Theories of number concepts often suppose that the natural numbers are acquired as children learn to count and as they draw an induction based on their interpretation of the first few count words. In a bold critique of this general approach, Rips, Asmuth, Bloomfield [Rips, L., Asmuth, J. & Bloomfield, A.. Giving the boot to the bootstrap: How not to learn the natural numbers. Cognition, 101, B51–B60.] argue that such an inductive inference is consistent with a representational system (...) that clearly does not express the natural numbers and that possession of the natural numbers requires further principles that make the inductive inference superfluous. We argue that their critique is unsuccessful. Provided that children have access to a suitable initial system of representation, the sort of inductive inference that Rips et al. call into question can in fact facilitate the acquisition of larger integer concepts without the addition of any further principles. (shrink)

John Tillson argues, on grounds of children’s well-being, that it is impermissible to teach them religious views. I defend a practice of pluralistically advocating religious views to children. As long as there are no monopolies of influence over children, and as long as advocates do not use coercion, deceit, or manipulation, children can greatly benefit without having their rational abilities subverted, or incurring undue risk to form false beliefs. This solution should counter, to some extent, both perfectionist and antiperfectionist reasons (...) against initiating children into religions. (shrink)

What might Adam Smith have learned from Jane Austen and other novelists of his moment? This paper finds and examines a serious problem at the center of Adam Smith’s moral psychology, stemming from an unacknowledged tension between the effort of the spectator to sympathize with the feelings of the agent and that of the agent to moderate her feelings. The agent’s efforts will result in her opacity to spectators, blocking their attempts to read her emotions. I argue that we can (...) resolve this tension by looking to developments in eighteenth-century literature, as perfected in the hands of Jane Austen. I focus on two techniques, focalization and free indirect style, and I show that the problems for spectatorship diminish when we see that good Smithian spectators are savvy readers. (shrink)

Most of us spend a significant portion of our lives learning, practising, and performing a wide range of skills. Many of us also have a great amount of control over which skills we learn and develop. From choices as significant as career pursuits to those as minor as how we spend our weeknight leisure time, we exercise a great amount of agency over what we know and what we can do. In this paper we argue, using a framework first (...) developed by Carbonell (2013) that in many real-world circumstances we have moral obligations to develop some skills rather than others. (shrink)

Philosophy begins and ends in disagreement. Philosophers disagree among themselves in innumerable ways, and this pervasive and permanent dissent is a sign of their inability to solve philosophical problems and establish substantive truths. This raises the question: What should I do with my philosophical beliefs in light of philosophy's epistemic failure? In this open-access book, János Tozsér develops four possible answers into comprehensive metaphilosophical visions and argues that we cannot find peace either by committing ourselves to one of these visions (...) or by abandoning our philosophical beliefs. Tozsér calls this disheartening insight "the experience of breakdown", making the case that philosophy's truth-seeking and justificatory tools are unsuitable for establishing truths. Shedding light on the epistemic status of our philosophical beliefs, Tozsér adopts a broad approach to assess the metaphilosophical visions used by philosophers to interpret their own activity and determine their epistemic self-esteem. Open access was funded by the Research Centre for the Humanities, Hungary. (shrink)

This research is motivated by the need to unravel the progression of learning models, which have been adapting to meet the demands of society in its constant dynamics of fluctuation and transformation. The aim of this work is to systematically examine the evolution of learning models, highlighting the paradigmatic changes that have favored the transition from traditional learning approaches to more innovative and transdisciplinary proposals. To achieve this, a bibliographic analysis is carried out, supported by the hermeneutic method for the (...) contextual interpretation of literature and discourses, in order to unravel the complexities inherent in the evolution of learning models. The results highlight the limiting influence of the simplicity paradigm in traditional educational formation and the need for a shift towards dialogicity and disciplinary collaboration and integration to advance towards complexity. It concludes by arguing in favor of adopting the complexity paradigm, advocating for a transdisciplinary epistemology and an interstructuring approach to learning, which allow for integral human development. Recognizing human complexity in teaching and learning demands a radical transformation of education towards more holistic and transformative practices, essential for building an equitable and just society. (shrink)

It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that the (...) resulting predictive model does not use race as an explicit predictor. However, if race is correlated with measured recidivism in the training data, the ML tool may ‘learn’ a perfect proxy for race. If such a proxy is found, the exclusion of race would do nothing to weaken the correlation between risk (mis)classifications and race. Is this a problem? We argue that, on some explanations of the wrongness of discrimination, it is. On these explanations, the use of an ML tool that perfectly proxies race would (likely) be more wrong than the use of a traditional tool that imperfectly proxies race. Indeed, on some views, use of a perfect proxy for race is plausibly as wrong as explicit racial profiling. We end by drawing out four implications of our arguments. (shrink)

In this paper I argue that to understand minded agency – the capacity we typically find instantiated in instances of human behaviour that could sensibly be questioned by asking “What did you do?” – one needs to understand childhood, i.e. the trajectory of learning to act. I discuss two different types of trajectory, both of which seem to take place during childhood and both of which might be considered crucial to learning to act: a growth of bodily control (GBC) and (...) a growth in taking responsibility (GTR). The discussion of GTR takes up about half of the entire paper. In the final two sections I argue that GTR is the most promising trajectory in terms of which to understand a child’s process of learning to act. (shrink)

As attention to the pervasiveness and severity of environmental challenges grows, technical universities are responding to the need to include environmental topics in engineering curricula and to equip engineering students, without training in ethics, to understand and respond to the complex social and normative demands of these issues. But as compared to other areas of engineering ethics education, environmental ethics has received very little attention. This article aims to address this lack and raises the question: How should we teach environmental (...) ethics to engineering students? We argue that one key aspect such teaching should address is the tendency of engineers towards technical framing of (social) problems. Drawing then on engineering ethics pedagogy we propose that the competencies of moral sensitivity and critical thinking can be developed to help engineering students with problem (re)framing. We conclude with an example from our teaching that operationalizes these competencies. (shrink)

What can we learn from cases of knowledge from falsehood? Critics of knowledge-first epistemology have argued that these cases provide us with good reason for rejecting the knowledge accounts of evidence, justification, and the norm of belief. I shall offer a limited defense of the knowledge-first approach to these matters. Knowledge from falsehood cases should undermine our confidence in like-from-like reasoning in epistemology. Just as we should be open to the idea that knowledge can come from non-knowledge, we should (...) be open to the idea that justified beliefs can come from unjustified beliefs. (shrink)

I formulate a resilient paradox about epistemic rationality, discuss and reject various solutions, and sketch a way out. The paradox exemplifies a tension between a wide range of views of epistemic justification, on the one hand, and enkratic requirements on rationality, on the other. According to the enkratic requirements, certain mismatched doxastic states are irrational, such as believing p, while believing that it is irrational for one to believe p. I focus on an evidentialist view of justification on which a (...) doxastic state regarding a proposition p is epistemically rational or justified just in case it tracks the degree to which one’s evidence supports p. If it is possible to have certain kinds of misleading evidence, then evidentialism and the enkratic requirements come into conflict. Yet, both have been defended as platitudinous. After discussing and rejecting three solutions, I sketch an account that rejects the enkratic requirements, while nevertheless explaining our sense that epistemic akrasia is a distinct kind of epistemic failure. Central to the account is distinguishing between two evaluative perspectives, one having to do with the relevant kind of success, the other having to do with manifesting good dispositions. The problem with akratic subjects, I argue, is that they manifest dispositions to fail to correctly respond to a special class of conclusive and conspicuous reasons. (shrink)

Can fictional literature help us lead better lives? This essay argues that some works of literature can help us both change our personal narratives and develop new narratives that will guide our actions, enabling us to better achieve our goals. Works of literature can lead us to consider the hypothesis that we might beneficially change our future-oriented, personal narratives. As a case study, this essay considers Ben Lerner’s novel, 10:04, which focuses on humans’ ability to develop new narratives, and which (...) articulates a narrative that takes into account both everyday life and large-scale issues like the global, environmental crisis. (shrink)

We discuss the evolutionary transition from animals with limited experiencing to animals with unlimited experiencing and basic consciousness. This transition was, we suggest, intimately linked with the evolution of associative learning and with flexible reward systems based on, and modifiable by, learning. During associative learning, new pathways relating stimuli and effects are formed within a highly integrated and continuously active nervous system. We argue that the memory traces left by such new stimulus-effect relations form dynamic, flexible, and varied global sensory (...) states, which we call categorizing sensory states . These CSSs acquired a function: they came to act as internal “evaluators” and led to positive and negative reinforcement of new behavior. They are therefore the simplest, distinct, first-person motivational states that an animal can have. They constitute what we call basic consciousness, and are the hallmark of animals that can experience. Since associative learning has been found in many invertebrate taxa that first appeared during the Cambrian era, we propose that the processes underlying basic consciousness are phylogenetically ancient, and that their emergence may have fueled the Cambrian explosion. (shrink)

At its strongest, Hume's problem of induction denies the existence of any well justified assumptionless inductive inference rule. At the weakest, it challenges our ability to articulate and apply good inductive inference rules. This paper examines an analysis that is closer to the latter camp. It reviews one answer to this problem drawn from the VC theorem in statistical learning theory and argues for its inadequacy. In particular, I show that it cannot be computed, in general, whether we are in (...) a situation where the VC theorem can be applied for the purpose we want it to. (shrink)

We consider an extended notion of reinforcement learning in which the environment can simulate the agent and base its outputs on the agent's hypothetical behavior. Since good performance usually requires paying attention to whatever things the environment's outputs are based on, we argue that for an agent to achieve on-average good performance across many such extended environments, it is necessary for the agent to self-reflect. Thus weighted-average performance over the space of all suitably well-behaved extended environments could be considered a (...) way of measuring how self-reflective an agent is. We give examples of extended environments and introduce a simple transformation which experimentally seems to increase some standard RL agents' performance in a certain type of extended environment. (shrink)

Along with fresh interpretations of Plato, this book proposes a radically new approach to reading him, one that can teach us about protreptic, as it is called, by reimagining the ways in which Socrates engages in it. Protreptic, as it is conceived in the book, is an attempt to bring about a fundamental change of heart in people so that they want truth more than anything else. In taking the approach developed in this book, one doesn't try to get Plato (...) right but simply uses his dialogues as a theoretical tool for gaining insight into protreptic. The book argues that by analyzing Socrates' behavior in the right way, one can better understand how to foster thoughtfulness nowadays, and there is a need to foster it, in part since the health of democracy is at stake. (shrink)

The scientific understanding of cognition and consciousness is currently hampered by the lack of rigorous and universally accepted definitions that permit comparative studies. This paper proposes new functional and un- ambiguous definitions for cognition and consciousness in order to provide clearly defined boundaries within which general theories of cognition and consciousness may be developed. The proposed definitions are built upon the construction and manipulation of reality representation, decision making and learning and are scoped in terms of an underlying logical structure. (...) It is argued that the presentation of reality also necessitates the concept of ab- sence and the capacity to perform transitive inference. Explicit predictions relating to these new definitions, along with possible ways to test them, are also described and discussed. (shrink)

This study explores a liberatory epistemic virtue that is suitable for good learning as a form of liberating socially situated epistemic agents toward ideal virtuousness. First, I demonstrate that the weak neutralization of epistemically bad stereotypes is an end of good learning. Second, I argue that weak neutralization represents a liberatory epistemic virtue, the value of which derives from liberating us as socially situated learners from epistemic blindness to epistemic freedom. Third, I explicate two distinct forms of epistemic transformation: constitutive (...) and causal epistemic transformation. I argue that compared with the ideal conception of epistemic virtue, constitutive epistemic transformation that involves good learning has a transcendent value in light of agents constantly renewing their default epistemic status toward ideal virtuousness. (shrink)

On an account of virtue as skill, virtues are acquired in the ways that skills are acquired. In this paper I focus on one implication of that account that is deserving of greater attention, which is that becoming more skillful requires learning from one’s failures, but that turns out to be especially challenging when dealing with moral failures. In skill acquisition, skills are improved by deliberate practice, where you strive to correct past mistakes and learn how to overcome your (...) current limitations. A similar story applies to virtue acquisition, as moral failures will be a part of anyone’s life, and we will all have to learn from these experiences. However, despite the importance of being able to learn from our mistakes, this is very difficult in practice, given that failure of any kind can be distressing, and especially so for moral failure. The distress created by a recognition of moral failure often prompts responses of anger, avoidance, or defensiveness; rather than attempts to make amends and when necessary to work on self-improvement. The most potentially distressing response to moral failure is shame, as it is often associated with defensiveness. It is here where emotion regulation will be important to manage that distress, and I focus on the skill of emotion differentiation. I argue that emotion differentiation is a promising strategy for distinguishing the emotions we may experience in the wake of failure, including shame, and to encourage those emotions that motivate self-improvement. Thus, emotion regulation is important for virtue acquisition. (shrink)

Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of synthetic audiovisual (...) media, its place within a broader taxonomy of audiovisual media, and how deep learning techniques differ from more traditional approaches to media synthesis. After reviewing important etiological features of deep learning pipelines for media manipulation and generation, I argue that “deepfakes” and related synthetic media produced with such pipelines do not merely offer incremental improvements over previous methods, but challenge traditional taxonomical distinctions, and pave the way for genuinely novel kinds of audiovisual media. (shrink)

Anil Gupta’s Conscious Experience: A Logical Inquiry provides an impressive and novel account of rational justification based on conscious experience which is used as a foundation for a new theory of empiricism. In this critical notice, I argue that Gupta’s project is fascinating, but is often hampered by a lack of sufficient philosophical justification and clarity regarding some essential features of his project, as well as a lack of engagement with relevant scientific domains that would directly bear on it, such (...) as computational neuroscience, cognitive neuroscience, and cognitive psychology. This limits the sort of logical inquiry available to him in problematic ways. (shrink)

Concept maps are found to be useful in eliciting knowledge, meaningful learning, evaluation of understanding and in studying the nature of changes taking place during cognitive development, particularly in the classroom. Several experts have claimed the effectiveness of this tool for learning science. We agree with the claim, but the effectiveness will improve only if we gradually introduce a certain amount of discipline in constructing the maps. The discipline is warranted, we argue, because science thrives to be an unambiguous and (...) rigorously structured body of knowledge. Since learning science may be seen as a process where a novice is expected to be transformed into an expert, we use the context of learning science for making the proposal. Further, we identify certain anomalies in the evaluation of concept maps, and suggest that the evaluation should be based on semantics of the linking words (relation types) and not on graphical criteria alone. (shrink)

In a remarkable and utterly original work of philosophical history, Richard Allen revivifies David Hartley's Observations on Man, his Frame, his Duty, and his Expectations (1749). Though it includes a detailed and richly annotated chronology, this is not a straight intellectual biography, attentive as it might be to the intricacies of Hartley's Cambridge contacts, or the mundane rituals of his medical practice, or the internal development of the doctrine of association of ideas. Instead Allen brings Hartley's book, a psychological epic (...) with a mystical finale, sympathetically to life in a generous and ambitious historical gesture of mutual recognition. Late 20th-century readers "are in a better position to understand Hartley's work" than were earlier sympathizers like Joseph Priestley and John Stuart Mill; and in turn, Allen argues that "Hartley has something to say to us" about just how rich and strange a full mechanistic psychology might be. (shrink)

Within the discourse surrounding mind-body interaction, mental causation is intimately associated with non-reductive physicalism. However, such a theory holds two opposing views: that all causal properties and relations can be explicated by physics and that special sciences have an explanatory role. Jaegwon Kim attempts to deconstruct this problematic contradiction by arguing that it is untenable for non-reductive physicalists to explain human behavior by appeal to mental properties. In combination, Kim’s critique of mental causation and the phenomenal concept strategy serves (...) as an effectual response to the anti-physicalist stance enclosed within the Knowledge Argument and the Zombie Thought Experiment. (shrink)

Our perceptual systems are not stagnant but can learn from experience. Why is this so? That is, what is the function of perceptual learning? I consider two answers to this question: The Offloading View, which says that the function of perceptual learning is to offload tasks from cognition onto perception, thereby freeing up cognitive resources (Connolly, 2019) and the Perceptual View, which says that the function of perceptual learning is to improve the functioning of perception. I argue that the (...) Perceptual View better explains data from infants and animals, and better accounts for learned tasks that only perception could perform. (shrink)

Perceptual experiences are not immediately responsive to reasons. You see a stick submerged in a glass of water as bent no matter how much you know about light refraction. Due to this isolation from reasons, perception is traditionally considered outside the scope of epistemic evaluability as justified or unjustified. Is perception really as independent from reasons as visual illusions make it out to be? I argue no, drawing on psychological evidence from perceptual learning. The flexibility of perceptual learning is a (...) way of responding to new epistemic reasons. The resulting perceptual experiences are epistemically evaluable as justified or unjustified. (shrink)

A new model of the development of temporal concepts is described that assumes that there are substantial changes in how children think about time in the early years. It is argued that there is a shift from understanding time in an event-dependent way to an event-independent understanding of time. Early in development, very young children are unable to think about locations in time independently of the events that occur at those locations. It is only with development that children begin to (...) have a proper grasp of the distinction between past, present, and future, and represent time as linear and unidirectional. The model assumes that although children aged 2 to 3 years may categorize events differently depending on whether they lie in the past or the future, they may not be able to understand that whether an event is in the past or future is something that changes as time passes and varies with temporal perspective. Around 4 to 5 years, children understand how causality operates in time, and can grasp the systematic relations that obtain between different locations in time, which provides the basis for acquiring the conventional clock and calendar system. (shrink)

The cognitive penetrability of perceptual experiences has been a long-standing topic of disagreement among philosophers and psychologists. Although the notion of cognitive penetrability itself has also been under dispute, the debate has mainly focused on the cases in which cognitive states allegedly penetrate perceptual experiences. This paper concerns the plausibility of two prominent cases. The first one originates from Susanna Siegel’s claim that perceptual experiences can represent natural kind properties. If this is true, then the concepts we possess change the (...) way things appear to us. The second candidate for cognitive penetration is Fiona Macpherson’s claim that, in addition to concepts, our beliefs can penetrate perceptual experiences. It is argued that neither candidate is a case of cognitive penetration. In doing so, I provide an explanation to both that is based on perceptual learning, a non-cognitive phenomenon where relatively slow and long-lasting modifications to an organism’s perceptual system bring about changes in perception. This explanation is theoretically more plausible and remains closer to the empirical data than the explanations based on cognitive penetration. (shrink)

In LOT 2: The Language of Thought Revisited, Jerry Fodor argues that concept learning of any kind—even for complex concepts—is simply impossible. In order to avoid the conclusion that all concepts, primitive and complex, are innate, he argues that concept acquisition depends on purely noncognitive biological processes. In this paper, we show (1) that Fodor fails to establish that concept learning is impossible, (2) that his own biological account of concept acquisition is unworkable, and (3) that there are in fact (...) many promising general models for explaining how concepts are learned. (shrink)

We need urgently to bring about a revolution in universities around the world, wherever possible, so that they take their fundamental task to be, not to acquire and apply knowledge, but rather to help humanity learn how to resolve conflicts and problems of living in increasingly cooperatively rational ways, so that we may make progress towards a good, genuinely civilized, wise world. The pursuit of knowledge would be a vital but subsidiary task. I have argued for the urgent need (...) for such an academic revolution for nearly 50 years, ever since the publication of two books: What’s Wrong With Science? Towards a People’s Rational Science of Delight and Compassion, 1976, and From Knowledge to Wisdom: A Revolution for Science and the Humanities, 1984, both available free online. This article, written in preparation for a talk given to Pittsburgh University on the 15th September 2023, gives an outline of my baffled struggles with problems of philosophy, science, literature and life that led up to the discovery of the urgent need for an intellectual and institutional revolution in universities around the world, needed in order to galvanize the social revolution required to enable us to make progress to a world in which peace, justice, democracy, individual freedom, sustainable prosperity, the possibility of a good life, are available to all, insofar as that is attainable. (shrink)

Bayesianism can be characterized as the following twofold position: (i) rational credences obey the probability calculus; (ii) rational learning, i.e., the updating of credences, is regulated by some form of conditionalization. While the formal aspect of various forms of conditionalization has been explored in detail, the philosophical application to learning from experience is still deeply problematic. Some philosophers have proposed to revise the epistemology of perception; others have provided new formal accounts of conditionalization that are more in line with how (...) we learn from perceptual experience. The current investigation argues that Bayesian epistemology is still incomplete; the epistemology of perception and the epistemology of rational reasoning have not been reconciled. (shrink)

In this essay I argue that theorists such as Kohn and Mitra have been too hasty in pronouncing the superiority of problem-based learning over direct instruction.

Extended and distributed cognition theories argue that human cognitive systems sometimes include non-biological objects. On these views, the physical supervenience base of cognitive systems is thus not the biological brain or even the embodied organism, but an organism-plus-artifacts. In this paper, we provide a novel account of the implications of these views for learning, education, and assessment. We start by conceptualising how we learn to assemble extended cognitive systems by internalising cultural norms and practices. Having a better grip on (...) how extended cognitive systems are assembled, we focus on the question: If our cognition extends, how should we educate and assess such extended cognitive systems? We suggest various ways to minimize possible negative effects of extending one’s cognition and to efficiently find and organise (online) information by adopting a virtue epistemology approach. Educational and assessment implications are foregrounded, particularly in the case of Danish students’ use of the Internet during exams. (shrink)

Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding misguided? In (...) this paper, using the case of deep neural networks, I argue that it is not the complexity or black box nature of a model that limits how much understanding the model provides. Instead, it is a lack of scientific and empirical evidence supporting the link that connects a model to the target phenomenon that primarily prohibits understanding. (shrink)

I argue for the role of reinforcement learning in the philosophy of mind. To start, I make several assumptions about the nature of reinforcement learning and its instantiation in minds like ours. I then review some of the contributions of reinforcement learning methods have made across the so-called 'decision sciences.' Finally, I show how principles from reinforcement learning can shape philosophical debates regarding the nature of perception and characterisations of desire.

It has been argued that some recent experimental findings about the mere exposure effect can be used to argue for aesthetic antirealism: the view that there is no fact of the matter about aesthetic value. The aim of this paper is to assess this argument and point out that this strategy, as it stands, does not work. But we may still be able to use experimental findings about the mere exposure effect in order to engage with the aesthetic realism/antirealism debate. (...) However, this argument would need to proceed very differently and would only support a much more modest version of aesthetic antirealism. (shrink)

In this article, we address a major outstanding question of probabilistic Bayesian epistemology: how should a rational Bayesian agent update their beliefs upon learning an indicative conditional? A number of authors have recently contended that this question is fundamentally underdetermined by Bayesian norms, and hence that there is no single update procedure that rational agents are obliged to follow upon learning an indicative conditional. Here we resist this trend and argue that a core set of widely accepted Bayesian norms is (...) sufficient to identify a normatively privileged updating procedure for this kind of learning. Along the way, we justify a privileged formalization of the notion of ‘epistemic conservativity’, offer a new analysis of the Judy Benjamin problem, and emphasize the distinction between interpreting the content of new evidence and updating one’s beliefs on the basis of that content. (shrink)

In this paper I defend a teleological explanation of normativity, i. e., I argue that what an organism is supposed to do is determined by its etiological function. In particular, I present a teleological account of the normativity that arises in learning processes, and I defend it from some objections.

Over the last two decades, the capabilities approach has become an increasingly influential theory of development. It conceptualises human wellbeing in terms of an individual's ability to achieve functionings we have reason to value. In contrast, the African ethic of ubuntu views human flourishing as the propensity to pursue relations of fellowship with others, such that relationships have fundamental value. These two theoretical perspectives seem to be in tension with each other; while the capabilities approach focuses on individuals as the (...) locus of ethical value, an ubuntu ethic concentrates on the relations between individuals. In this article, we ask: to what extent is the capabilities approach compatible with this African ethical theory? We argue that, on reflection, relations play a much stronger role in the capabilities approach than often assumed. There is good reason to believe that relationality is part of the concept of a capability itself, where such relationality has intrinsic ethical value. This understanding of the ethical centrality of relations grounds new normative perspectives on the capabilities approach, and offers a more comprehensive grasp of the relevance of relationships to empirical enquiry. (shrink)

Proponents of cognitive penetration often argue for the thesis on the basis of combined intuitions about categorical perception and perceptual learning. The claim is that beliefs penetrate perceptions in the course of learning to perceive categories. I argue that this "diachronic" penetration thesis is false. In order to substantiate a robust notion of penetration, the beliefs that enable learning must describe the particular ability that subjects learn. However, they cannot do so, since in order to help with learning they (...) must instruct learners to employ previously existing abilities. I argue that a better approach recognizes that we can have sophisticated causal precursors to perceptual learning, but that the learning process itself must operate outside of cognitive influence. (shrink)

In this article, we provide a broad overview of the interplay among cognition, belief systems, and institutions, and how they affect economic performance. We argue that a deeper understanding of institutions’ emergence, their working properties, and their effect on economic and political outcomes should begin from an analysis of cognitive processes. We explore the nature of individual and collective learning, stressing that the issue is not whether agents are perfectly or boundedly rational, but rather how human beings actually reason and (...) choose, individually and in collective settings. We then tie the processes of learning to institutional analysis, providing arguments in favor of what can be characterized as “cognitive institutionalism.” Besides, we show that a full treatment of the phenomenon of path dependence should start at the cognitive level, proceed at the institutional level, and culminate at the economic level. (shrink)

Philosophers and psychologists have argued that fiction can ethically educate us: fiction supposedly can make us better people. This view has been contested. It is, however, rarely argued that fiction can morally “corrupt” us. In this article, we focus on the alleged power of fiction to decrease one's prejudices and biases. We argue that if fiction has the power to change prejudices and biases for the better, then it can also have the opposite effect. We further argue that fictions are (...) more likely to be a bad influence than a good one. (shrink)

Today, artificial intelligence, especially machine learning, is structurally dependent on human participation. Technologies such as Deep Learning (DL) leverage networked media infrastructures and human-machine interaction designs to harness users to provide training and verification data. The emergence of DL is therefore based on a fundamental socio-technological transformation of the relationship between humans and machines. Rather than simulating human intelligence, DL-based AIs capture human cognitive abilities, so they are hybrid human-machine apparatuses. From a perspective of media philosophy and social-theoretical critique, I (...) differentiate five types of “media technologies of capture” in AI apparatuses and analyze them as forms of power relations between humans and machines. Finally, I argue that the current hype about AI implies a relational and distributed understanding of (human/artificial) intelligence, which I categorize under the term “cybernetic AI”. This form of AI manifests in socio-technological apparatuses that involve new modes of subjectivation, social control and discrimination of users. (shrink)

In Philosophy and Technology 36, David Watson discusses the epistemological and metaphysical implications of unsupervised machine learning (ML) algorithms. Watson is sympathetic to the epistemological comparison of unsupervised clustering, abstraction and generative algorithms to human cognition and sceptical about ML’s mechanisms having ontological implications. His epistemological commitments are that we learn to identify “natural kinds through clustering algorithms”, “essential properties via abstraction algorithms”, and “unrealized possibilities via generative models” “or something very much like them.” The same issue contains a (...) commentary on Watson’s paper in which Tom Sterkenburg fiercely opposes the epistemological claim that clustering algorithms can identify natural kinds. Sterkenburg argues there’s nothing about clustering arguments themselves that enables natural kind identification. What’s at stake in the Watson-Sterkenburg debate is whether it is possible for clustering algorithms to identify natural kinds and whether they underly human identification of natural kinds. My contribution to the Watson-Sterkenburg debate is twofold. First, I argue Sterkenburg’s criticism of Watson’s claim is too severe because it denies any clustering algorithm to identify any natural kind. Secondly, I argue Watson’s reply overestimates both clustering algorithms’ and humans’ access to natural kinds and his claim has to be restricted accordingly to ‘We identify kinds via clustering algorithms, or something very much like them’. (shrink)

Complex constraints like conditionals ('If A, then B') and probabilistic constraints ('The probability that A is p') pose problems for Bayesian theories of learning. Since these propositions do not express constraints on outcomes, agents cannot simply conditionalize on the new information. Furthermore, a natural extension of conditionalization, relative information minimization, leads to many counterintuitive predictions, evidenced by the sundowners problem and the Judy Benjamin problem. Building on the notion of a `paradigm shift' and empirical research in psychology and economics, I (...) argue that the model of hypothesis testing can explain how people learn complex, theory-laden propositions like conditionals and probability constraints. Theories are formalized as probability distributions over a set of possible outcomes and theory change is triggered by a constraint which is incompatible with the initial theory. This leads agents to consult a higher order probability function, or a 'prior over priors,' to choose the most likely alternative theory which satisfies the constraint. The hypothesis testing model is applied to three examples: learning a simple probabilistic constraint involving coin bias, the sundowners problem for conditional learning, and the Judy Benjamin problem for learning conditional probability constraints. (shrink)

Theoretical models are widely held as sources of knowledge of reality. Imagination is vital to their development and to the generation of plausible hypotheses about reality. But how can imagination, which is typically held to be completely free, effectively instruct us about reality? In this paper I argue that the key to answering this question is in constrained uses of imagination. More specifically, I identify make-believe as the right notion of imagination at work in modelling. I propose the first overarching (...) taxonomy of types of constraints on scientific imagination that enables knowledge of reality. And I identify two main kinds of knowledge enabled by models, knowledge of the imaginary scenario specified by models and knowledge of reality. (shrink)

Fodor argued that learning a concept by hypothesis testing would involve an impossible circularity. I show that Fodor's argument implicitly relies on the assumption that actually φ-ing entails an ability to φ. But this assumption is false in cases of φ-ing by luck, and just such luck is involved in testing hypotheses with the kinds of generative random sampling methods that many cognitive scientists take our minds to use. Concepts thus can be learned by hypothesis testing without circularity, and it (...) is plausible that this is how humans in fact acquire at least some of their concepts. (shrink)

Understanding humans requires viewing them as mechanisms of some sort, since understanding anything requires seeing it as a mechanism. It is science’s job to reveal mechanisms. But science reveals much more than that: it also reveals enduring mystery—strangeness in the proportion. Concentrating just on the scientific side of Selinger’s and Engström’s call for a moratorium on cyborg discourse, I argue that this strangeness prevents cyborg discourse from diminishing us.

Harry Frankfurt has a comprehensive and, at times, compelling, account of love, which are outlined in several of his works. However, he does not think that romantic love fits the ideal of love as it ‘includes a number of vividly distracting elements, which do not belong to the essential nature of love as a mode of disinterested concern’. In this paper, I argue that we can, nonetheless, learn some important things about romantic love from his account. Furthermore, I will (...) suggest, conversely, that there is distinct value in romantic love, which derives from the nature of the relationship on which it is based. Frankfurt tries to take agape and reformulate it so that it can also account for love of particular people. Whilst he succeeds, to some extent, in describing parental love, he fails to accurately describe romantic love and friendship, and, moreover, overlooks what is distinctly valuable about them. Although it was not his intention to describe romantic love, by failing to include features such as reciprocity in his account of love, Frankfurt leaves no room for a kind of love that is important and valuable to many people. (shrink)

Today professionals have to deal with more uncertainties in their field than before. We live in complex and rapidly changing environments. The British philosopher Ronald Barnett adds the term ‘supercomplexity’ to highlight the fact that ‘we can no longer be sure how even to describe the world that faces us’ (Barnett, 2004). Uncertainty is, nevertheless, not a highly appreciated notion. An obvious response to uncertainty is to reduce it—or even better, to wipe it away. The assumption of this approach is (...) that uncertainty has no advantages. This assumption is, however, not correct as several contemporary authors have argued. Rather than problematising uncertainty, I will investigate the pros and cons of embedding uncertainty in educational practice of professional higher education. In order to thoroughly explore the probabilities and challenges that uncertainty poses in education, I will dwell on the radical ideas on uncertainty of the German philosopher Friedrich Nietzsche. In The Birth of Tragedy (1872) he recognises two forces: the Apollinian, that is the pursuit of order and coherence, and the Dionysian, that is the human tendency to nullify all systematisation and idealisation. Uncertainty is part of the Dionysian. I will argue that when educators take Nietzsche's plea to make room for the Dionysian to heart, they can better prepare students for an uncertain world. If, and only if, students are encouraged to deploy both tendencies—the Apollinian and the Dionysian—they can become professionals who are able to stand their ground in an uncertain and changing (professional) world. (shrink)