Biological evolution provides a creative fount of complex and subtle adaptations, often surprising the scientists who discover them. However, because evolution is an algorithmic process that transcends the substrate in which it occurs, evolution’s creativity is not limited to nature. Indeed, many researchers in the field of digital evolution have observed their evolving algorithms and organisms subverting their intentions, exposing unrecognized bugs in their code, producing unexpected adaptations, or exhibiting outcomes uncannily convergent with ones in nature. Such stories routinely reveal (...) creativity by evolution in these digital worlds, but they rarely fit into the standard scientific narrative. Instead they are often treated as mere obstacles to be overcome, rather than results that warrant study in their own right. The stories themselves are traded among researchers through oral tradition, but that mode of information transmission is inefficient and prone to error and outright loss. Moreover, the fact that these stories tend to be shared only among practitioners means that many natural scientists do not realize how interesting and lifelike digital organisms are and how natural their evolution can be. To our knowledge, no collection of such anecdotes has been published before. This paper is the crowd-sourced product of researchers in the fields of artificial life and evolutionary computation who have provided first-hand accounts of such cases. It thus serves as a written, fact-checked collection of scientifically important and even entertaining stories. In doing so we also present here substantial evidence that the existence and importance of evolutionary surprises extends beyond the natural world, and may indeed be a universal property of all complex evolving systems. (shrink)

A distributed neural network model called SPEC for processing sentences with recursive relative clauses is described. The model is based on separating the tasks of segmenting the input word sequence into clauses, forming the case‐role representations, and keeping track of the recursive embeddings into different modules. The system needs to be trained only with the basic sentence constructs, and it generalizes not only to new instances of familiar relative clause structures but to novel structures as well. SPEC exhibits plausible memory (...) degradation as the depth of the center embeddings increases, its memory is primed by earlier constituents, and its performance is aided by semantic constraints between the constituents. The ability to process structure is largely due to a central executive network that monitors and controls the execution of the entire system. This way, in contrast to earlier subsymbolic systems, parsing is modeled as a controlled high‐level process rather than one based on automatic reflex responses. (shrink)

This article addresses the ability of Parallel Distributed Processing (PDP) networks to generate stagewise cognitive development in accordance with Piaget's theory of cognitive epigenesis. We carried out a replication study of the simulation experiments by McClelland (1989) and McClelland and Jenkins (1991) in which a PDP network learns to solve balance scale problems. In objective tests motivated from catastrophe theory, a mathematical theory of transitions in epigenetical systems, no evidence for stage transitions in network performance was found. It is concluded (...) that PDP networks lack the ability to recover the positive outcomes of analogous catastrophe analyses of real cognitive developmental data. In an attempt to further characterize the learning behaviour of PDP networks, we carried out a second simulation study using the discrimination‐shift paradigm. The results thus obtained indicate that PDP learning is compatible with the learning of stimulus‐response relationships, not with the acquisition of mediating rules such as conceived in (neo‐)Piagetian theory. In closing, we speculate about the feasibility of simulating stagewise development with alternative network architectures. (shrink)

Many of the computing systems programmed using Machine Learning are opaque: it is difficult to know why they do what they do or how they work. Explainable Artificial Intelligence aims to develop analytic techniques that render opaque computing systems transparent, but lacks a normative framework with which to evaluate these techniques’ explanatory successes. The aim of the present discussion is to develop such a framework, paying particular attention to different stakeholders’ distinct explanatory requirements. Building on an analysis of “opacity” from (...) philosophy of science, this framework is modeled after accounts of explanation in cognitive science. The framework distinguishes between the explanation-seeking questions that are likely to be asked by different stakeholders, and specifies the general ways in which these questions should be answered so as to allow these stakeholders to perform their roles in the Machine Learning ecosystem. By applying the normative framework to recently developed techniques such as input heatmapping, feature-detector visualization, and diagnostic classification, it is possible to determine whether and to what extent techniques from Explainable Artificial Intelligence can be used to render opaque computing systems transparent and, thus, whether they can be used to solve the Black Box Problem. (shrink)

Words become associated following repeated co-occurrence episodes. This process might be further determined by the semantic characteristics of the words. The present study focused on how semantic and episodic factors interact in incidental formation of word associations. First, we found that human participants associate semantically related words more easily than unrelated words; this advantage increased linearly with repeated co-occurrence. Second, we developed a computational model, SEMANT, suggesting a possible mechanism for this semantic-episodic interaction. In SEMANT, episodic associations are implemented through (...) lateral connections between nodes in a pre-existent self-organized map of word semantics. These connections are strengthened at each instance of concomitant activation, proportionally with the amount of the overlapping activity waves of activated nodes. In computer simulations SEMANT replicated the dynamics of associative learning in humans and led to testable predictions concerning normal associative learning as well as impaired learning in a diffuse semantic system like that characteristic of schizophrenia. (shrink)

The received view of dynamical explanation is that dynamical cognitive science seeks to provide covering law explanations of cognitive phenomena. By analyzing three prominent examples of dynamicist research, I show that the received view is misleading: some dynamical explanations are mechanistic explanations, and in this way resemble computational and connectionist explanations. Interestingly, these dynamical explanations invoke the mathematical framework of dynamical systems theory to describe mechanisms far more complex and distributed than the ones typically considered by philosophers. Therefore, contemporary dynamicist (...) research reveals the need for a more sophisticated account of mechanistic explanation. (shrink)

Models developed using machine learning are increasingly prevalent in scientific research. At the same time, these models are notoriously opaque. Explainable AI aims to mitigate the impact of opacity by rendering opaque models transparent. More than being just the solution to a problem, however, Explainable AI can also play an invaluable role in scientific exploration. This paper describes how post-hoc analytic techniques from Explainable AI can be used to refine target phenomena in medical science, to identify starting points for future (...) investigations of causal relationships, and to generate possible explanations of target phenomena in cognitive science. In this way, this paper describes how Explainable AI—over and above machine learning itself—contributes to the efficiency and scope of data-driven scientific research. (shrink)

Bayesian reverse-engineering is a research strategy for developing three-level explanations of behavior and cognition. Starting from a computational-level analysis of behavior and cognition as optimal probabilistic inference, Bayesian reverse-engineers apply numerous tweaks and heuristics to formulate testable hypotheses at the algorithmic and implementational levels. In so doing, they exploit recent technological advances in Bayesian artificial intelligence, machine learning, and statistics, but also consider established principles from cognitive psychology and neuroscience. Although these tweaks and heuristics are highly pragmatic in character and (...) are often deployed unsystematically, Bayesian reverse-engineering avoids several important worries that have been raised about the explanatory credentials of Bayesian cognitive science: the worry that the lower levels of analysis are being ignored altogether; the challenge that the mathematical models being developed are unfalsifiable; and the charge that the terms ‘optimal’ and ‘rational’ have lost their customary normative force. But while Bayesian reverse-engineering is therefore a viable and productive research strategy, it is also no fool-proof recipe for explanatory success. (shrink)

In a context of pervasive digitalization of the social world, both before and during the COVID-19 pandemic, the field of education has undergone major changes with the development of digital practices and settings. However, the physical presence of the subjects and the body remain something primordial and irreplaceable in traditional educational processes. Thus, it is often assumed that virtuality is opposed to the corporeal reality of the subjects involved in teaching, learning and studying. In this paper we aim to critically (...) challenge this assumption by addressing the phenomenon of virtuality in a more original sense: as a fundamental dimension of corporeality itself. Drawing on Merleau-Ponty’s phenomenological insights, we argue that the experience of the virtual is inherently embodied and fully real. We understand corporeality and virtuality as entangled and multidimensional phenomena. At the same time, this leads us to rethink the digital as only one possible medium in which virtuality can appear as inherent to embodied experience. We develop our phenomenological approach in three instances. First, we question and bracket two common assumptions about corporeality. From our critical perspective, assumptions about a disembodied digitality and a devirtualized corporeality represent extremes within which educational discourses currently move. Second, we address the inherent virtuality of embodied experience. We outline the heuristic concept of the virtual body to describe corporeality and virtuality as entangled and multidimensional phenomena that encompass extension, intercorporeality and intermediality. Finally, we make some remarks on the relationships of corporeality and virtuality considering the challenges of digital education. (shrink)

The philosophical conception of mechanistic explanation is grounded on a limited number of canonical examples. These examples provide an overly narrow view of contemporary scientific practice, because they do not reflect the extent to which the heuristic strategies and descriptive practices that contribute to mechanistic explanation have evolved beyond the well-known methods of decomposition, localization, and pictorial representation. Recent examples from evolutionary robotics and network approaches to biology and neuroscience demonstrate the increasingly important role played by computer simulations and mathematical (...) representations in the epistemic practices of mechanism discovery and mechanism description. These examples also indicate that the scope of mechanistic explanation must be re-examined: With new and increasingly powerful methods of discovery and description comes the possibility of describing mechanisms far more complex than traditionally assumed. (shrink)

This chapter subsumes David Marr’s levels of analysis account of explanation in cognitive science under the framework of mechanistic explanation: Answering the questions that define each one of Marr’s three levels is tantamount to describing the component parts and operations of mechanisms, as well as their organization, behavior, and environmental context. By explicating these questions and showing how they are answered in several different cognitive science research programs, this chapter resolves some of the ambiguities that remain in Marr’s account, and (...) shows that many different areas and traditions of cognitive scientific research can be unified under the mechanistic framework. (shrink)

Whereas most branches of neuroscience are thought to provide mechanistic explanations, systems neuroscience is not. Two reasons are traditionally cited in support of this conclusion. First, systems neuroscientists rarely, if ever, rely on the dual strategies of decomposition and localization. Second, they typically emphasize organizational properties over the properties of individual components. In this paper, I argue that neither reason is conclusive: researchers might rely on alternative strategies for mechanism discovery, and focusing on organization is often appropriate and consistent with (...) the norms of mechanistic explanation. Thus, many explanations in systems neuroscience can also be viewed as mechanistic explanations. (shrink)

This paper considers the way mathematical and computational models are used in network neuroscience to deliver mechanistic explanations. Two case studies are considered: Recent work on klinotaxis by Caenorhabditis elegans, and a longstanding research effort on the network basis of schizophrenia in humans. These case studies illustrate the various ways in which network, simulation and dynamical models contribute to the aim of representing and understanding network mechanisms in the brain, and thus, of delivering mechanistic explanations. After outlining this mechanistic construal (...) of network neuroscience, two concerns are addressed. In response to the concern that functional network models are non-explanatory, it is argued that functional network models are in fact explanatory mechanism sketches. In response to the concern that models which emphasize a network’s organization over its composition do not explain mechanistically, it is argued that this emphasis is both appropriate and consistent with the principles of mechanistic explanation. What emerges is an improved understanding of the ways in which mathematical and computational models are deployed in network neuroscience, as well as an improved conception of mechanistic explanation in general. (shrink)

This article argues for a new interpretation of the realist claim that politics is autonomous from morality and involves specific political values. First, this article defends an original normative source: functional normativity. Second, it advocates a substantive functional standard: political institutions ought to be assessed by their capacity to select and implement collective decisions. Drawing from the ‘etiological account’ in philosophy of biology, I will argue that functions yield normative standards, which are independent from morality. For example, a ‘good heart’ (...) is one that pumps blood well, and a good army is one that it is effective at exerting military force. I then interpret realism’s naturalistic conception of politics as an etiological function of social groups: namely making binding collective decisions under persistent disagreement. I conclude that political institutions should be evaluated realistically by how well they perform this task. Finally, I assess trade-offs between this functional political normativity and other moral values. I conclude that justice, fairness, freedom and equality remain obviously important concerns, but only once the basic political function is secured. (shrink)

This article discusses the relation between empirical and normative approaches in bioethics. The issue of dwarf tossing, while admittedly unusual, is chosen as a point of departure because it challenges the reader to look with fresh eyes upon several central bioethical themes, including human dignity, autonomy, and the protection of vulnerable people. After an overview of current approaches to the integration of empirical and normative ethics, we consider five ways that the empirical and normative can be brought together to speak (...) to the problem of dwarf tossing: prescriptive applied ethics, theoretical ethics, critical applied ethics, particularist ethics and integrated empirical ethics. We defend a position of critical applied ethics that allows for a two-way relation between empirical and normative theories. Against efforts fully to integrate the normative and the empirical into one synthesis, we propose that the two should stand in tension and relation to one another. The approach we endorse acknowledges that a social practice can and should be judged both by the gathering of empirical data and by normative ethics. Critical applied ethics uses a five stage process that includes: (a) determination of the problem, (b) description of the problem, (c) empirical study of effects and alternatives, (d) normative weighing and (e) evaluation of the effects of a decision. In each stage, we explore the perspective from both the empirical (sociological) and the normative ethical point of view. We conclude by applying our five-stage critical applied ethics to the example of dwarf tossing. (shrink)

This article argues for a new interpretation of the realist claim that politics is autonomous from morality and involves specific political values. First, this article defends an original normative...

This article argues that political realists have at least two strategies to provide distinctively political normative judgements that have nothing to do with morality. The first ground is instrumental normativity, which states that if we believe that something is a necessary means to a goal we have, we have a reason to do it. In politics, certain means are required by any ends we may intend to pursue. The second ground is epistemic normativity, stating that if something is true, this (...) gives us a reason to believe it. In politics, there are certain empirical regularities that ought to be acknowledged for what they are. Both sources are flawed. Instrumental normativity only requires coherence between attitudes and beliefs, and one can hang on to false beliefs to preserve attitudes incompatible with reality. I may desire to eschew power relations, and accordingly I may imagine politics to be like a camping trip. Epistemic normativity, on the other hand, operates critically, striking down existing normative claims. It shows us that politics is nothing like a camping trip, but it doesn’t tell us what we should do about it. We conclude by showing that if the two are taken together, they remedy each other’s flaws. (shrink)

This chapter provides an overview of the basic research strategies and analytic techniques deployed in computational cognitive neuroscience. On the one hand, “top-down” strategies are used to infer, from formal characterizations of behavior and cognition, the computational properties of underlying neural mechanisms. On the other hand, “bottom-up” research strategies are used to identify neural mechanisms and to reconstruct their computational capacities. Both of these strategies rely on experimental techniques familiar from other branches of neuroscience, including functional magnetic resonance imaging, single-cell (...) recording, and electroencephalography. What sets computational cognitive neuroscience apart, however, is the explanatory role of analytic techniques from disciplines as varied as computer science, statistics, machine learning, and mathematical physics. These techniques serve to describe neural mechanisms computationally, but also to drive the process of scientific discovery by influencing which kinds of mechanisms are most likely to be identified. For this reason, understanding the nature and unique appeal of computational cognitive neuroscience requires not just an understanding of the basic research strategies that are involved, but also of the formal methods and tools that are being deployed, including those of probability theory, dynamical systems theory, and graph theory. (shrink)

The concept of dignity is notoriously vague. In this paper it is argued that the reason for this is that there are three versions of dignity that are often confused. First we will take a short look at the history of the concept of dignity in order to demonstrate how already from Roman Antiquity two versions of dignity can be distinguished. Subsequently, the third version will be introduced and it will be argued that although the three versions of dignity hang (...) together, they should also be clearly distinguished in order to avoid confusion. The reason for distinguishing the three versions is because all three of them are only partially effective. This will be demonstrated by taking the discussion about voluntary ‘dying with dignity’ as an example. Inspired by both Paul Ricoeur’s concept of ethics and the ethics of care a proposition will be done as to how the three versions of dignity may sustain each other and help achieve what neither one of the versions can do on its own. (shrink)

In this paper I unpack a realistic conception of politics by tightly defining its constitutive features: conflict and order. A conflict emerges when an actor is disposed to impose his/her views against the resistance of others. Conflicts are more problematic than moralists realize because they emerge unilaterally, are potentially violent, impermeable to content-based reason, and unavoidable. Order is then defined as an institutional framework that provides binding collective decisions. Order is deemed necessary because individuals need to cooperate to survive, but (...) groups cannot spontaneously secure collective decisions and are prone to conflicts. Particularly, the fact that potentially violent conflicts emerge unilaterally means that order requires coercion. I conclude that mischaracterizing conflict and order leads to undesirable normative principles, and that this criticism can be leveraged not only against Rawlsian liberals who moralize conflicts away, but also against some agonists who underestimate the need for order and some communitarians who underplay both circumstances. (shrink)

Este artículo plantea que el concepto de solidaridad, usualmente exaltado en tiempos de crisis, contiene en sí mismo el conjunto de límites que lo debilitan y lo convierten, paradójicamente, en una sutil manifestación del egoísmo. Para analizar esta contradicción, se abordan las posiciones emblemáticas de cinco autores contemporáneos: John Rawls, Richard Rorty, Jürgen Habermas, Charles Taylor y Hannah Arendt. A través de este análisis puede mostrarse que los grandes desafíos de nuestra civilización permiten advertir los dilemas y las contingencias que (...) afectan el nexo entre el liberalismo y la solidaridad. (shrink)

RESUMENEl trabajo critica la fundamentación liberal del a democracia. Por dos razones: la primera, por la imposible defensa de un modelo neutral del estado; y la segunda, por el componente individualista tanto de su epistemología como de su filosofía moral y política, que reduce de modo significativo las posibilidades emancipadoras del proyecto democrático. por último, señala que estos rasgos básicos del a fundamentación liberal se mantienen incluso en una de las versiones del liberalismo social más acordes con la democracia constitucional; (...) el liberalismo político de John Rawls. PALABRAS CLAVELIBERALISMO-DEMOCRACIA LIBERAL- HOBBES-RAWLS- ARENDTABSTRACTThe paper critiques the liberal foundation of democracy. For two reasons: the first, because of the imposible defense of a neutral model of the state; and the second, because of the individualist element both of its epistemology and of its moral and political phiosophy, that reduces significantly the emancipatory chances of the democratic project. Lastly, it points out that these basic features of the liberal foundation even remain in one the versions of liberalism more akin to constitutional democracy: John Rawls' political liberalism.KEYWORDSLIBERALISM-LIBERAL DEMOCRACY-HOBBES-RAWLS-ARENDT. (shrink)

In this note we give two new simple derivations of the “good-cut” equation, the equation which governs (complex) self-dual asymptotically flat gravitational fields. One of these derivations is remarkably simple, involving only a few lines. Our main point of interest, however, is in the second derivation. Though it is slightly more complicated, this method of derivation is almost certainly generalizable to cover real asymptotically flat space-times and thus lead to a generalization of the good-cut equation.

A detailed outline is presented of several convergent points of view connecting the self-dual and anti-self-dual fields with their free data. This is done for the Maxwell and for linearized gravity as exemplifying the approaches. The Sparling equation provides one tool of great power and characterizes one approach. The twistor theory of Penrose yields another equally powerful point of view. The links between these two basic approaches given in this paper provide a unification that allows workers and others with interest (...) in this area to proceed more readily toward the goal of understanding the full nonlinear Einstein equations. (shrink)

Naïve Realism claims that veridical perceptual experiences essentially consist in genuine relations between perceivers and mind-independent objects and their features. The contemporary debate in the philosophy of perception has devoted little attention to assessing one of the main motivations to endorse Naïve Realism–namely, that it is the only view which articulates our ‘intuitive’ conception of perception. In this paper, I first clarify in which sense Naïve Realism is supposed to be ‘naïve’. In this respect, I argue that it is put (...) forward as the only view which can take our introspective knowledge of perception at face value, and I identify the two key features of such introspective knowledge. Second, I challenge the claim that one of these features-namely, that it seems as one could not be in the same perceptual state unless the putative objects of perception existed and were perceived–is introspectively evident. Consequently, I argue that a view of perceptual experience–such as Intentionalism–which denies that this feature is true of perception can still take introspection at face value. This undermines the claim that Naïve Realism is the only account which accommodates our intuitions on the nature of perception. (shrink)

The book is a comprehensive introduction to the work of the Estonian-German biologist Jakob von Uexküll. After a first introductory chapter by Morten Tønnessen and a second chapter on Uexküll's life and philosophical background, it contains four chapters devoted to the analysis of his main works; they are followed by a vast eighth chapter which deals with the influence Uexküll had on other philosophers and scientists, and by a conclusions focused on the possibility of updating Uexküll's work. The monograph combines (...) a careful reconstruction of the historical context in which the Uexküllian concepts emerged (the debate between mechanism and vitalism, contemporary scientific studies) and a thorough analysis of the philosophical contents of the Uexküllian views. As far as the key issue is concerned, Uexküll's notion of Umwelt refers to the perceptive and operative world which surrounds animal species; it is a subjective species-specific construction which provides living organisms with great security and behaviour stability. Moreover, the relationship that the animal carries out with its environment proves to be a complex system of semiotic interactions: its behaviour is not a set of mechanical reactions, but the result of a spontaneous attribution of meaning to the outside world, whose environmental elements are actively interpreted by the subject. The environment of animal species becomes a field of meaning, an exceedingly complex subjective elaboration; this can lessen the distance between animals and men, crediting both with the cognitive ability to grasp meanings and to use signs. (shrink)

In this paper I unpack a realistic conception of politics by tightly defining its constitutive features: conflict and order. A conflict emerges when an actor is disposed to impose his/her views against the resistance of others. Conflicts are more problematic than moralists realize because they emerge unilaterally, are potentially violent, impermeable to content-based reason, and unavoidable. Order is then defined as an institutional framework that provides binding collective decisions. Order is deemed necessary because individuals need to cooperate to survive, but (...) groups cannot spontaneously secure collective decisions and are prone to conflicts. Particularly, the fact that potentially violent conflicts emerge unilaterally means that order requires coercion. I conclude that mischaracterizing conflict and order leads to undesirable normative principles, and that this criticism can be leveraged not only against Rawlsian liberals who moralize conflicts away, but also against some agonists who underestimate the need for order and some communitarians who underplay both circumstances. (shrink)