Cognitive scientists claim to have discovered a large number of cognitive biases, which have a tendency to mislead reasoners. Might cognitive scientists themselves be subject to the very biases they purport to discover? And how should this alter the way they evaluate their research as evidence for the existence of these biases? In this paper, we posit a new paradox (the ‘Self-Reflexive Bias Paradox’), which bears a striking resemblance to some classical logical paradoxes. Suppose that research R (...) appears to be good evidence for the existence of bias B, but if B exists, then R would have been subject to B. Thus, it seems sensible for the researcher to reject R as good evidence for the existence of B. However, rejecting R for this reason admits the existence of B. We examine four putative cognitive biases and criticisms of them, each of which seem to be subject to self-reflexivity. In two cases, we argue, paradox is avoidable. In the remaining two, we cannot find a way to avoid the paradox, which poses a practical obstacle to scientific inquiry and results in an intriguing theoretical quandary. (shrink)

Recent work in the behavioral sciences asserts that we are subject to a variety of cognitive biases. For example, we mourn losses more than we prize equivalently sized gains; we are more inclined to believe something if it matches our previous beliefs; and we even relate more warmly or coldly to others depending on whether the coffee cup we are holding is warm or cold. Drawing on this work, case law and legal scholarship have asserted that we have reason (...) to select legal norms, or revise existing norms, so as to eliminate the influence of these and other cognitive biases. -/- In this Article, I critically evaluate whether and when this reaction is warranted. I begin by contrasting predominantly descriptive definitions of bias, on which bias is merely deviation from a predictive model, with prescriptive definition of bias, on which biased conduct is conduct that actors ought not do. I then similarly contrast the behavioral-scientific concepts of statistical significance and effect size with the concept of significance required to justify legal conclusions. -/- With this apparatus in place, I go on to consider a variety of examples where legal commentators and decisionmakers have worried about the effects of cognitive bias on law. I argue that many of these cognitive biases (for example, our aversion to losses), while reflecting deviations from behavioral scientists’ models of human behavior, are not normatively objectionable and so give us no reason to revise our legal norms to eliminate their effect. Others (e.g., the effect of judges’ hunger on their decisionmaking), however, constitute biases under both descriptive and prescriptive definitions and therefore give us good reason to revise our legal norms. -/- I conclude by contrasting my conclusion — that evaluation of cognitive biases’ legal significance must explicitly evaluate the normative arguments for and against the model of decisionmaking in question on a case-by-case basis — with the arguments of influential scientists and legal commentators like Daniel Kahneman and John Mikhail, who treat cognitive heuristics and biases as more broadly desirable or objectionable. (shrink)

There are two problems with Cimpian & Salomon’s (C&S’s) claim that an innate inherence heuristic is part of our cognitive makeup. First, some of their examples of inherent features do not seem to accord with the authors’ own definition of inherence. Second, rather than posit an inherence heuristic to explain why humans rely more heavily on inherent features, it may be more parsimonious to do so on the basis of aspects of the world itself and our relationship to it.

In this dissertation, I construct scientifically and practically adequate moral analogs of cognitive heuristics and biases. Cognitive heuristics are reasoning “shortcuts” that are efficient but flawed. Such flaws yield systematic judgment errors—i.e., cognitive biases. For example, the availability heuristic infers an event’s probability by seeing how easy it is to recall similar events. Since dramatic events, such as airplane crashes, are disproportionately easy to recall, this heuristic explains systematic overestimations of their probability (availability bias). The research program (...) on cognitive heuristics and biases (e.g., Daniel Kahneman’s work) has been scientifically successful and has yielded useful error-prevention techniques—i.e., cognitive debiasing. I attempt to apply this framework to moral reasoning to yield moral heuristics and biases. For instance, a moral bias of unjustified differences in the treatment of particular animal species might be partially explained by a moral heuristic that dubiously infers animals’ moral status from their aesthetic features. While the basis for identifying judgments as cognitive errors is often unassailable (e.g., per violating laws of logic), identifying moral errors seemingly requires appealing to moral truth, which, I argue, is problematic within science. Such appeals can be avoided by repackaging moral theories as mere “standards-of-interest” (a la non-normative metrics of purportedly right-making features/properties). However, standards-of-interest do not provide authority, which is needed for effective debiasing. Nevertheless, since each person deems their own subjective morality authoritative, subjective morality (qua standard-of-interest and not moral subjectivism) satisfies both scientific and practical concerns. As such, (idealized) subjective morality grounds a moral analog of cognitive biases—namely, subjective moral biases (e.g., committed anti-racists unconsciously discriminating). I also argue that "cognitive heuristic" is defined by its contrast with rationality. Consequently, heuristics explain biases, which are also so defined. However, such contrasting with rationality is causally irrelevant to cognition. This frustrates the presumed usefulness of the kind, heuristic, in causal explanation. As such, in the moral case, I jettison the role of causal explanation and tailor categories solely for contrastive explanation. As such, “moral heuristic” is replaced with "subjective moral fallacy," which is defined by its contrast with subjective morality and explains subjective moral biases. The resultant subjective moral biases and fallacies framework can undergird future empirical research. (shrink)

My aim in this paper is to develop a unified solution to two paradoxes of bounded rationality. The first is the regress problem that incorporating cognitive bounds into models of rational decisionmaking generates a regress of higher-order decision problems. The second is the problem of rational irrationality: it sometimes seems rational for bounded agents to act irrationally on the basis of rational deliberation. I review two strategies which have been brought to bear on these problems: the way of weakening (...) which responds by weakening rational norms, and the way of indirection which responds by letting the rationality of behavior be determined by the rationality of the deliberative processes which produced it. Then I propose and defend a third way to confront the paradoxes: the way of level separation. (shrink)

In the philosophy of science, it is a common proposal that values are illegitimate in science and should be counteracted whenever they drive inquiry to the confirmation of predetermined conclusions. Drawing on recent cognitive scientific research on human reasoning and confirmation bias, I argue that this view should be rejected. Advocates of it have overlooked that values that drive inquiry to the confirmation of predetermined conclusions can contribute to the reliability of scientific inquiry at the group level (...) even when they negatively affect an individual’s cognition. This casts doubt on the proposal that such values should always be illegitimate in science. It also suggests that advocates of that proposal assume a narrow, individualistic account of science that threatens to undermine their own project of ensuring reliable belief formation in science. (shrink)

This work aims to contribute to the explanation of cognitive capacities that are essential to human intelligence: commonsense and situation holism. The attempt to explain them within the field of cognitive sciences raises a foundational challenge. How can human cognition distinguish what’s relevant and what’s not in an open-ended set of contexts? The challenge is characterized by a circularity. Potential solutions end up relying on the very capacity that they should be explaining, i.e. the sensitivity to what’s contextually (...) relevant. The argument here developed is an attempt to get out of this circularity. It is grounded on a bi-dimensional analysis of the problem. The first one is representational and is about how cognitive knowledge on what’s relevant can be stored. This dimension is related to the frame problem from artificial intelligence. I claim that this representational aspect of the issue can be neutralized by abandoning language-like representational schemes and sticking to a plurality of structural ones. They allow representational states to play a clear and non-trivial explanatory role while enabling a kind of representational productivity that is not bothered by the frame problem. The second dimension is the inferential one. It encompasses our relevance-sensitive inferential productivity, i.e. our capacity to efficiently infer what’s relevant in indefinitely many contexts, including ones we’ve never faced before. I argue that such relevance sensitivity cannot be neither innate, for innate mechanisms result in the aforementioned circularity, nor learned through innate mechanisms, for learning processes themselves rely on relevance sensitivity. The suggested alternative is that relevance sensitivity is a cognitive gadget. A kind of mental mechanism that is culturally, rather than genetically, inherited. This possibility is rendered plausible within Cecilia Heyes’ “cognitive gadgets” framework. She shows how developmental tweaks and biases culturally established can participate in the constitution of cognitive mechanisms. Thus, cultural elements can participate in human cognition not only as information sources, but also in the form of tweaks that bias the processing of that information towards what’s culturally established as contextually relevant. (shrink)

Some recent work in philosophy of religion addresses what can be called the “axiological question,” i.e., regardless of whether God exists, would it be good or bad if God exists? Would the existence of God make the world a better or a worse place? Call the view that the existence of God would make the world a better place “Pro-Theism.” We argue that Pro-Theism is not implausible, and moreover, many Theists, at least, (often implicitly) think that it is true. That (...) is, many Theists think that various good outcomes would arise if Theism is true. We then discuss work in cognitive science concerning human cognitive bias, before discussing two noteworthy attempts to show that at least some religious beliefs arise because of cognitive bias: Hume’s, and Draper’s and Nichols’s. We then argue that, as a result of certain cognitive biases that result when good outcomes might be at stake, Pro-Theism causes many Theists to inflate the epistemic probability that God exists, and as a result, Theists should lower the probability they assign to God’s existence. Finally, based our arguments, we develop a novel objection to Pascal’s wager. (shrink)

Nicholas Shea offers Varitel Semantics as a naturalistic account of mental content. I argue that the account secures determinate content only by appeal to pragmatic considerations, and so it fails to respect naturalism. But that is fine, because representational content is not, strictly speaking, necessary for explanation in cognitive science. Even in Shea’s own account, content serves only a variety of heuristic functions.

My basic research question – well beyond the scope of this book – is what the relationships between cognitive processes and cultural structures and practices are. Here, I get closer to answering this question in the following five steps: (1) I present cognitive ecology as a research tradition in cognitive science, characteristic of the approaches to wide cognition, i.e., embodied, embedded, extended, ecological psychology, enactivism, etc. (2) I distinguish two dimensions of the distributed cognition approach: as (...) a theoretical framework and as a task model, focusing on the former. This distinction has so far eluded cognitive science theorists, and this approach has not been sufficiently analysed as a potential theory of cognitive science in general and the basis for its integration, being reduced to the dimension of the task model. (3) I discuss approaches in research on interactions in distributed cognitive systems, focusing more on the notion of external representations, and mostly on the notion of affordance. When assessing the potential of the latter, I look for consistency in what is crucial for understanding the interactions, between ecological psychology and design research. (4) I analyze the up to now underestimated potential of the distributed cognition approach in the dispute over the bounds of cognitive processes. (5) I identify and assess the analogies between the distributed cognition approach and the neo-mechanistic model of explanation that has become popular in cognitive science, and indicate possible benefits for the integration of the latter. As one can see, I am not trying to fully answer the question about the relationship between cognition and culture, but rather assess to what extent cognitive science in its current form is capable of. (shrink)

I discuss whether there are some lessons for philosophical inquiry over the nature of simulation to be learnt from the practical methodology of reengineering. I will argue that reengineering serves a similar purpose as simulations in theoretical science such as computational neuroscience or neurorobotics, and that the procedures and heuristics of reengineering help to develop solutions to outstanding problems of simulation.

John Bickle recently proposed a metascientific reading of certain neuroscientific practices related to phenomena traditionally studied by psychology. According to this view, the dominant explanatory proceeding in neuroscience is to apply empirical reductions to explain psychological phenomena in cellular and molecular terms, relegating the role of psychology to a mere heuristic, without explanatory power. Thus, according to the strength of the conclusions reached by this method, it puts in check the value of psychological functional explanations. In this work, we seek (...) to reformulate some of these challenging proposals in philosophy of neuroscience. To this end, the main weaknesses of Bickle's proposal will be shown. Also, here will put into perspective some (reductionist, eliminativists?) features of ruthless reductionism, showing that this model maybe represent only a reading of the pragmatic use of certain methods in neuroscience, rather than a statement of principles generalizable to all cognitive science. (shrink)

Many scientists routinely generalize from study samples to larger populations. It is commonly assumed that this cognitive process of scientific induction is a voluntary inference in which researchers assess the generalizability of their data and then draw conclusions accordingly. We challenge this view and argue for a novel account. The account describes scientific induction as involving by default a generalization bias that operates automatically and frequently leads researchers to unintentionally generalize their findings without sufficient evidence. The result is unwarranted, (...) overgeneralized conclusions. We support this account of scientific induction by integrating a range of disparate findings from across the cognitive sciences that have until now not been connected to research on the nature of scientific induction. The view that scientific induction involves by default a generalization bias calls for a revision of the current thinking about scientific induction and highlights an overlooked cause of the replication crisis in the sciences. Commonly proposed interventions to tackle scientific overgeneralizations that may feed into this crisis need to be supplemented with cognitive debiasing strategies against generalization bias to most effectively improve science. (shrink)

In the philosophical literature, self-deception is mainly approached through the analysis of paradoxes. Yet, it is agreed that self-deception is motivated by protection from distress. In this paper, we argue, with the help of findings from cognitive neuroscience and psychology, that self-deception is a type of affective coping. First, we criticize the main solutions to the paradoxes of self-deception. We then present a new approach to self-deception. Self-deception, we argue, involves three appraisals of the distressing evidence: (a) appraisal of (...) the strength of evidence as uncertain, (b) low coping potential and (c) negative anticipation along the lines of Damasio’s somatic marker hypothesis. At the same time, desire impacts the treatment of flattering evidence via dopamine. Our main proposal is that self-deception involves emotional mechanisms provoking a preference for immediate reward despite possible long-term negative repercussions. In the last part, we use this emotional model to revisit the philosophical paradoxes. (shrink)

In this paper, I argue that embodied cognition, like many other research traditions in cognitive science, offers mostly fallible research heuristics rather than grand principles true of all cognitive processing. To illustrate this claim, I discuss Aizawa’s rebuttal of embodied and enactive accounts of vision. While Aizawa’s argument is sound against a strong reading of the enactive account, it does not undermine the way embodied cognition proceeds, because the claim he attacks is one of fallible heuristics. These (...) heuristics may be helpful in developing models of cognition in an interdisciplinary fashion. I briefly discuss the issue of whether this fallibility actually makes embodied cognition vulnerable to charges of being untestable or non-scientific. I also stress that the historical approach to this research tradition suggests that embodied cognition is not poised to become a grand unified theory of cognition. (shrink)

Commonsense reasoning is one of the main open problems in the field of Artificial Intelligence (AI) while, on the other hand, seems to be a very intuitive and default reasoning mode in humans and other animals. In this talk, we discuss the different paradigms that have been developed in AI and Computational Cognitive Science to deal with this problem (ranging from logic-based methods, to diagrammatic-based ones). In particular, we discuss - via two different case studies concerning commonsense categorization (...) and knowledge invention tasks - how cognitively inspired heuristics can help (both in terms of efficiency and efficacy) in the realization of intelligent artificial systems able to reason in a human-like fashion, with results comparable to human-level performances. (shrink)

The sciences occasionally generate discoveries that undermine their own assumptions. Two such discoveries are characterized here: the discovery of apophenia by cognitive psychology and the discovery that physical systems cannot be locally bounded within quantum theory. It is shown that such discoveries have a common structure and that this common structure is an instance of Priest’s well-known Inclosure Schema. This demonstrates that science itself is dialetheic: it generates limit paradoxes. How science proceeds despite this fact is briefly (...) discussed, as is the connection between our results and the realism-antirealism debate. We conclude by suggesting a position of epistemic modesty. (shrink)

As we have seen in the transition form Part I to Part II of this book, the inductive riskiness of doxastic methods applied in testimonial uptake or prescribed as exemplary of religious faith, helpfully operationalizes the broader social scientific, philosophical, moral, and theological interest that people may have with problems of religious luck. Accordingly, we will now speak less about luck, but more about the manner in which highly risky cognitive strategies are correlated with psychological studies of bias studies (...) and human cognitive ecology. Chapter Four is concerned with connections between psychological study of biases and heuristics, and the comparative study of fundamentalism. The first section looks at work by psychologists and philosophers on our bias blind spot. Later sections ask, ‘In what ways might biases and heuristics play a special role in aiding our understanding of, and response to, fundamentalist orientation?’. The judgments we make in ignorance of our own biases Montaigne calls our importunate presumptions, and he suggests a host of practical factors that make them appealing. Montaigne, as I discuss in the first section, associates many of our errors with one or another kind of presumption, often about our similarity or differences from others, or from God. Our obvious psychographic diversity, and the polemical ground dynamics involved in our ‘culture wars’ are compounded on the agential side by the invisibility of our biases to ourselves. A number of person and social biases are described that plausibly affect all of our beliefs in domains of controversial views, religious views included. The second section continues to study of how etiological symmetry (similar patterns of belief-uptake) gives rise to religious contrariety (diverse narratives and theologies) in testimonial faith traditions, and what the implications of this are for philosophy of religion, generally, and for an improved comparative study of fundamentalism, in particular. Utilizing the work of philosophers such as Rachel Fraser and psychologists such as Emily Pronin and her co-authors, I offer a four-step genealogical account for how etiological symmetry so easily gives rise to religious contrariety. This account begins with the narrative nature of testimony in the Abrahamic family of religions, and how narrative content confounds our “source monitoring.” My genealogy also introduces what I term biased-closure inferences (BCI) as one of the key enablers of religious exclusivism and absolutism. These are the seemingly ‘logical’ but actually very self-serving inferences people often make, inferences from their own belief being true, to any belief contrary to it being false. Those who claim unique truth, epistemic access, and/or virtue and religious value for the home religion are no exception to the broad pertinence of bias studies across domains of controversial view. The proximate causes of belief are all that we can study, and in these there may be significant etiological symmetries. Yet those groups themselves, especially to the extent that they are exclusivist, are tunnel-visioned on claims of doctrinal uniqueness: on content differences of a theological sort. Comparative philosophy is met with the puzzlement that symmetric or essentially similar doxastic strategies should give rise not just to cognitive diversity, but to what we can call polarized or polemical contrariety, contrariety of a kind where each view adamantly rejects all others. Arguably, the more that theologies offer explanations of a counter-inductive sort, or profess counter-inductive thinking as exemplary of faith, the better evidential ground there for inferring that bias involved in the acquisition or maintenance of beliefs. This provides more substance to the question of when censure, and etiological challenges to faith-based beliefs are philosophically well-motivated. (shrink)

What is the status of research on implicit bias? In light of meta‐analyses revealing ostensibly low average correlations between implicit measures and behavior, as well as various other psychometric concerns, criticism has become ubiquitous. We argue that while there are significant challenges and ample room for improvement, research on the causes, psychological properties, and behavioral effects of implicit bias continues to deserve a role in the sciences of the mind as well as in efforts to understand, and ultimately combat, discrimination (...) and inequality. (shrink)

This dissertation argues that cognition is a kind of natural agency. Natural agency is the capacity that certain systems have to act in accordance with their own norms. Natural agents are systems that bias their repertoires in response to affordances in the pursuit of their goals. Cognition is a special mode of this general phenomenon. Cognitive systems are agents that have the additional capacity to actively take their worlds to be certain ways, regardless of whether the world is really (...) that way. In this way, cognitive systems are desituated. Desituatedness is the root of specifically cognitive capacities for representation and abstraction. There are two main reasons why this view needs defending. First, natural agency is typically viewed as incompatible with natural science because it is committed to a teleological mode of explanation. Second, cognition is typically held to be categorically distinct from natural agency. This dissertation argues against both of these views. It argues against the incompatibility of agency and natural science by demonstrating that systems biology, general systems theory, and sciences that deal with complex systems have typically underappreciated conceptual and theoretical resources for grounding agency in the causal structure of the world. These conceptual resources do not, however, reduce agency to systems theory because the normativity inherent in agency demands descriptive resources beyond those of even the most sophisticated systems theory. It argues against the categorical difference between natural agency and cognition by pointing out that separating cognition from a richer web of situated, ecologically embedded relations between the agent and the world generates the frame problem, which is an insuperable obstacle to making cognition that is sufficiently responsive to the complexity of the world. Rooting cognition in natural agency is a more robust empirical bet for theorizing cognition and artificial intelligence. (shrink)

Relativity Theory by Albert Einstein has been so far littleconsidered by cognitive scientists, notwithstanding its undisputedscientific and philosophical moment. Unfortunately, we don't have adiary or notebook as cognitively useful as Faraday's. But physicshistorians and philosophers have done a great job that is relevant bothfor the study of the scientist's reasoning and the philosophy ofscience. I will try here to highlight the fertility of a `triangulation'using cognitive psychology, history of science and philosophy of sciencein starting answering a clearly (...) very complex question:why did Einstein discover Relativity Theory? Here we arenot much concerned with the unending question of precisely whatEinstein discovered, that still remains unanswered, for we have noconsensus over the exact nature of the theory's foundations. We are mainly interested in starting to answer the`how question', and especially the following sub-question: what were his goals and strategies in hissearch? I will base my argument on fundamental publications ofEinstein, aiming at pointing out a theory-specific heuristic, settingboth a goal and a strategy: covariance/invariance.The result has significance in theory formation in science, especiallyin concept and model building. It also raises other questions that gobeyond the aim of this paper: why was he so confident in suchheuristic? Why didn't many other scientists use it? Where did he keep? such a heuristic? Do we have any other examples ofsimilar heuristic search in other scientific problemsolving? (shrink)

Advancement in cognitive science depends, in part, on doing some occasional ‘theoretical housekeeping’. We highlight some conceptual confusions lurking in an important attempt at explaining the human capacity for rational or coherent thought: Thagard & Verbeurgt’s computational-level model of humans’ capacity for making reasonable and truth-conducive abductive inferences (1998; Thagard, 2000). Thagard & Verbeurgt’s model assumes that humans make such inferences by computing a coherence function (f_coh), which takes as input representation networks and their pair-wise constraints and gives (...) as output a partition into accepted (A) and rejected (R) elements that maximizes the weight of satisfied constraints. We argue that their proposal gives rise to at least three difficult problems. (shrink)

Explanatory pluralism holds that the sorts of comprehensive theoretical and ontological economies, which microreductionists and New Wave reductionists envision and which antireductionists fear, offer misleading views of both scientific practice and scientific progress. Both advocates and foes of employing reductionist strategies at the interface of psychology and neuroscience have overplayed the alleged economies that interlevel connections (including identities) justify while overlooking their fundamental role in promoting scientific research. A brief review of research on visual processing provides support for the explanatory (...) pluralist=s general model of cross-scientific relations and discloses the valuable heuristic role hypothetical identities play in cross-scientific research. That model also supplies grounds for hesitation about the correlation objection to the psycho-physical identity theory and complaints about an explanatory gap in physicalist accounts of consciousness. These takes on psycho-neural connections miss both the sorts of considerations that motivate hypothetical identities in science and their fundamental contribution to progressive research. Thus, their focus on the contributions of research at multiple levels of analysis does not bar explanatory pluralists from considering heuristic identity theory (HIT). Arguably, it encourages it. (shrink)

The concept of bias is pervasive in both popular discourse and empirical theorizing within philosophy, cognitive science, and artificial intelligence. This widespread application threatens to render the concept too heterogeneous and unwieldy for systematic investigation. This article explores recent philosophical literature attempting to identify a single theoretical category—termed ‘bias’—that could be unified across different contexts. To achieve this aim, the article provides a comprehensive review of theories of bias that are significant in the fields of philosophy of mind, (...) cognitive science, machine learning, and epistemology. It focuses on key examples such as perceptual bias, implicit bias, explicit bias, and algorithmic bias, scrutinizing their similarities and differences. Although these explorations may not conclusively establish the existence of a natural theoretical kind, pursuing the possibility offers valuable insights into how bias is conceptualized and deployed across diverse domains, thus deepening our understanding of its complexities across a wide range of cognitive and computational processes. (shrink)

In this paper, an account of theoretical integration in cognitive (neuro)science from the mechanistic perspective is defended. It is argued that mechanistic patterns of integration can be better understood in terms of constraints on representations of mechanisms, not just on the space of possible mechanisms, as previous accounts of integration had it. This way, integration can be analyzed in more detail with the help of constraintsatisfaction account of coherence between scientific representations. In particular, the account has resources to (...) talk of idealizations and research heuristics employed by researchers to combine separate results and theoretical frameworks. The account is subsequently applied to an example of successful integration in the research on hippocampus and memory, and to a failure of integration in the research on mirror neurons as purportedly explanatory of sexual orientation. (shrink)

The current debates in social sciences show that the paradox of observing—the embeddedness of observer in the process of observing—is at the heart of the controversy about their cognitive status and future. Although the problem of observing has been addressed in numerous theoretical perspectives—some of which (Habermas, Leydesdorff, Maturana, and Luhmann) are examined in this article—the prospects for resolving this paradox remain problematic. Locating a point that allows reflection on the process of autopoiesis in general, not just the operation (...) of a particular autopoietic system, may be one condition for resolving this paradox. Such point will offer reflection on all autopoietic systems, including the observer. The dynamic balance between equilibrium and disequilibrium is the mechanism which regulates the process of autopoiesis. Since the function of regulation is essentially a reflective function, this equilibrium between equilibrium and disequilibrium, which can be identified with the concept of homeorhesis introduced by Conrad Waddington, may offer a possibility to reflect on the process of observing. (shrink)

Following Marr’s famous three-level distinction between explanations in cognitive science, it is often accepted that focus on modeling cognitive tasks should be on the computational level rather than the algorithmic level. When it comes to mathematical problem solving, this approach suggests that the complexity of the task of solving a problem can be characterized by the computational complexity of that problem. In this paper, I argue that human cognizers use heuristic and didactic tools and thus engage in (...) cognitive processes that make their problem solving algorithms computationally suboptimal, in contrast with the optimal algorithms studied in the computational approach. Therefore, in order to accurately model the human cognitive tasks involved in mathematical problem solving, we need to expand our methodology to also include aspects relevant to the algorithmic level. This allows us to study algorithms that are cognitively optimal for human problem solvers. Since problem solving methods are not universal, I propose that they should be studied in the framework of enculturation, which can explain the expected cultural variance in the humanly optimal algorithms. While mathematical problem solving is used as the case study, the considerations in this paper concern modeling of cognitive tasks in general. (shrink)

In this article, an account of the architecture of the cognitive contamination system is offered, according to which the contamination system can generate contamination represen- tations in circumstances that do not satisfy the norms of contamination, including in cases of mere visual contact with disgusting objects. It is argued that this architecture is important for explaining the content, logic, distribution, and persistence of maternal impression beliefs – according to which fetal defects are caused by the pregnant mother’s experiences and (...) actions – which in turn provide important evidence of the architecture of the cognitive contamination system. (shrink)

Many cognitive scientists, having discovered that some computational-level characterization f of a cognitive capacity φ is intractable, invoke heuristics as algorithmic-level explanations of how cognizers compute f. We argue that such explanations are actually dysfunctional, and rebut five possible objections. We then propose computational-level theory revision as a principled and workable alternative.

Like any social science, management and organization sits astride two literary and epistemic disciplines; the empirical and the conceptual. I argue that emphasizing the former to the detriment of the latter, as is often the case in management and organization research, creates a conceptual blindness that compromises progress in the field. I show how adopting a more philosophically attuned methodology buttresses the conceptual tools of management and organization research via deduction, induction, normative grounding, and overcoming the illusion of unanimity.

This interdisciplinary study explores the philosophical evolution of John Keats' poetics, integrating insights from philosophy, cognitive science, psychology, and literary hermeneutics to unravel the complex interplay between aesthetics and epistemology in Romantic literature. The research traces Keats' intellectual journey from solipsistic idealism to naturalistic humanism, analyzing his conceptualization of truth, beauty, and imagination through the lens of both Continental philosophy and analytical logic.

Discussions in social psychology overlook an important way in which biases can be encoded in conceptual representations. Most accounts of implicit bias focus on ‘mere associations’ between features and representations of social groups. While some have argued that some implicit biases must have a richer conceptual structure, they have said little about what this richer structure might be. To address this lacuna, we build on research in philosophy and cognitive science demonstrating that concepts represent dependency relations between features. (...) These relations, in turn, determine the centrality of a feature f for a concept C: roughly, the more features of C depend on f, the more central f is for C. In this paper, we argue that the dependency networks that link features can encode significant biases. To support this claim, we present a series of studies that show how a particular brilliance-gender bias is encoded in the dependency networks which are part of the concepts of female and male academics. We also argue that biases which are encoded in dependency networks have unique implications for social cognition. (shrink)

I develop an epistemic focal bias account of certain patterns of judgments about knowledge ascriptions by integrating it with a general dual process framework of human cognition. According to the focal bias account, judgments about knowledge ascriptions are generally reliable but systematically fallible because the cognitive processes that generate them are affected by what is in focus. I begin by considering some puzzling patters of judgments about knowledge ascriptions and sketch how a basic focal bias account seeks to account (...) for them. In doing so, I argue that the basic focal bias account should be integrated in a more general framework of human cognition. Consequently, I present some central aspects of a prominent general dual process theory of human cognition and discuss how focal bias may figure at various levels of processing. On the basis of this discussion, I attempt to categorize the relevant judgments about knowledge ascriptions. Given this categorization, I argue that the basic epistemic focal bias account of certain contrast effects and salient alternatives effects can be plausibly integrated with the dual process framework. Likewise, I try to explain the absence of strong intuitions in cases of far-fetched salient alternatives. As a manner of conclusion, I consider some methodological issues concerning the relationship between cognitive psychology, experimental data and epistemological theorizing. -/- . (shrink)

Examining imagination, 4E cognition and the arts together expands our understanding of them all. 4E cognition is a framework that comprises the theories separately known as embodied, enactive, embedded, and extended cognition. This paper draws on research in cognitive science (including 4E and recent predictive processing approaches), ideas in phenomenology, and artworks from The Extended Mind exhibition (2019–20). The artworks offer diverse reflections on 4E cognition, as well as revealing personal, political and ethical benefits and issues predicated on (...) a 4E cognition perspective. This approach further provides a way of defending the epistemic value of the imagination and of unpacking the four key puzzles associated with its relationship with the arts regarding its production of emotional response, imaginative resistance, and moral persuasion, and the paradox of our attraction towards horror and tragedy. The arts are a valuable mode of inquiry into the nature of cognition and neglect of their relevance negatively impacts understandings of the mind. (shrink)

Accounts of arguments from expert opinion take it for granted that expert judgments count as (defeasible) evidence for propositions, and so an argument that proceeds from premises about what an expert judges to a conclusion that the expert is probably right is a strong argument. In Mizrahi (2013), I consider a potential justification for this assumption, namely, that expert judgments are significantly more likely to be true than novice judgments, and find it wanting because of empirical evidence suggesting that expert (...) judgments under uncertainty are not significantly more likely to be true than novice judgments or even chance. In this paper, I consider another potential justification for this assumption, namely, that expert judgments are not influenced by the cognitive biases novice judgments are influenced by, and find it wanting, too, because of empirical evidence suggesting that experts are vulnerable to pretty much the same cognitive biases that novices are vulnerable to. If this is correct, then the basic assumption at the core of accounts of arguments from expert opinion, namely, that expert judgments count as (defeasible) evidence for propositions, remains unjustified. (shrink)

The central concept of this edited volume is "blended cognition", the natural skill of human beings for combining constantly different heuristics during their several task-solving activities. Something that was sometimes observed like a problem as “bad reasoning”, is now the central key for the understanding of the richness, adaptability and creativity of human cognition. The topic of this book connects in a significant way with the disciplines of psychology, neurology, anthropology, philosophy, logics, engineering, logics, and AI. In a nutshell: understanding (...) better humans for designing better machines. It contains a Preface by the editors and 12 chapters. (shrink)

In this paper, I argue that visual attention is cognitively penetrated by intention. I present a detailed account of attention and its neural basis, drawing on a recent computational model of neural modulation during attention: divisive normalization. I argue that intention shifts computations during divisive normalization. The epistemic consequences of attentional bias are discussed.

Human behavior is an underlying cause for many of the ecological crises faced in the 21st century, and there is no escaping from the fact that widespread behavior change is necessary for socio-ecological systems to take a sustainable turn. Whilst making people and communities behave sustainably is a fundamental objective for environmental policy, behavior change interventions and policies are often implemented from a very limited non-systemic perspective. Environmental policy-makers and psychologists alike often reduce cognition ‘to the brain,’ focusing only to (...) a minor extent on how everyday environments systemically afford pro-environmental behavior. Symptomatic of this are the widely prevalent attitude–action, value–action or knowledge–action gaps, understood in this paper as the gulfs lying between sustainable thinking and behavior due to lack of affordances. I suggest that by adopting a theory of affordances as a guiding heuristic, environmental policy-makers are better equipped to promote policies that translate sustainable thinking into sustainable behavior, often self-reinforcingly, and have better conceptual tools to nudge our socio–ecological system toward a sustainable turn. Affordance theory, which studies the relations between abilities to perceive and act and environmental features, is shown to provide a systemic framework for analyzing environmental policies and the ecology of human behavior. This facilitates the location and activation of leverage points for systemic policy interventions, which can help socio–ecological systems to learn to adapt to more sustainable habits. Affordance theory is presented to be applicable and pertinent to technically all nested levels of socio–ecological systems from the studies of sustainable objects and households to sustainable urban environments, making it an immensely versatile conceptual policy tool. Finally, affordance theory is also discussed from a participatory perspective. Increasing the fit between local thinking and external behavior possibilities entails a deep understanding of tacit and explicit attitudes, values, knowledge as well as physical and social environments, best gained via inclusive and polycentric policy approaches. (shrink)

While agreeing with the main conclusion of Dominic Wilkinson and colleagues (Wilkinson, Butcherine, and Savulescu 2019), namely, that there is no moral difference between treatment withholding and withdrawal as such, we wish to criticize their approach on the basis that it treats the widespread acceptance of withdrawal aversion (WA) as a cognitive bias. Wilkinson and colleagues understand WA as “a nonrational preference for withholding (WH) treatment over withdrawal (WD) of treatment” (22). They treat WA as a manifestation of loss (...) aversion and refer to Kahneman and colleagues (1991), which defined this effect as follows: “the disutility of giving up an object is greater that the utility associated with acquiring it” (194). In a previous work, Wilkinson and Savulescu understood nonequivalence between treatment withholding and withdrawal as a reflection of slightly different, although related, phenomena: status quo bias or omission bias (Wilkinson and Savulescu 2012, 130–131). In neither of these two papers do they describe precisely the relation between these well-known psychological effects and WA, nor do they explain why they treat these effects as examples of nonrational preferences, despite the fact that these issues have been the subject of wide-ranging discussions on the intersection of psychology, economy, and philosophy. (shrink)

This monograph is an in-depth and engaging discourse on the deeply cognitive roots of human scientific quest. The process of making scientific inferences is continuous with the day-to-day inferential activity of individuals, and is predominantly inductive in nature. Inductive inference, which is fallible, exploratory, and open-ended, is of essential relevance in our incessant efforts at making sense of a complex and uncertain world around us, and covers a vast range of cognitive activities, among which scientific exploration constitutes the (...) pinnacle. Inductive inference has a personal aspect to it, being rooted in the cognitive unconscious of individuals, which has recently been found to be of paramount importance in a wide range of complex cognitive processes. One other major aspect of the process of inference making, including the making of scientific inferences, is the role of a vast web of beliefs lodged in the human mind, as also of a huge repertoire of heuristics, that constitute an important component of ‘unconscious intelligence’. Finally, human cognitive activity is dependent in a large measure on emotions and affects, that operate mostly at an unconscious level. Of special importance in scientific inferential activity is the process of hypothesis making, which is examined in this book, along with the above aspects of inductive inference, at considerable depth. The book focuses on the inadequacy of the viewpoint of naive realism in understanding the contextual nature of scientific theories, where a cumulative progress towards an ultimate truth about Nature appears to be too simplistic a generalization. It poses a critique to the commonly perceived image of science which is seen as the last word in logic and objectivity, the latter in the double sense of being independent of individual psychological propensities and, at the same time, approaching a correct understanding of the workings of a mind-independent nature. Adopting the naturalist point of view, it examines the essential tension between the cognitive endeavours of individuals and scientific communities, immersed in belief systems and cultures, on the one hand, and the engagement with a mind-independent reality on the other. In the end, science emerges as an interpretation of nature, which is perceived by us only contextually, as successively emerging cross-sections of limited scope and extent. Successive waves of theory building in science appear as episodic and kaleidoscopic changes in perspective as certain in-built borders are crossed, rather than as a cumulative progress towards some ultimate truth. While written in an informal and conversational style, the book raises a number of deep and intriguing questions located at the interface of cognitive psychology and philosophy of science, meant for both the general lay reader and the specialist. Of particular interest is the way it explores the role of belief (aided by emotions and affects) in making the process of inductive inference possible since belief is a subtle though all-pervasive cognitive factor not adequately investigated in the current literature. (shrink)

For some reason, participants hold agents more responsible for their actions when a situation is described concretely than when the situation is described abstractly. We present examples of this phenomenon, and survey some attempts to explain it. We divide these attempts into two classes: affective theories and cognitive theories. After criticizing both types of theories we advance our novel hypothesis: that people believe that whenever a norm is violated, someone is responsible for it. This belief, along with the familiar (...) workings of cognitive dissonance theory, is enough to not only explain all of the abstract/concrete paradoxes, but also explains seemingly unrelated effects, like the anthropomorphization of malfunctioning inanimate objects. (shrink)

The "myside bias'' in evaluating arguments is an empirically well-confirmed phenomenon that consists of overweighting arguments that endorse one's beliefs or attack alternative beliefs while underweighting arguments that attack one's beliefs or defend alternative beliefs. This paper makes two contributions: First, it proposes a probabilistic model that adequately captures three salient features of myside bias in argument evaluation. Second, it provides a Bayesian justification of this model, thus showing that myside bias has a rational Bayesian explanation under certain conditions.

The following aesthetic discussion examines in a philosophical-scientific way the relationship between computation and artistic creativity. Currently, there is a criticism about the possible artistic creativity that an algorithm could have. Supporting the above, the term computer-generated art (CG-Art) defined by Margaret Boden would seem to have no exponents yet. Moreover, it has been pointed out that, rather than a matter of primitive technological development, CG-Art would have in its very foundations the inability to exist. This, because art is considered (...) as one of the most unique and exclusive human manifestations of our species. On the contrary, I propose that the denial of CG-Art has an anthropocentric bias. For this, I use the recent studies that, from the cognitive sciences, have been carried out on artistic creativity. In this way, I intend to convince the reader that behind the denial of the creative artistic capacity to the machines, a negationist mysticism of the current scientific advances necessarily lies. (shrink)

I argue that bounded agents face a systematic accuracy-coherence tradeoff in cognition. Agents must choose whether to structure their cognition in ways likely to promote coherence or accuracy. I illustrate the accuracy-coherence tradeoff by showing how it arises out of at least two component tradeoffs: a coherence-complexity tradeoff between coherence and cognitive complexity, and a coherence-variety tradeoff between coherence and strategic variety. These tradeoffs give rise to an accuracy-coherence tradeoff because privileging coherence over complexity or strategic variety often leads (...) to a corresponding reduction in accuracy. I conclude with a discussion of two normative consequences for the study of bounded rationality: the importance of procedural rationality and the role of coherence in theories of bounded rationality. (shrink)

Children acquire complex concepts like DOG earlier than simple concepts like BROWN, even though our best neuroscientific theories suggest that learning the former is harder than learning the latter and, thus, should take more time (Werning 2010). This is the Complex- First Paradox. We present a novel solution to the Complex-First Paradox. Our solution builds on a generalization of Xu and Tenenbaum’s (2007) Bayesian model of word learning. By focusing on a rational theory of concept learning, we show that it (...) is easier to infer the meaning of complex concepts than that of simple concepts. (shrink)

Cognitive modules are internal mental structures. Some theorists and empirical researchers hypothesise that the human mind is either partially or massively comprised of structures that are modular in nature. Is the massive modularity of mind hypothesis a cogent view about the ontological nature of human mind or is it, rather, an effective/ineffective adaptationist discovery heuristic for generating predictively successful hypotheses about both heretofore unknown psychological traits and unknown properties of already identified psychological traits? Considering the inadequacies of the case (...) in favour of massive modularity as an ontological hypothesis, I suggest approaching and valuing massive modularity as an adaptationist discovery heuristic. (shrink)

Illusionism is the view that conscious experience is some sort of introspective illusion. According to illusionism, there is no conscious experience, but it merely seems like there is conscious experience. This would suggest that much phenomenological enquiry, including work on phenomenological psychopathology, rests on a mistake. Some philosophers have argued that illusionism is obviously false, because seeming is itself an experiential state, and so necessarily presupposes the reality of conscious experience. In response, the illusionist could suggest that the relevant sort (...) of seeming here is not an experiential state, but is a cognitive state, such as a judgement or a belief, which is fully amenable to a physical or functionalist analysis. Herein, I argue that this response is unsuccessful and fails to undermine the reality of conscious experience. Nonetheless, the response does raise the problem of how a judgement or belief about the character of a conscious experience, even if it is true, can be justified if the conscious experience has no causal role in the formation of the judgement or belief. This is not a new problem, but is a reiteration of an old problem that is known in the philosophy of mind literature as the paradox of phenomenal judgement. I consider how the paradox of phenomenal judgement can be resolved and how the judgement or belief about conscious experience can be justified with appeal to the notion of acquaintance. (shrink)

The cognitive sciences are facing questions of how to select from competing theories or develop those that suit their current needs. However, traditional accounts of theoretical virtues have not yet proven informative to theory development in these fields. We advance a pragmatic account by which theoretical virtues are heuristics we use to estimate a theory’s contribution to a field’s body of knowledge and the degree to which it increases that knowledge’s ability to solve problems in the field’s domain or (...) problem space. From this perspective, properties that are traditionally considered epistemic virtues, such as a theory’s fit to data or internal coherence, can be couched in terms of problem space coverage, and additional virtues come to light that reflect a theory’s alignment with problem-having agents and the context in a societally embedded scientific system. This approach helps us understand why the needs of different fields result in different kinds of theories and allows us to formulate the challenges facing cognitive science in terms that we hope will facilitate their resolution through further theoretical development. (shrink)

The theoretical heuristic of assuming distinct alleles (or genotypes) for alternative phenotypes is the foundation of the paradigm of evolutionary explanation we call the Modern Synthesis. In modeling the evolution of sociality, the heuristic has been to set altruism and selfishness as alternative phenotypes under distinct genotypes, which has been dubbed the “phenotypic gambit.” The prevalence of the altruistic genotype that is of lower evolutionary fitness relative to the alternative genotype for non-altruistic behavior in populations is the basis of the (...) “paradox of altruism.” I show in this article that the assumption of contrasting genotypes for altruism and selfishness in our “phenotypic gambit” is inconsistent with the empirical data when viewed in the light of today’s post-Mendelian understanding of gene expression. I demonstrate that however nuanced and sophisticated the models may have become today, they are still rooted in that fundamentally problematic assumption. I then offer a genetic conception of altruism that best fits the field data. (shrink)