Which rules should guide our reasoning? Human reasoners often use reasoning shortcuts, called heuristics, which function well in some contexts but lack the universality of reasoning rules like deductive implication or inference to the best explanation. Does it follow that human reasoning is hopelessly irrational? I argue: no. Heuristic reasoning often represents human reasoners reaching a local rational maximum, reasoning more accurately than if they try to implement more “ideal” rules of reasoning. (...) I argue this is a genuine rational achievement. Our ideal rational advisors would advise us to reason with heuristic rules, not more complicated ideal rules. I argue we do not need a radical new account of epistemic norms to make sense of the success of heuristic reasoning. (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)

Even when they are defined with precision, one can often read and hear judgments about the vagueness of heuristics in debates about heuristic reasoning. This opinion is not just frequent but also quite reasonable. In fact, during the 1990s, there was a certain controversy concerning this topic that confronted two of the leading groups in the field of heuristic reasoning research, each of whom held very different perspectives. In the present text, we will focus on two (...) of the papers published in Psychological Review, wherein the arguments of each of these groups were presented:. (shrink)

An influential suggestion about the relationship between Bayesianism and inference to the best explanation holds that IBE functions as a heuristic to approximate Bayesian reasoning. While this view promises to unify Bayesianism and IBE in a very attractive manner, important elements of the view have not yet been spelled out in detail. I present and argue for a heuristic conception of IBE on which IBE serves primarily to locate the most probable available explanatory hypothesis to serve as (...) a working hypothesis in an agent’s further investigations. Along the way, I criticize what I consider to be an overly ambitious conception of the heuristic role of IBE, according to which IBE serves as a guide to absolute probability values. My own conception, by contrast, requires only that IBE can function as a guide to the comparative probability values of available hypotheses. This is shown to be a much more realistic role for IBE given the nature and limitations of the explanatory considerations with which IBE operates. (shrink)

Arguments for the effectiveness, and even the indispensability, of mathematics in scientific explanation rely on the claim that mathematics is an effective or even a necessary component in successful scientific predictions and explanations. Well-known accounts of successful mathematical explanation in physical science appeals to scientists’ ability to solve equations directly in key domains. But there are spectacular physical theories, including general relativity and fluid dynamics, in which the equations of the theory cannot be solved directly in target domains, and yet (...) scientists and mathematicians do effective work there (McLarty 2023, Elder 2023). Building on extant accounts of structural scientific explanation (Bokulich 2011, Leng 2021), I argue that philosophical accounts of the role of equations in scientific explanation need not rely on scientists’ ability to solve equations independently of their understanding of the empirical or experimental context. For instance, the process of formulating solutions to equations can involve significant appeal to information about experimental contexts (Curiel 2010) or of physically similar systems (Sterrett 2023). Working from a close analysis of work in fluid mechanics by Martin Bazant and Keith Moffatt (2005), I propose an account of heuristic structural explanation in mathematics (Einstein 1921, Pincock 2021), which explains how physical explanations can be constructed even in domains where basic equations cannot be solved directly. (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)

A heuristic is a rule of thumb. In psychology, heuristics are relatively simple rules for making judgments. A fast heuristic is easy to use and allows one to make judgments quickly. A frugal heuristic relies on a small fraction of the available evidence in making judgments. Typically, fast and frugal heuristics (FFHs) have, or are claimed to have, a further property: They are very reliable, yielding judgments that are about as accurate in the long run as ideal (...) non-fast, non-frugal rules. This paper introduces some well-known examples of FFHs, raises some objections to the FFH program, and looks at the implications of those parts of the FFH program about which we can have some reasonable degree of confidence. (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)

This paper discusses logic, rationality and the subjective nature of thought.

Extant research suggests that individuals employ traditional moral heuristics to support their observed altruistic behavior; yet findings have largely been limited to inductive extrapolation and rely on relatively few traditional frames in so doing, namely, deontology in organizational behavior and virtue theory in law and economics. Given that these and competing moral frames such as utilitarianism can manifest as identical behavior, we develop a moral framing instrument—the Philosophical Moral-Framing Measure (PMFM)—to expand and distinguish traditional frames associated and disassociated with observed (...) altruistic behavior. The validation of our instrument based on 1015 subjects in 3 separate real stakes scenarios indicates that heuristic forms of deontology, virtue-theory, and utilitarianism are strongly related to such behavior, and that egoism is an inhibitor. It also suggests that deontic and virtue-theoretical frames may be commonly perceived as intertwined and opens the door for new research on self-abnegation, namely, a perceived moral obligation toward suffering and self-denial. These findings hold the potential to inform ongoing conversations regarding organizational citizenship and moral crowding out, namely, how financial incentives can undermine altruistic behavior. (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)

The notion of Simulative Reasoning in the study of propositional attitudes within Artificial Intelligence (AI) is strongly related to the Simulation Theory of mental ascription in Philosophy. Roughly speaking, when an AI system engages in Simulative Reasoning about a target agent, it reasons with that agent’s beliefs as temporary hypotheses of its own, thereby coming to conclusions about what the agent might conclude or might have concluded. The contrast is with non-simulative meta-reasoning, where the AI system reasons (...) within a detailed theory about the agent’s (conjectured) reasoning acts. The motive within AI for preferring Simulative Reasoning is that it is more convenient and efficient, because of a simplification of the representations and reasoning processes. The chapter discusses this advantage in detail. It also sketches the use of Simulative Reasoning in an AI natural language processing system, ATT-Meta, that is currently being implemented. This system is directed at the understanding of propositional attitude reports. In ATT-Meta, Simulative Reasoning is yoked to a somewhat independent set of ideas about how attitude reports should be treated. Central here are the claims that (a) speakers often employ commonsense (and largely metaphorical) models of mind in describing agents’ attitudes, (b) the listener accordingly needs often to reason within the terms of such models, rather than on the basis of any objectively justifiable characterization of the mind, and (c) the commonsense models filter the suggestions that Simulative Reasoning comes up with concerning target agents’ reasoning conclusions. There is a yet tighter connection between the commonsense models and the Simulative Reasoning. It turns out that Simulative Reasoning can be rationally reconstructed in terms of a more general type of reasoning about the possibly-counterfactual “world” that the target agent believes in, together with an assumption that that agent has a faithful representation of the world. In the ATT-Meta approach, the reasoner adopts that assumption when it views the target agent through a particular commonsense model (called IDEAS-AS-MODELS). (shrink)

Presumption is a complex concept in law, affecting the dialogue setting. However, it is not clear how presumptions work in everyday argumentation, in which the concept of “plausible argumentation” seems to encompass all kinds of inferences. By analyzing the legal notion of presumption, it appears that this type of reasoning combines argument schemes with reasoning from ignorance. Presumptive reasoning can be considered a particular form of reasoning, which needs positive or negative evidence to carry a probative (...) weight on the conclusion. For this reason, presumptions shift the burden of providing evidence or explanations onto the interlocutor. The latter can provide new information or fail to do so: whereas in the first case the new information rebuts the presumption, in the second case, the absence of information that the interlocutor could reasonably provide strengthen the conclusion of the presumptive reasoning. In both cases the result of the presumption is to strengthen the conclusion of the reasoning from lack of evidence. As shown in the legal cases, the effect of presumption is to shift the burden of proof to the interlocutor; however, the shift a presumption effects is only the shift of the evidential burden, or the burden of completing the incomplete knowledge from which the conclusion was drawn. The burden of persuasion remains on the proponent of the presumption. On the contrary, reasoning from definition in law is a conclusive proof, and shifts to the other party the burden to prove the contrary. This crucial difference can be applied to everyday argumentation: natural arguments can be divided into dialectical and presumptive arguments, leading to conclusions materially different in strength. -/- . (shrink)

According to Steiner (1998), in contemporary physics new important discoveries are often obtained by means of strategies which rely on purely formal mathematical considerations. In such discoveries, mathematics seems to have a peculiar and controversial role, which apparently cannot be accounted for by means of standard methodological criteria. M. Gell-Mann and Y. Ne׳eman׳s prediction of the Ω− particle is usually considered a typical example of application of this kind of strategy. According to Bangu (2008), this prediction is apparently based on (...) the employment of a highly controversial principle—what he calls the “reification principle”. Bangu himself takes this principle to be methodologically unjustifiable, but still indispensable to make the prediction logically sound. In the present paper I will offer a new reconstruction of the reasoning that led to this prediction. By means of this reconstruction, I will show that we do not need to postulate any “reificatory” role of mathematics in contemporary physics and I will contextually clarify the representative and heuristic role of mathematics in science. (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)

Answer Set Programming is a new paradigm based on logic programming. The main component of answer set programming is a system that finds the answer sets of logic programs. During the computation of an answer set, systems are faced with choice points where they have to select a literal and assign it a truth value. Generally, systems utilize some heuristics to choose new literals at the choice points. The heuristic used is one of the key factors for the performance (...) of the system. A new heuristic for answer set programming has been developed. This heuristic is inspired by hierarchical planning. The notion of criticality, which was introduced for generating abstraction hierarchies in hierarchical planning, is used in this heuristic. The resulting system (CSMODELS) uses this new heuristic in a static way. CSMODELS is based on the system SMODELS. The experimental results show that this new heuristic is promising for answer set programming. A comparison of search times with SMODELS demonstrate CSMODELS’ usefulness. (shrink)

According to an increasingly popular epistemological view, people need outright beliefs in addition to credences to simplify their reasoning. Outright beliefs simplify reasoning by allowing thinkers to ignore small error probabilities. What is outright believed can change between contexts. It has been claimed that thinkers manage shifts in their outright beliefs and credences across contexts by an updating procedure resembling conditionalization, which I call pseudo-conditionalization (PC). But conditionalization is notoriously complicated. The claim that thinkers manage their beliefs via (...) PC is thus in tension with the view that the function of beliefs is to simplify our reasoning. I propose to resolve this puzzle by rejecting the view that thinkers employ PC. Based on this solution, I furthermore argue for a descriptive and a normative claim. The descriptive claim is that the available strategies for managing beliefs and credences across contexts that are compatible with the simplifying function of outright beliefs can generate synchronic and diachronic incoherence in a thinker’s attitudes. Moreover, I argue that the view of outright belief as a simplifying heuristic is incompatible with the view that there are ideal norms of coherence or consistency governing outright beliefs that are too complicated for human thinkers to comply with. (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)

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)

The relationship between teaching and argumentation is becoming a crucial issue in the field of education and, in particular, science education. Teaching has been analyzed as a dialogue aimed at persuading the interlocutors, introducing a conceptual change that needs to be grounded on the audience’s background knowledge. This paper addresses this issue from a perspective of argumentation studies. Our claim is that argumentation schemes, namely abstract patterns of argument, can be an instrument for reconstructing the tacit premises in students’ argumentative (...) reasoning and retrieving the background beliefs that are the basis of their arguments. On this perspective, the process of premise reconstruction is followed by a heuristic reasoning process aimed at discovering the students’ previous intuitions that can explain the premises and concepts that are left unexpressed in their arguments. The theoretical insights advanced in this paper are illustrated through selected examples taken from activities concerning predictive claims on scientific issues. (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 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)

Eliminative reasoning is a method that has been employed in many significant episodes in the history of science. It has also been advocated by some philosophers as an important means for justifying well-established scientific theories. Arguments for how eliminative reasoning is able to do so, however, have generally relied on a too narrow conception of evidence, and have therefore tended to lapse into merely heuristic or pragmatic justifications for their conclusions. This paper shows how a broader conception (...) of evidence not only can supply the needed justification but also illuminates the methodological significance of eliminative reasoning in a variety of contexts. (shrink)

There are emotively powerful words that can modify our judgment, arouse our emotions, and influence our decisions. The purpose of this paper is to provide instruments for analyzing the structure of the reasoning underlying the inferences that they trigger, in order to investigate their reasonableness conditions and their persuasive effect. The analysis of the mechanism of persuasion triggered by such words involves the complex systematic relationship between values, decisions, and emotions, and the reasoning mechanisms that have been investigated (...) under the label of “heuristics.” On the one hand, arguing using ethical words is shown to sometimes involve value-based practical reasoning grounded on evaluative classifications stemming from hierarchies of values and maxims of experience. On the other hand, ethical words provide representations bound to the interlocutor’s experiences and judgments, which trigger specific emotions yielding a particular reaction. This chain of judgments and reactions and the potential fallaciousness thereof can be inquired into by examining the relationship between the heuristic processes of reasoning and the more complex argumentative structure that the use of such words involves. The analysis of the 2013 Italian political campaign and the ad hominem arguments used by the political candidates shows the different strategies and counterstrategies for the manipulation of emotions. (shrink)

A Guide to Good Reasoning has been described by reviewers as “far superior to any other critical reasoning text.” It shows with both wit and philosophical care how students can become good at everyday reasoning. It starts with attitude—with alertness to judgmental heuristics and with the cultivation of intellectual virtues. From there it develops a system for skillfully clarifying and evaluating arguments, according to four standards—whether the premises fit the world, whether the conclusion fits the premises, whether (...) the argument fits the conversation, and whether it is possible to tell. (shrink)

The article develops and justifies, on the basis of the epistemological argumentation theory, two central pieces of the theory of evaluative argumentation interpretation: 1. criteria for recognizing argument types and 2. rules for adding reasons to create ideal arguments. Ad 1: The criteria for identifying argument types are a selection of essential elements from the definitions of the respective argument types. Ad 2: After presenting the general principles for adding reasons (benevolence, authenticity, immanence, optimization), heuristics are proposed for finding missing (...) reasons, for deductive arguments, e.g., semantic tableaux are suggested. (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)

There are emotively powerful words that can modify our judgment, arouse our emotions and influence our decisions. This paper shows how the use of emotive meaning in argumentation can be explained by showing how their logical dimension, which can be analysed using argumentation schemes, combines with heuristic processes triggered by emotions. Arguing with emotive words is shown to use value-based practical reasoning grounded on hierarchies of values and maxims of experience for evaluative classification.

Modern fundamental science tends to avoid the principle of physical causality and realism, replacing it with heuristically postulated and separated mathematical constructions that impose their own rules before being adjusted to measurement results. While it is officially accepted as the single possible kind of rigorous knowledge, we argue that another, explicitly extended kind of science can provide the causally complete picture of reality avoiding the glaring gaps, growing problems and persisting stagnation of the artificially reduced knowledge paradigm. The logic of (...) science development and especially its current state call for the urgently needed transition to the extended, causally complete kind of knowledge and related sustainable progress at superior creativity levels of self-aware, reason-based society. (shrink)

Misinformation can have significant societal consequences. For example, misinformation about climate change has confused the public and stalled support for mitigation policies. When people lack the expertise and skill to evaluate the science behind a claim, they typically rely on heuristics such as substituting judgment about something complex (i.e. climate science) with judgment about something simple (i.e. the character of people who speak about climate science) and are therefore vulnerable to misleading information. Inoculation theory offers one approach to effectively neutralize (...) the influence of misinformation. Typically, inoculations convey resistance by providing people with information that counters misinformation. In contrast, we propose inoculating against misinformation by explaining the fallacious reasoning within misleading denialist claims. We offer a strategy based on critical thinking methods to analyse and detect poor reasoning within denialist claims. This strategy includes detailing argument structure, determining the truth of the premises, and checking for validity, hidden premises, or ambiguous language. Focusing on argument structure also facilitates the identification of reasoning fallacies by locating them in the reasoning process. Because this reason-based form of inoculation is based on general critical thinking methods, it offers the distinct advantage of being accessible to those who lack expertise in climate science. We applied this approach to 42 common denialist claims and find that they all demonstrate fallacious reasoning and fail to refute the scientific consensus regarding anthropogenic global warming. This comprehensive deconstruction and refutation of the most common denialist claims about climate change is designed to act as a resource for communicators and educators who teach climate science and/or critical thinking. (shrink)

In this work we present an explainable system for emotion attribution and recommendation (called DEGARI (Dynamic Emotion Generator And ReclassIfier) relying on a recently introduced probabilistic commonsense reasoning framework (i.e. the TCL logic, see Lieto & Pozzato 2020) which is based on a human-like procedure for the automatic generation of novel concepts in a Description Logics knowledge base (see also Lieto et al. 2019, Chiodino et al. 2020 for other applications). In particular, in order to model human-like forms of (...) concept combinations, the TCL logic combines a probabilistic description logics of typicality with the HEAD-MODIFIER heuristics coming from cognitive semantics. In the context of our application of such framework, our system exploits the logic TCL to automatically generate novel commonsense semantic representations of compound emotions (e.g. Love as derived from the combination of Joy and Trust according to Plutchik’s theory of emotions, see Plutchik 2001). The generated emotions corresponds to prototypes, i.e. commonsense representations of given concepts, and have been used to reclassify emotion-related contents in a variety of artistic domains. We have tested our system in the context of the H2020 EU project SPICE for providing artistic recommendations of museum items in the Galleria di Arte Moderna (GAM) of Turin. The obtained results (reported in Lieto et al, 2021 and Lieto at al., to appear) show promising results for what concerns both the acceptance of the provided affective recommendation and the explainability associated to each suggestion made by the users. Here we discuss, the open problems and the lessons learned. -/- . (shrink)

We offer a model of moral reform and regeneration that involves a wrong-doer making two movements: on the one hand, he identifies with himself as the one who did the act, while he also intentionally moves away from that self (or set of desires and intentions) and moves toward a transformed identity. We see this model at work in the formal practice of contrition and reform in Christian and Buddhist rites. This paper is part of a broader project we are (...) undertaking on the philosophy of forgiveness. (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 relationship between teaching and argumentation is becoming a crucial issue in the field of education and, in particular, science education. Teaching has been analyzed as a dialogue aimed at persuading the interlocutors, introducing a conceptual change that needs to be grounded on the audience’s background knowledge. This paper addresses this issue from a perspective of argumentation studies. Our claim is that argumentation schemes, namely abstract patterns of argument, can be an instrument for reconstructing the tacit premises in students’ argumentative (...) reasoning and retrieving the background beliefs that are the basis of their arguments. On this perspective, the process of premise reconstruction is followed by a heuristic reasoning process aimed at discovering the students’ previous intuitions that can explain the premises and concepts that are left unexpressed in their arguments. The theoretical insights advanced in this paper are illustrated through selected examples taken from activities concerning predictive claims on scientific issues. (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)

In the last forty years the number of specialized publications on deliberative democracy has increased steadily. Yet, today, one of the greatest challenges we still face today is to deepen into the knowledge of our actual and singular deliberative cultures. In order to achieve this, it is necessary that we use theoretical and methodological approaches that enable us to capture the inherent complexity to the specific forms of deliberation that are present in as different areas as that of politics, economics, (...) law, science, urbanism or the Net. (shrink)

We expand on Della Croce’s ambition to interpret “epistemic injustice” as a specification of non-maleficence in the use of the influential four-principle framework. This is an alluring line of thought for conceptual, moral, and heuristic reasons. Although it is commendable, Della Croce’s attempt remains tentative. So does our critique of it. Yet, we take on the challenge to critically address two interrelated points. First, we broaden the analysis to include deliberations about hermeneutical injustice. We argue that, if due consideration (...) of epistemic injustice is to require more than negative ethical obligations in medicine, dimensions of hermeneutical injustice should be explored as an avenue to arrive at such positive duties. Second, and relatedly, we argue that this may encompass moral responsibilities beyond the individual level, that is: positive obligations to take action on a structural level. Building on Dotson’s concept of “contributory injustice” and Scheman’s concept of “perceptual autonomy,” we suggest that the virtues of testimonial and hermeneutical justice may provide additional content not only to negative prohibitions of action (i.e. non-maleficence) but also to positive requirements of action, like respecting patient autonomy. (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)

This dissertation is a collection of essays exploring the role of metaphor in Aristotle’s scientific method. Aristotle often appeals to metaphors in his scientific practice; but in the Posterior Analytics, he suggests that their use is inimical to science. Why, then, does he use them in natural science? And what does his use of metaphor in science reveal about the nature of his scientific investigations? I approach these questions by investigating the epistemic status of metaphor in Aristotelian science. In the (...) first essay, I defend an interpretation of metaphor as a type of heuristic reasoning: I claim that Aristotle uses metaphor to express conditions an explanation in natural science must meet if it is to explain regular, ordered change. These conditions specify the kinds of causes—particularly unmoved efficient causes—which the inquirer into nature is seeking. In the second essay, I look to Aristotle’s use of certain endoxa or common beliefs as explanatory principles in science, and show that his use of these principles is similar to his use of metaphor. In the final essay, I present a historical study of the analogy of art and nature, and I suggest that by looking to how the Greeks understood the role of inquiry in the arts, we can shed some light on Aristotle’s views concerning the method of inquiry he thinks the natural scientist should adopt. (shrink)

In “The Possibility of Epistemic Nudging” (2021), I address a phenomenon that is widely neglected in the current literature on nudges: intentional doxastic nudging, i.e. people’s intentional influence over other people’s beliefs, rather than over their choices. I argue that, at least in brute cases, nudging is not giving reasons, but rather bypasses reasoning altogether. More specifically, nudging utilizes psychological heuristics and the nudged person’s biases in smart ways. The goal of my paper is to defend the claim that (...) nudging, even when it bypasses reasoning, can result in justified beliefs and knowledge. As I argue, it takes two things to accomplish this goal: suitable meta-epistemological views and appropriate circumstances. If a broadly reliabilist account of justified beliefs and knowledge is correct, and if the relevant belief-forming methods are externally individuated in the right way, then nudging to knowledge is possible. If, in addition, the nudger is knowledgeable, epistemically benevolent and systematically effective, then nudging to knowledge will become reality. In their replies Neil Levy (2021) and Jonathan Matheson and Valerie Joly Chock (2021), put pressure on my argument from different angles. Levy thinks that a better case can be made for his view that nudging is giving testimonial reasons, and finds my objections to this view unconvincing. Matheson and Joly Chock, on the other hand, point out that acquiring knowledge through nudging (i.e. epistemic nudging) is compatible with evidentialism, even if nudging is not giving reasons. On their view, evidentialism provides an explanation of epistemic nudging that is superior to my own account, which, according to them, also suffers from a number of counterintuitive consequences. I am grateful to my critics for raising these concerns, because considering them deepens our perspective on the target phenomenon, and has made me think harder about the relevant epistemological issues. Nevertheless, I am convinced that my core claims can be defended against these criticisms. (shrink)

Many philosophers agree that there is an epistemic norm governing action. However, they disagree on what this norm is. It has been observed that the word ‘know’ is prominent in ordinary epistemic evaluations of actions. Any opponent of the knowledge norm must provide an explanation of this fact. Gerken has recently proposed the most developed explanation. It invokes the hypothesis that, in normal contexts, knowledge-level warrant is frequently necessary and very frequently sufficient (Normal Coincidence), so that knowledge-based assessments would be (...) a good heuristic for practical reasoning and epistemic evaluations of action. In this paper, I raise three problems for this approach. First, I argue that Normal Coincidence is ad hoc: it relies on an unsupported frequency hypothesis that we should expect to be false given the warrant account that Gerken also endorses. Second, I argue that, in any case, Normal Coincidence is insufficient to support the hypothesis that knowledge-based evaluation of action constitutes a good heuristic. Third, I consider three other hypotheses close to Normal Coincidence apparently more likely to support the heuristic hypothesis, but I argue that they seem even more ad hoc than Normal Coincidence. (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)

If A is better than B and B is better than C, then A is better than C, right? Larry Temkin and Stuart Rachels say: No! Betterness is nontransitive, they claim. In this paper, I discuss the central type of argument advanced by Temkin and Rachels for this radical idea, and argue that, given this view very likely has sceptical implications for practical reason, we would do well to identify alternative responses. I propose one such response, which employs the idea (...) that rational agents might regard some options as incommensurate in value, and will reasonably employ a heuristic of status quo maintenance to avoid suboptimal choices from incommensurate goods. (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)

In this paper, I argue that Psychological Essentialism (PE), the view that essences are a heuristic or mental shortcut, is a better explanation for modal intuitions than Metaphysical Essentialism (ME), the view that objects have essences, or more precisely, that (at least some) objects have (at least some) essential properties. If this is correct, then the mere fact that we have modal intuitions is not a strong reason to believe that objects have essential properties.

In the last twenty years, there has been an enormous growth of scientific research concerning the process of human moral reasoning and moral intuitions. In contemporary descriptive ethics, three dominant approaches can be found – heuristic approach, dual-process theory, and universal moral grammar. Each of these accounts is based on similar empirical evidence combining findings from evolutionary biology, moral psychology, and neuroethics. Nevertheless, they come to different conclusions about the reliability of moral intuitions. The aim of this paper (...) is to critically investigate each of these approaches and compare them with recent scientific findings. Last chapter addresses implications of these findings for moral epistemology and normative ethics. The aim is to show that despite different interpretations of available data, we can reach a satisfying pragmatical conclusion which would be in compliance with the empirical evidence, yet it would not necessarily depend on it. (shrink)

In this article, we discuss some issues concerning magical thinking—forms of thought and association mechanisms characteristic of early stages of mental development. We also examine good reasons for having an ambivalent attitude concerning the later permanence in life of these archaic forms of association, and the coexistence of such intuitive but informal thinking with logical and rigorous reasoning. At the one hand, magical thinking seems to serve the creative mind, working as a natural vehicle for new ideas and innovative (...) insights, and giving form to heuristic arguments. At the other hand, it is inherently difficult to control, lacking effective mechanisms needed for rigorous manipulation. Our discussion is illustrated with many examples from the Hebrew Bible, and some final examples from modern science. (shrink)