognitive science: microexplanation, which relates neoclassical economics to recent developments in cognitive science, might revolutionize the methodology of economics. Since Ross challenges a conception of economics associated with what is pejoratively called 'Folk psychology', the paper discusses ideas of the philosopher Daniel Dennett on which this challenge is largely based. This discussion could not avoid bearing on questions such as the nature (...) of consciousness, the interpretation of ontological realism, the relations between agency and selfhood, and the nature and scope of economics. The paper attempts to rehabilitate the two pieces of the traditional conception of economics that were most radically contested by Ross, namely methodological individualism and the foundational role of rationality in economics. A relatively nuanced judgment on Ross's bold enterprise is proposed in conclusion. (shrink)

We claim that the process of theoretical model refinement in economics is best characterised as robustness analysis: the systematic examination of the robustness of modelling results with respect to particular modelling assumptions. We argue that this practise has epistemic value by extending William Wimsatt's account of robustness analysis as triangulation via independent means of determination. For economists robustness analysis is a crucial methodological strategy because their models are often based on idealisations and abstractions, and it is usually difficult to tell (...) which idealisations are truly harmful. (shrink)

An otherwise lawlike generalisation hedged by a ceteris paribus (CP) clause qualifies as a law of nature, if the CP clause can be substituted with a set of conditions derived from the multivariate regression model used to interpret the empirical data in support of the gen- eralisation. Three studies in human biology that use regression analysis are surveyed, showing that standard objections to cashing out CP clauses in this way—based on alleged vagueness, vacuity, or lack of testability—do not apply. CP (...) laws also cannot be said to be simply false due to the indefinitely many conditions not explicitly stated in their associated model: scientific CP clauses imply that these are, given the evidence, not nomically relevant. (shrink)

One striking feature of the contemporary modelling practice is its interdisciplinary nature. The same equation forms, and mathematical and computational methods, are used across different disciplines, as well as within the same discipline. Are there, then, differences between intra- and interdisciplinary transfer, and can the comparison between the two provide more insight on the challenges of interdisciplinary theoretical work? We will study the development and various uses of the Ising model within physics, contrasting them to its applications to socio-economic systems. (...) While the renormalization group methods justify the transfer of the Ising model within physics – by ascribing them to the same universality class – its application to socio-economic phenomena has no such theoretical grounding. As a result, the insights gained by modelling socio-economic phenomena by the Ising model may remain limited. (shrink)

Much scientific thinking and thinking about science involves assumptions that there is a deep and pervasive order to the world that it is the business of science to disclose. A paradigmatic statement of such a view can be found in a widely discussed paper by a prominent economist, Milton Friedman (a paper which will be discussed in more detail shortly): A fundamental hypothesis of science is that appearances are deceptive and that there is a way of looking at or interpreting (...) or organizing the evidence that will reveal superficially disconnected and diverse phenomena to be manifestations of a more fundamental and relatively simple structure. (1953/1984, p.231) On the other hand, the person sometimes described as the father of modern science, Francis Bacon, wrote: The human understanding is of its own nature prone to suppose the existence of more order and regularity in the world than it finds. And though there be many things in nature which are singular and unmatched, yet it devises for them conjugates and relatives which do not exist. (1620/1960, p. 50). (shrink)

La filosofía estándar de la economía presupone que en el dominio de los fenómenos económicos subyacen regularidades estables, las cuales pueden explicarse mediante el funcionamiento de mecanismos o de máquinas socioeconómicas. Asimismo, se considera que una vez puestos en funcionamiento, su comportamiento no necesita de subsecuentes intervenciones. Esto implica asumir que los procesos socioeconómicos tienen una naturaleza semejante a los de las ciencias naturales. No obstante, dichas regularidades son por lo general examinadas a la luz de algún modelo económico, por (...) lo cual pierden muchas veces contacto con el mundo real. Este trabajo tiene como objetivo poner en el centro del análisis otro objeto de estudio: los procesos económicos basados en expectativas. Se trata de procesos en los cuales la acción humana funciona como nexo causal entre las variables económicas y en los que dicha acción es producto de una formación previa de expectativas, las cuales son sensibles a la información del contexto. Se mostrará que en esta clase de procesos la intervención sistemática sobre las condiciones de fondo y sobre las expectativas es fundamental si lo que se busca es alcanzar un objetivo deseado o lograr un proceso estable. Esta intervención requerirá no solo del conocimiento proporcionado por los modelos, sino también de un conocimiento extrateorético o interdisciplinario. Mainstream philosophy of economics assumes that steady regularities underlie the domain of economic phenomena which can be explained by the operation of mechanisms or socioeconomic machines. It is also considered that once operating those mechanisms don't need further interventions. This implies the assumption that the nature of socioeconomic processes is similar to the one of the natural sciences. Nevertheless, such regularities are usually examined in the light of some economic model, which often ends up losing contact with the real world. The present paper aims at putting in the center of the analysis another object of study: the economic processes based on expectations. In these processes the human action operates as a causal link between economic variables; such an action being the result of a previous building of expectations which are sensitive to the information of the context. It will be shown that the systematic intervention on the background conditions and expectations is fundamental in this kind of processes if what is sought is fulfilling a desired goal or managing a stable process. That intervention will not only require the knowledge provided by models but also an extra-theoretical or interdisciplinary knowledge. (shrink)

This note replies to a comment by Daniel Hausman on our paper ‘Preference purification and the inner rational agent: a critique of the conventional wisdom of behavioural welfare economics’. We clarify our characterisation of behavioural welfare economics and acknowledge that Hausman does fully endorse this approach. However, we argue that Hausman’s response to our critique, like behavioural welfare economics itself, implicitly uses a model of an inner rational agent.

New technologies not only contribute greatly to society and the economy; they also involve fundamental societal shifts, challenging our values and ideas about ourselves and the world. With a view to aligning technological change and innovation with ethical values, the concept of responsible innovation advocates the inclusion of a variety of stakeholders, in particular from society. In shifting moral responsibility towards the producers of innovations, responsible innovation rejects the standard normative economic view that the ethical evaluation of innovations is a (...) matter of individual consumers’ market-based choices. However, in this article we argue that responsible innovation should not abandon all normative consideration of the individual outright, to which end we present an alternative normative economic approach based on preference learning. We show how this approach can provide an enhanced understanding of responsible innovation by clarifying the redistribution of moral responsibility and casting individuals in the normative role of co-innovators, rather than mere consumers. We argue that responsible innovation should enable individuals to form preferences and evaluate innovations, so as to align innovation with ethical demands. Finally, we show how our proposed approach can be put into practice in so-called laboratories in real-world contexts, using methods from the field of design. In short, drawing on normative economics, this article aims to establish a new understanding of responsible innovation that is conceptually sound and can form the basis for novel innovation practices. (shrink)

It is argued that one can learn from minimal economic models. Minimal models are models that are not similar to the real world, do not resemble some of its features, and do not adhere to accepted regularities. One learns from a model if constructing and analysing the model affects one’s confidence in hypotheses about the world. Economic models, I argue, are often assessed for their credibility. If a model is judged credible, it is considered to be a relevant possibility. Considering (...) such relevant possibilities may affect one’s confidence in necessity or impossibility hypotheses. Thus, one can learn from minimal economic models. (shrink)

The notion of bounded rationality has recently gained considerable popularity in the behavioural and social sciences. This article surveys the different usages of the term, in particular the way ‘anomalosus’ behavioural phenomena are elicited, how these phenomena are incorporated in model building, and what sort of new theories of behaviour have been developed to account for bounded rationality in choice and in deliberation. It also discusses the normative relevance of bounded rationality, in particular as a justifier of non‐standard reasoning and (...) deliberation heuristics. For each of these usages, the overview discusses the central methodological problems. (shrink)

The thesis that in social sciences causal explanations are possible only in terms o mechanisms due to the lack of genuine laws has been increasingly popular among social scientist and philosophers. In this article it is examined whether the explanation by mechanism is necessarily an explanation without laws or, on the contrary, it can involve some kind o laws. To this end it is argued, firstly, that mechanisms are not always the antonym of law insofar as they express propensities and (...) so tendencies; secondly, that these tendencies ar causal and entail capacities and dispositions; thirdly, that capacities and dispositions involve in human behaviour have to face the problem of free will; and finally, reasons are offered i favor of considering causal tendencies as authentic laws. The ultimate aim of this article is to demonstrate that explanation of social facts can involve well-established laws in its explanans although they are not universal laws. (shrink)

In recent years, several authors have reconstructed the relationship between 20th-century economic theory and neuro-psychological research in terms of a three-stage narrative of initial unity, increasing separation, and ongoing reunification. In this article, I draw on major developments in economic theory and neuro-psychological research to provide a descriptive and normative critique of this reconstruction. Moreover, I put forward a reconstruction of the relationship between economics and neuro-psychology that, I claim, better fits both the available empirical evidence and the methodological foundations (...) of these disciplines. In doing so, I argue that recent calls to develop a unified interdisciplinary framework for modeling choice are premised on disputable presuppositions concerning both the domain of economic theory and the relationship between this theory’s axiomatic foundations and empirical findings about the neuro-psychological substrates of choice. (shrink)

ABSTRACTNormative political epistemologists, such as epistemic democrats, study whether political decision makers can, in principle, be expected to know what they need to know if they are to make wise public policy. Empirical political epistemologists study the content and sources of real-world political actors' knowledge and interpretations of knowledge. In recent years, empirical political epistemologists have taken up the study of the ideas of political actors other than voters, such as bureaucrats and politicians. Normative political epistemologists could follow this lead (...) if they were to focus on the technocratic orientation of nearly all political actors in the West: that is, on their desire to solve social and economic problems. Since most technocratic policy is made by political elites, the reliability of elites' knowledge of the causes of and cures for social and economic problems is a natural topic for normative political epistemology. (shrink)