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)

Invited Lecture at the SRM ACM Student Chapter, India, on Cognitive Heuristics for Commonsense Thinking and Reasoning in the next generation Artificial Intelligence. The lecture proposes a historical and technical overview of strategies for commonsense reasoning in AI.

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)

We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of the combination of prototypical concepts. The proposed logic relies on the logic of typicality ALC + TR, whose semantics is based on the notion of rational closure, as well as on the distributed semantics of probabilistic Description Logics, and is equipped with a cognitive heuristic used by humans for concept composition. We first extend the logic of typicality ALC + TR by typicality inclusions of (...) the form p :: T(C) v D, whose intuitive meaning is that “we believe with degree p about the fact that typical Cs are Ds”. As in the distributed semantics, we define different scenarios containing only some typicality inclusions, each one having a suitable probability. We then exploit such scenarios in order to ascribe typical properties to a concept C obtained as the combination of two prototypical concepts. We also show that reasoning in the proposed Description Logic is EXPTIME-complete as for the underlying standard Description Logic ALC. (shrink)

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)

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)

We argue that the interaction of biased media coverage and widespread employment of the recognition heuristic can produce epistemic injustices. First, we explain the recognition heuristic as studied by Gerd Gigerenzer and colleagues, highlighting how some of its components are largely external to, and outside the control of, the cognitive agent. We then connect the recognition heuristic with recent work on the hypotheses of embedded, extended, and scaffolded cognition, arguing that the recognition heuristic is best understood as an instance (...) of scaffolded cognition. In section three, we consider the double-edged sword of cognitive scaffolding. On the one hand, scaffolds can reduce the internal processing demands on cognitive agents while increasing their access to information. On the other hand, the use of scaffolding leaves cognitive agents increasingly vulnerable to forming false beliefs or failing to form beliefs at all about particular topics. With respect to the recognition heuristic, agents rely on third parties (such as the media) to report not just what’s true but also what’s important or valuable. This makes cognitive agents relying on these third parties vulnerable to two erroneous influences: 1) because they don’t recognize something, it isn’t important or valuable, and 2) because they do recognize something, it is important or valuable. Call the latter the Kardashian Inference and the former the Darfur Inference. In section four, we use Fricker’s (2007) concept of epistemic injustice to characterize the nature and harm of these false inferences, with special emphasis on the Darfur Inference. In section five, we use data-mining and an empirical study to show how Gigerenzer’s population estimation task is liable to produce Darfur Inferences. We conclude with some speculative remarks on more important Darfur Inferences, and how to avoid them by scaffolding better. One primary way to accomplish this it to shift the burden of embodying the virtue of epistemic justice from the hearer or consumer of media to the media themselves. (shrink)

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)

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)

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.

This paper evaluates the claim that it is possible to use nature’s variation in conjunction with retention and selection on the one hand, and the absence of ultimate groundedness of hypotheses generated by the human mind as it knows on the other hand, to discard the ascription of ultimate certainty to the rationality of human conjectures in the cognitive realm. This leads to an evaluation of the further assumption that successful hypotheses with specific applications, in other words heuristics, (...) seem to have a firm footing because they were useful in another context. I argue that usefulness evaluated through adaptation misconstrues the search for truth, and that it is possible to generate talk of randomness by neglecting aspects of a system’s insertion into a larger situation. The framing of the problem in terms of the elimination of unfit hypotheses is found to be unsatisfying. It is suggested that theories exist in a dimension where they can be kept alive rather than dying as phenotypes do. The proposal that the subconscious could suggest random variations is found to be a category mistake. A final appeal to phenomenology shows that this proposal is orphan in the history of epistemology, not in virtue of its being a remarkable find, but rather because it is ill-conceived. (shrink)

Timothy Williamson has defended the claim that the semantics of the indicative ‘if’ is given by the material conditional. Putative counterexamples can be handled by better understanding the role played in our assessment of indicatives by a fallible cognitive heuristic, called the Suppositional Procedure. Williamson’s Suppositional Conjecture has it that the Suppositional Procedure is humans’ primary way of prospectively assessing conditionals. This paper raises some doubts on the Suppositional Procedure and Conjecture.

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)

If A confirms H and B confirms H, it seems reasonable to infer that A&B confirms H. However, this inference is not valid; it is only a heuristic. I show that the level of confirmation A and B each give to H by itself implies nothing about the level of confirmation that A&B gives to H. Any combination of values is possible for P(H), P(H|A), P(H|B) and P(H|AB) is possible. Still, I show the heuristic leads from true premises to true (...) conclusions whenever A and B are statistically independent or correlated,which includes most situations where we evaluate evidence. There is risk, though, when one does not consider how A and B interact; one can miss anti-correlations that lead the heuristic to fail. The problem is exacerbated when groups of people are motivated to support a favored hypothesis. Each person finds evidence that confirms the hypothesis and contributes that evidence to the group’s discourse (e.g. through a climate change denial website). The temptation to focus solely on the number of individual pieces of evidence can lead people to ignore whether the evidence fits together. In combination with cognitive biases, this can lead to serious errors. (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 (...) class='Hi'>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)

This chapter argues that the only tenable unconscious inferences theories of cognitive achievement are ones that employ a theory internal technical notion of representation, but that once we give cash-value definitions of the relevant notions of representation and inference, there is little left of the ordinary notion of representation. We suggest that the real value of talk of unconscious inferences lies in (a) their heuristic utility in helping us to make fruitful predictions, such as about illusions, and (b) their (...) providing a high-level description of the functional organization of subpersonal faculties that makes clear how they equip an agent to navigate its environment and pursue its goals. (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)

In the present study it was shown that decision heuristics and confidence judgements play important roles in the building of preferences. Based on a dual-process account of thinking, the study compared people who did well versus poorly on a series of decision heuristics and overconfidence judgement tasks. The two groups were found to differ with regard to their information search behaviour in introduced multiattribute choice tasks. High performers on the judgemental tasks were less influenced in their decision processes (...) by numerical information format (probabilities vs. frequencies) compared to low performers. They also looked at more attributes and spent more time on the multiattribute choice tasks. The results reveal that performance on decision heuristics and overconfidence tasks has a bearing both on heuristic and analytic processes in multiattribute decision making. (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)

How do mushroom foragers make safe and efficient decisions under high degrees of uncertainty, or deal with the genuine risks of misidentification and poisoning? This article is an inquiry into ecological rationality, heuristics, perception, and decision-making in mushroom foraging. By surveying 894 Finnish mushroom foragers with a total of 22,304 years of foraging experience, this article illustrates how socially learned rules of thumb and heuristics are used in mushroom foraging. It illustrates how traditional foraging cultures have evolved precautionary (...) principles to deal with uncertainties and poisonous species, and how foragers leverage both simple heuristics and complex cognitive strategies in their search for, and identification of, mushrooms. Foragers also develop selective attention through experience. The results invite us to consider whether other human foraging cultures might use heuristics similarly, how and why such traditions have culturally evolved, and whether early hunter-gatherers might have used fast and frugal heuristics to deal with uncertainty. (shrink)

(1) An introduction to the principles of conceptual modelling, combinatorial heuristics and epistemological history; (2) the examination of a number of perennial epistemological-methodological schemata: conceptual spaces and blending theory; ars inveniendi and ars demonstrandi; the two modes of analysis and synthesis and their relationship to ars inveniendi; taxonomies and typologies as two fundamental epistemic structures; extended cognition, cognitio symbolica and model-based reasoning; (3) Plato’s notions of conceptual spaces, conceptual blending and hypothetical-analogical models (paradeigmata); (4) Ramon Llull’s concept analysis and (...) combinatoric spaces; (5) Gottfried Leibniz’s development of compositional analysis and synthesis as a general modelling method and a paradigm for ars inveniendi; (6) Fritz Zwicky’s revival of the morphological method of analysis and construction, and its subsequent computerised applications. (shrink)

The traditional approach to explanation in cognitive neuroscience is realist about psychological constructs, and treats them as explanatory. On the “standard framework,” cognitive neuroscientists explain behavior as the result of the instantiation of psychological functions in brain activity. This strategy is questioned by results suggesting the distribution of function in the brain, the multifunctionality of individual parts of the brain, and the overlap in neural realization of purportedly distinct psychological constructs. One response to this in the field has (...) been to employ the tools of databasing and machine learning to attempt to find and quantify specific correlations between psychological kinds such as ‘memory’ or ‘attention’ (or sub-kinds thereof) and patterns of activity in the brain. I assess the status and prospects of these projects. I argue that current proponents of the project are vague about their aims, vis-à-vis the standard framework, sometimes suggesting substantiation of the framework, sometimes suggesting retaining the framework but revising the ontology of mental constructs, and sometimes suggesting abandonment of the framework. I argue that extant results from within the projects fail to substantiate the standard framework, and propose an alternative. On my view, psychological constructs should not be viewed as explanantia, but instead as heuristic concepts that help us uncover ways that behaviors can vary and the ways that the brain implements those distinctions. I then discuss the normative upshot of these views for databasing and brain mapping projects. (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)

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)

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)

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)

In their response to our article (Keestra and Cowley, 2009), Hacker and Bennett charge us with failing to understand the project of their book Philosophical Foundations of Neuroscience (PFN; Bennett and Hacker, 2003) and do this by discussing foundationalism, linguistic conservatism and the passivity of perception. In this rebuttal we explore disagreements that explain the alleged errors. First, we reiterate our substantial disagreement with Bennett and Hacker (B&H) regarding their assumption that, even regarding much debated concepts like ‘consciousness’, we can (...) assume conceptual consensus within a community of competent speakers. Instead, we emphasize variability and divergence between individuals and groups in such contexts. Second, we plead for modesty in conceptual analysis, including the use of conceptual ambiguities as heuristics for the investigation of explanatory mechanisms. Third, we elucidate our proposal by discussing the interdependence of perception and action, which in some cases appear to be problematic for PFN. Fourth, we discuss why our view of conceptual innovation is different from B&H’s, as we plead for linking explanatory ingredients with conceptual analysis. We end by repeating our particular agreement with their mereological principle, even though we present different reasons: psychological concepts should not be applied to mere components or operations of explanatory mechanisms, for which another vocabulary should be developed. (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)

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)

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.

In the course of daily life we solve problems often enough that there is a special term to characterize the activity and the right to expect a scientific theory to explain its dynamics. The classical view in psychology is that to solve a problem a subject must frame it by creating an internal representation of the problem’s structure, usually called a problem space. This space is an internally generable representation that is mathematically identical to a graph structure with nodes and (...) links. The nodes can be annotated with useful information, and the whole representation can be distributed over internal and external structures such as symbolic notations on paper or diagrams. If the representation is distributed across internal and external structures the subject must be able to keep track of activity in the distributed structure. Problem solving proceeds as the subject works from an initial state in mentally supported space, actively constructing possible solution paths, evaluating them and heuristically choosing the best. Control of this exploratory process is not well understood, as it is not always systematic, but various heuristic search algorithms have been proposed and some experimental support has been provided for them. (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.

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.

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)

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)

This article addresses an open problem in the area of cognitive systems and architectures: namely the problem of handling (in terms of processing and reasoning capabilities) complex knowledge structures that can be at least plausibly comparable, both in terms of size and of typology of the encoded information, to the knowledge that humans process daily for executing everyday activities. Handling a huge amount of knowledge, and selectively retrieve it according to the needs emerging in different situational scenarios, is an (...) important aspect of human intelligence. For this task, in fact, humans adopt a wide range of heuristics (Gigerenzer & Todd) due to their “bounded rationality” (Simon, 1957). In this perspective, one of the requirements that should be considered for the design, the realization and the evaluation of intelligent cognitively-inspired systems should be rep- resented by their ability of heuristically identify and retrieve, from the general knowledge stored in their artificial Long Term Memory (LTM), that one which is synthetically and contextually relevant. This requirement, however, is often neglected. Currently, artificial cognitive systems and architectures are not able, de facto, to deal with complex knowledge structures that can be even slightly comparable to the knowledge heuris- tically managed by humans. In this paper I will argue that this is not only a technological problem but also an epistemological one and I will briefly sketch a proposal for a possible solution. (shrink)

In How We Understand Others: Philosophy and Social Cognition, Shannon Spaulding develops a novel account of social cognition with pessimistic implications for mindreading accuracy: according to Spaulding, mistakes in mentalizing are much more common than traditional theories of mindreading commonly assume. In this commentary, I push against Spaulding’s pessimism from two directions. First, I argue that a number of the heuristic mindreading strategies that Spaulding views as especially error prone might be quite reliable in practice. Second, I argue that current (...) methods for measuring mindreading performance are not well-suited for the task of determining whether our mental-state attributions are generally accurate. I conclude that any claims about the accuracy or inaccuracy of mindreading are currently unjustified. (shrink)

What factors affect judicial decision-making? The legal system is of utmost importance because of its impact on our lives. Judges appear to have the most power among any social workers seeing as the precedents set in their decisions are tantamount to written law. Nevertheless, judges may be subject to certain biases, moral and cognitive alike, which influence their rulings. Looking into how morality and cognitive biases affect judges may also reveal how we as individuals handle combining morals with (...) ethics- as well as whether any discrepancies among ourselves are justifiable. An investigation into relevant moral and jurisprudential theories revealed much about the inner workings of a judge’s mindset- whether he or she recognizes it or not. Coupling this with corroborated research on a select few heuristics present specifically for judges sets the foundation for an array of possible solutions in order to ensure the most impartial judicial proceedings. Plausible remedies include conducting premortems, implicit association tests, and a revised ruling procedure. (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)

Inventing novel knowledge to solve problems is a crucial, creative, mechanism employed by humans, to extend their range of action. In this paper, we present TCL (typicality-based compositional logic): a probabilistic, non monotonic extension of standard Description Logics of typicality, and will show how this framework is able to endow artificial systems of a human-like, commonsense based, concept composition procedure that allows its employment in a number of applications (ranging from computational creativity to goal-based reasoning to recommender systems and affective (...) computing). -/- The framework relies on 3 main ingredients: a non monotonic extension of standard Description Logics (allowing to reason on exceptions to inheritance in standard knowledge bases) a probabilistic extension coming from the field of logic programming (the DISPONTE semantics) a cognitive heuristics known ad HEAD-Modifier determining preference rules for the inheritance mechanisms of the novel concepts to be generated via commonsense rules. -/- We report the obtained results and the lessons learned of this research path in the context of model-based AI applications. -/- . (shrink)

Scientists regularly invoke broadly aesthetic properties like elegance and simplicity when evaluating theories, but why should we expect aesthetic pleasure to signal an epistemic good? I argue that aesthetic judgements in science are best understood as a special case of affective cognition, and that the feelings on which these judgements are based are the upshots of metacognitive monitoring of the quality of our engagement with theory and evidence. Finding a theory beautiful fallibly signals that it fits well with our background (...) knowledge and that it’s neither artificially adjusted to accommodate otherwise disconfirming evidence nor fitted to noise in the data, which makes aesthetic pleasure a good heuristic for theory evaluation. (shrink)

Beyond the predominant paradigm of an essentially rational human cognition, based on the classical binary logic, we want to propose some reflections that are organized around the intuition that the representations we have of the world are weighted with appreciations, for example affective ones. resulting from our integration into a social environment. We see these connotations as essentially ternary in nature, depending on the concepts underlying neutrosophy: either positive, negative or neutral. This form of representation would then influence the very (...) nature of the cognitive process, which in complex real-world situations, has to deal with problems of a combinatorial nature leading to a number of cases too large for our abilities. Forced to proceed by shortcuts on the basis of heuristics, cognition would use these assessments of the representations it manipulates to decide whether partial solutions are attractive for solving the problem or on the contrary are judged negative and are then quickly rejected. There is still the case of a neutral weighting that allows processing to continue. Thus a neutrosophical conception of our representations of the world explains how our cognition functions in its treatment of combinatorial problems in the form of producing processing accelerating heuristics, both in terms of partial solutions selection and processing optimization. (shrink)

We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of combining prototypical concepts, an open problem in the fields of AI and cognitive modelling. Our logic extends the logic of typicality ALC + TR, based on the notion of rational closure, by inclusions p :: T(C) v D (“we have probability p that typical Cs are Ds”), coming from the distributed semantics of probabilistic Description Logics. Additionally, it embeds a set of cognitive (...) class='Hi'>heuristics for concept combination. We show that the complexity of reasoning in our logic is EXPTIME-complete as in ALC. (shrink)

This paper discusses the ecological case for epistemic innocence: does biased cognition have evolutionary benefits, and if so, does that exculpate human reasoners from irrationality? Proponents of ‘ecological rationality’ have challenged the bleak view of human reasoning emerging from research on biases and fallacies. If we approach the human mind as an adaptive toolbox, tailored to the structure of the environment, many alleged biases and fallacies turn out to be artefacts of narrow norms and artificial set-ups. However, we argue that (...) putative demonstrations of ecological rationality involve subtle locus shifts in attributions of rationality, conflating the adaptive rationale of heuristics with our own epistemic credentials. By contrast, other cases also involve an ecological reframing of human reason, but do not involve such problematic locus shifts. We discuss the difference between these cases, bringing clarity to the rationality debate. (shrink)

Recent work in cognitive modelling has found that most of the data that has been cited as evidence for the dual-process theory (DPT) of reasoning is best explained by non-linear, “monotonic” one-process models (Stephens et al., 2018, 2019). In this paper, I consider an important caveat of this research: it uses models that are committed to unrealistic assumptions about how effectively task conditions can isolate Type-1 and Type-2 reasoning. To avoid this caveat, I develop a coordinated theoretical, experimental, and (...) modelling strategy to better test DPT. First, I propose that Type-1 and Type-2 reasoning are defined as reasoning that precedes and follows metacognitive control, respectively. Second, I argue that reasoning that precedes and follows metacognitive control can be effectively isolated using debiasing paradigms that manipulate metacognitive heuristics (e.g., processing fluency) to prevent or trigger metacognitive control, respectively. Third, I argue that monotonic modelling can allow us to decisively test DPT only when we use them to analyse data from this particular kind of debiasing paradigm. (shrink)

Hostile epistemology is the study of how environmental features exploit our cognitive vulnerabilities. I am particularly interested in those vulnerabilities arise from the basic character of our epistemic lives. We are finite beings with limited cognitive resources, perpetually forced to reasoning a rush. I focus on two sources of unavoidable vulnerability. First, we need to use cognitive shortcuts and heuristics to manage our limited time and attention. But hostile forces can always game the gap between the (...) heuristic and the ideal. Second, we need to trust others, and trust makes us vulnerable. In particular, we need to trust experts whose expertise lies beyond our individual ability to vet. So we must rely on various imperfect signals and proxies, like institutional affiliation, to manage our trust. We are forced to use these imperfect and exploitable forms of reasoning, in order to cope with a cognitively overwhelming world. I present the hostile epistemology framework as a counterbalance to vice epistemology, which tends to locate responsibility for bad beliefs in the character of the believer. I draw two conclusions from my analysis. First: suppose we accept that that only communities and institutions can know about the world. This deeply social approach doesn’t solve the problem of expert identification. The individual still faces a problem: given their incomplete understanding, how should the individual pick which group to trust? Second: we might have hoped to get some kind of static picture of the right principles of reasoning — but hostile epistemology presents a different picture. We have to use risky heuristics and shortcuts, which hostile forces can game and exploit. We can respond by shifting to a different set of heuristics, but this simply shifts the location of our vulnerabilities. These new heuristics are also exploitable. There is no end to this, only a constant struggle to adapt. Limited beings in a hostile epistemic environment are locked in an unending epistemic arms race. (shrink)

Creativity pervades human life. It is the mark of individuality, the vehicle of self-expression, and the engine of progress in every human endeavor. It also raises a wealth of neglected and yet evocative philosophical questions: What is the role of consciousness in the creative process? How does the audience for a work for art influence its creation? How can creativity emerge through childhood pretending? Do great works of literature give us insight into human nature? Can a computer program really be (...) creative? How do we define creativity in the first place? Is it a virtue? What is the difference between creativity in science and art? Can creativity be taught? The new essays that comprise The Philosophy of Creativity take up these and other key questions and, in doing so, illustrate the value of interdisciplinary exchange. Written by leading philosophers and psychologists involved in studying creativity, the essays integrate philosophical insights with empirical research. CONTENTS I. Introduction Introducing The Philosophy of Creativity Elliot Samuel Paul and Scott Barry Kaufman II. The Concept of Creativity 1. An Experiential Account of Creativity Bence Nanay III. Aesthetics & Philosophy of Art 2. Creativity and Insight Gregory Currie 3. The Creative Audience: Some Ways in which Readers, Viewers and/or Listeners Use their Imaginations to Engage Fictional Artworks Noël Carroll 4. The Products of Musical Creativity Christopher Peacocke IV. Ethics & Value Theory 5. Performing Oneself Owen Flanagan 6. Creativity as a Virtue of Character Matthew Kieran V. Philosophy of Mind & Cognitive Science 7. Creativity and Not So Dumb Luck Simon Blackburn 8. The Role of Imagination in Creativity Dustin Stokes 9. Creativity, Consciousness, and Free Will: Evidence from Psychology Experiments Roy F. Baumeister, Brandon J. Schmeichel, and C. Nathan DeWall 10. The Origins of Creativity Elizabeth Picciuto and Peter Carruthers 11. Creativity and Artificial Intelligence: a Contradiction in Terms? Margaret Boden VI. Philosophy of Science 12. Hierarchies of Creative Domains: Disciplinary Constraints on Blind-Variation and Selective-Retention Dean Keith Simonton VII. Philosophy of Education (& Education of Philosophy) 13. Educating for Creativity Berys Gaut 14. Philosophical Heuristics Alan Hájek. (shrink)

The feeling of clarity can be dangerously seductive. It is the feeling associated with understanding things. And we use that feeling, in the rough-and-tumble of daily life, as a signal that we have investigated a matter sufficiently. The sense of clarity functions as a thought-terminating heuristic. In that case, our use of clarity creates significant cognitive vulnerability, which hostile forces can try to exploit. If an epistemic manipulator can imbue a belief system with an exaggerated sense of clarity, then (...) they can induce us to terminate our inquiries too early — before we spot the flaws in the system. How might the sense of clarity be faked? Let’s first consider the object of imitation: genuine understanding. Genuine understanding grants cognitive facility. When we understand something, we categorize its aspects more easily; we see more connections between its disparate elements; we can generate new explanations; and we can communicate our understanding. In order to encourage us to accept a system of thought, then, an epistemic manipulator will want the system to provide its users with an exaggerated sensation of cognitive facility. The system should provide its users with the feeling that they can easily and powerfully create categorizations, generate explanations, and communicate their understanding. And manipulators have a significant advantage in imbuing their systems with a pleasurable sense of clarity, since they are freed from the burdens of accuracy and reliability. I offer two case studies of seductively clear systems: conspiracy theories; and the standardized, quantified value systems of bureaucracies. (shrink)

This paper provides an empirical defense of credit theories of knowing against Mark Alfano’s challenges to them based on his theses of inferential cognitive situationism and of epistemic situationism. In order to support the claim that credit theories can treat many cases of cognitive success through heuristic cognitive strategies as credit-conferring, the paper develops the compatibility between virtue epistemologies qua credit theories, and dual-process theories in cognitive psychology. It also a response to Lauren Olin and John (...) Doris’ “vicious minds” thesis, and their “tradeoff problem” for virtue theories. A genuine convergence between virtue epistemology and dual-process theory is called for, while acknowledging that this effort may demand new and more empirically well-informed projects on both sides of the division between Conservative virtue epistemology (including the credit theory of knowing) and Autonomous virtue epistemology (including projects for providing guidance to epistemic agents). (shrink)

The view that folk psychology is primarily mindreading beliefs and desires has come under challenge in recent years. I have argued that we also understand others in terms of individual properties such as personality traits and generalizations from past behavior, and in terms of group properties such as stereotypes and social norms (Andrews 2012). Others have also argued that propositional attitude attribution isn’t necessary for predicting others’ behavior, because this can be done in terms of taking Dennett’s Intentional Stance (Zawidzki (...) 2013), appealing to social structures (Maibom 2007), shared norms (McGeer 2007) or via solution based heuristics for reaching equilibrium between social partners (Morton 2003). But it isn’t only prediction that can be done without thinking about what others think; we can explain and understand people in terms of their personality traits, habitual behaviors, and social practices as well. The decentering of propositional attitude attributions goes hand in hand with a move away from taking folk psychology to be primarily a predictive device. While experiments examining folk psychological abilities in children, infants, and other species still rest on asking subjects to predict behavior, theoretical investigations as to the evolutionary function of folk psychology have stressed the role of explanation (Andrews 2012) and regulative functions (McGeer 2007, Zawidzki 2013, Fenici 2011). In this paper I argue that an explanatory role for folk psychology is also a regulative role, and that language is not required for these regulative functions. I will start by drawing out the relationship between prediction, explanation, and regulation of behavior according to both mindreading approaches to folk psychology and the pluralistic account I defend. I will argue that social cognition does not take the form of causal reasoning so much as it does normative reasoning, and will introduce the folk psychological spiral. Then I will examine the cognitive resources necessary for participating in the folk psychological spiral, and I will argue that these cognitive resources can be had without language. There is preliminary evidence that some other species understand one another through a normative lens that, through looping effects, creates expectations that community members strive to live up to. (shrink)