Les neurosciences sont utilisées en économie dans l’objectif d’améliorer la compréhension et la description des choix individuels. Elles permettent aussi d’évaluer la rationalité des décideurs et de réguler les comportements. Cet article analyse les implications normatives de la neuroéconomie, en dégageant les apports des neurosciences à l’économie du bien-être et à l’économie publique. L’interventionnisme économique défendu par les neuroéconomistes (par exemple, Bernheim et Rangel 2004) y est interprété comme une politique caractéristique du néo-libéralisme, au sens qu’en donne Michel Foucault (1978b). (...) Si la neuroimagerie ne permet pas de « manipuler » directement le cerveau des décideurs, elle offre en revanche la possibilité de détecter le caractère pathologique ou irrationnel de certaines conduites. Ce diagnostic justifie une régulation comportementale du bien-être, qui doit être distinguée du paternalisme libertarien de Sunstein et Thaler (2003). Dans les deux cas, c’est l’environnement plutôt que le décideur lui-même qui est la cible de l’intervention, mais la justification théorique n’est pas la même. Pour les neuroéconomistes, l’irrationalité d’un comportement tel que l’addiction ne résulte pas d’un biais cognitif de l’individu, mais de son interaction avec un environnement pathologique. Les réflexions normatives des neuroéconomistes s’inscrivent dans le prolongement théorique des réflexions de Michel Foucault sur la biopolitique et le néolibéralisme (Foucault 2004b). Notre étude vaut ainsi comme une contribution à l’étude de la gouvernementalité. Elle nous conduit à défendre une interprétation non-réductionniste des rapports entre savoir et pouvoir chez Foucault. Classification JEL : D87, H10, B41. (shrink)

This PhD thesis focuses on the philosophical foundations of Neuroeconomics, an innovative research program which combines findings and modelling tools from economics, psychology and neuroscience to account for human choice behaviour. The proponents of Neuroeconomics often manifest the ambition to foster radical modifications in the accounts of choice behaviour developed by its parent disciplines. This enquiry provides a philosophically informed appraisal of the potential for success and the relevance of neuroeconomic research for economics. My central claim is that neuroeconomists can (...) help other economists to build more predictive and explanatory models, yet are unlikely to foster revolutionary modifications in the economic theory of choice. The contents are organized as follows. In chapters 1-2, I present neuroeconomists’ investigative tools, distinguish the most influential approaches to neuroeconomic research and reconstruct the case in favour of a neural enrichment of economic theory. In chapters 3-7, I combine insights from neuro-psychology, economic methodology and philosophy of science to develop a systematic critique of Neuroeconomics. In particular, I articulate four lines of argument to demonstrate that economists are provisionally justified in retaining a methodologically distinctive approach to the modelling of decision making. My first argument points to several evidential and epistemological concerns which complicate the interpretation of neural data and cast doubt on the inferences neuroeconomists often make in their studies. My second argument aims to show that the trade-offs between the modelling desiderata that neuroeconomists and other economists respectively value severely constrain the incorporation of neural insights into economic models. My third argument questions neuroeconomists’ attempts to develop a unified theory of choice behaviour by identifying some central issues on which they hold contrasting positions. My fourth argument differentiates various senses of the term ‘revolution’ and illustrates that neuroeconomists are unlikely to provide revolutionary contributions to economic theory in any of these senses. (shrink)

The books’ goal is to answer the question: Do the weaknesses of value-free economics imply the need for a paradigm shift? The author synthesizes criticisms from different perspectives (descriptive and methodological). Special attention is paid to choices over time, because in this area value-free economics has the most problems. In that context, the enriched concept of multiple self is proposed and investigated. However, it is not enough to present the criticisms towards value-free economics. For scientists, a bad paradigm is better (...) than no paradigm. Therefore, the author considers whether value-based economics with normative approaches such as economics of happiness, capability approach, libertarian paternalism, and the concept of multiple self can be the alternative paradigm for value-free economics. This book is essential reading to everyone interested in the current state of economics as a discipline. (shrink)

Neuroscience is a fascinating discipline – its dynamic progress has led to the emergence of new interdisciplinary research programmes with great potential. One of these research areas is neuroeconomics. As will be shown in this article, this discipline, which is difficult to clearly characterize and define, is faced with many problems. This paper argues that social scientists should be interested in the problems and tendencies in social neuroscience for several reasons. Neuroeconomics, and other disciplines inspired by neuroscience, will compete with (...) their parent disciplines in many fields of interest. On one hand it will be necessary for scientists to define and defend the irreplaceable roles of their disciplines, but also critically evaluate the potential of new approaches on the other. In the context of this discussion, which reopens questions about the scientific status of economics and its roles, this paper introduces the main problems related to neuroeconomics. This paper concludes that these problems represent a wide domain for social scientists and methodologists of science. (shrink)

There continues to be significant confusion about the goals, scope, and nature of modelling practice in neuroeconomics. This article aims to dispel some such confusion by using one of the most recent critiques of neuroeconomic modelling as a foil. The article argues for two claims. First, currently, for at least some economic model of choice behaviour, the benefits derivable from neurally informing an economic model do not involve special tractability costs. Second, modelling in neuroeconomics is best understood within Marr’s three-level (...) of analysis framework and in light of a co-evolutionary research ideology. The first claim is established by elucidating the relationship between the tractability of a model, its descriptive accuracy, and its number of variables. The second claim relies on an explanation of what it can take to neurally inform an economic model of choice behaviour. 1 Introduction2 Neurally Informed Models of Choice: A Case Study2.1 A case study on risk-sensitive choice2.1.1 Target and modelling framework2.1.2 Research question and hypotheses2.1.3 Competitive models of risk-sensitive behaviour2.1.4 Model-based fMRI: from economics to brains and back2.2 Neurally informed modelling3 Tractability: When Does Size Matter?4 Neural Integration and the Co-evolutionary Research Ideology5 Conclusion. (shrink)

In traditional decision theory, utility is regarded as a mathematical representation of preferences to be inferred from agents hedonic experiences. Some go as far as to contend that utility is literally computed by specific neural areas and urge economists to complement or substitute their notion of utility with some neuro-psychological construct. In this paper, I distinguish three notions of utility that are frequently mentioned in debates about decision theory and examine some critical issues regarding their definition and measurability. Moreover, I (...) provide various empirical and conceptual reasons to doubt that economists should base decision theoretic analyses on some neuro-psychological notion of utility. (shrink)

Book Reviews Jack Vromen, Economics and Philosophy, FirstView Article.

By the late 1990s, several converging trends in economics, psychology, and neuroscience had set the stage for the birth of a new scientific field known as “neuroeconomics”. Without the availability of an extensive variety of experimental designs for dealing with individual and social decision-making provided by experimental economics and psychology, many neuroeconomics studies could not have been developed. At the same time, without the significant progress made in neuroscience for grasping and understanding brain functioning, neuroeconomics would have never seen the (...) light of day. The paper is an overview of the main significant advances in the knowledge of brain functioning by neuroscience that have contributed to the emergence of neuroeconomics and its rise over the past two decades. These advances are grouped over three non-independent topics referred to as the “emo-rational” brain, “social” brain, and “computational” brain. For each topic, it emphasizes findings considered as critical to the birth and development of neuroeconomics while highlighting some of prominent questions about which knowledge should be improved by future research. In parallel, it shows that the boundaries between neuroeconomics and several recent sub-fields of cognitive neuroscience, such as affective, social, and more generally, decision neuroscience, are rather porous. (shrink)

In a recent article in this Journal, Fumagalli argues that economists are provisionally justified in resisting prominent calls to integrate neural variables into economic models of choice. In other articles, various authors engage with Fumagalli’s argument and try to substantiate three often-made claims concerning neuroeconomic modelling. First, the benefits derivable from neurally informing some economic models of choice do not involve significant tractability costs. Second, neuroeconomic modelling is best understood within Marr’s three-level of analysis framework for information-processing systems. And third, (...) neural findings enable choice modellers to confirm the causal relevance of variables posited by competing economic models, identify causally relevant variables overlooked by existing models, and explain observed behavioural variability better than standard economic models. In this paper, I critically examine these three claims and respond to the related criticisms of Fumagalli’s argument. Moreover, I qualify and extend Fumagalli’s account of how trade-offs between distinct modelling desiderata hamper neuroeconomists’ attempts to improve economic models of choice. I then draw on influential neuroeconomic studies to argue that even the putatively best available neural findings fail to substantiate current calls for a neural enrichment of economic models. (shrink)

Proponents of neuroeconomics often argue that better knowledge of the human neural architecture enables economists to improve standard models of choice. In their view, these improvements provide compelling reasons to use neural findings in constructing and evaluating economic models. In a recent article, I criticized this view by pointing to the trade-offs between the modeling desiderata valued by neuroeconomists and other economists, respectively. The present article complements my earlier critique by focusing on three modeling desiderata that figure prominently in economic (...) and neuroeconomic modeling. For each desideratum, I examine findings that neuroeconomists deem to be especially relevant for economists and argue that neuroeconomists have failed to substantiate their calls to use these findings in constructing and evaluating economic models. In doing so, I identify methodological and evidential constraints that will continue to hinder neuroeconomists’ attempts to improve such models. Moreover, I draw on the literature on scientific modeling to advance the ongoing philosophical discussion regarding the prospects of interdisciplinary models of choice. (shrink)

In the recent literature at the interface between economics, biology and neuroscience, several authors argue that by adopting an interdisciplinary approach to the analysis of decision making, economists will be able to construct predictively and explanatorily superior models. However, most economists remain quite reluctant to import biological or neural insights into their account of choice behaviour. In this paper, I reconstruct and critique one of the main arguments by means of which economists attempt to vindicate their conservative position. Furthermore, I (...) develop an alternative defense of the thesis that economists justifiably rely on a methodologically distinctive approach to the modelling of choice behaviour. (shrink)

In Homo Deus, Yuval Noah Harari argues that technological advances of the twenty-first century will usher in a significant shift in how humans make important life decisions. Instead of turning to the Bible or the Quran, to the heart or to our therapists, parents, and mentors, people will turn to Big Data recommendation algorithms to make these choices for them. Much as we rely on Spotify to recommend music to us, we will soon rely on algorithms to decide our careers, (...) spouses, and commitments. Harari also predicts that next, the state will take away individuals’ rights to make their own choices about their lives. If Google knows where your children would flourish best in school, why should the state allow a fallible human parent to decide? Liberalism—which, as Harari uses this term, refers to a state of society in which human freedom to choose is respected and championed—will collapse. In this paper, I argue that Harari’s conception of the future implications of recommendation algorithms is deeply flawed, for two reasons. First, users will not rely on algorithms to make decisions for them because they have no reason to trust algorithms, which are developed by companies with their own incentives, such as profit. Second, for most of our life decisions, algorithms will not be able to be developed, because the factors relevant to the decisions we face are unique to our situation. I present an alternative depiction of the future: instead of relying on algorithms to make decisions for us, humans will use algorithms to enhance our decision-making by helping us consider the most relevant choices first and notice information we might not otherwise. Finally, I will also argue that even if computers could make many of our decisions for us, liberalism as a political system would emerge unscathed. (shrink)

À la fin des années 1990, plusieurs tendances convergentes en économie, psychologie et neuroscience ont préparé le terrain pour la naissance d’un nouveau champ scientifique qualifié de « neuroéconomie ». Comme pour toute discipline émergente – pensons par exemple à l’économie mathématique, l’économétrie ou l’économie expérimentale en d’autres temps – la neuroéconomie est plutôt controversée en économie. Elle soulève un grand nombre de questions d’ordre empirique, méthodologique et philosophiques donnant lieu à des débats et controverses que l’article identifie et discute (...) à travers trois questions majeures relatives aux connaissances produites : Sont-elles fiables? Sont-elles scientifiquement légitimes? Sont-elles utiles pour les économistes? Sans prétendre à l’exhaustivité, ce cadre analytique permet de comprendre l’essence des principales critiques adressées à la neuroéconomie. Dans le même temps, l’article éclaire la nature des réponses susceptibles d’être apportées à ces critiques au vu des progrès conceptuels et empiriques qu’a connus ce champ de recherche depuis son émergence et à la lumière du tournant apparu dans l’agenda de la neuroéconomie au cours de la dernière décennie. JEL Codes : A12, B41, C51, C81, C9, D03, D87. (shrink)