The relationship between abstract formal procedures and the activities of actual physical systems has proved to be surprisingly subtle and controversial, and there are a number of competing accounts of when a physical system can be properly said to implement a mathematical formalism and hence perform a computation. I defend an account wherein computational descriptions of physical systems are high-level normative interpretations motivated by our pragmatic concerns. Furthermore, the criteria of utility and success vary according to our diverse purposes (...) and pragmatic goals. Hence there is no independent or uniform fact to the matter, and I advance the ‘anti-realist’ conclusion that computational descriptions of physical systems are not founded upon deep ontological distinctions, but rather upon interest-relative human conventions. Hence physical computation is a ‘conventional’ rather than a ‘natural’ kind. (shrink)

This book presents one of the first attempts at developing a precise, grammatically rooted, theory of conversation motivated by data from real conversations. The theory has descriptive reach from the micro-conversational - e.g. self-repair at the word level - to macro-level phenomena such as multi-party conversation and the characterization of distinct conversational genres. It draws on extensive corpus studies of the British National Corpus, on evidence from language acquisition, and on computer simulations of language evolution. The theory provides accounts of (...) the opening, middle game, and closing stages of conversation. it also offers a new perspective on traditional semantic concerns such as quanitifcation and anaphora. The Interactive Stance challenges orthodox views of grammar by aruging that, unless we wish to excluse from analysis a large body of frequently occurrring words and constructions, the right way to construe grammar is as a system that characterizes types of talk in interaction. (shrink)

Electronic computers form an integral part of modern mathematical practice. Several high-profile results have been proven with techniques where computer calculations form an essential part of the proof. In the traditional philosophical literature, such proofs have been taken to constitute a posteriori knowledge. However, this traditional stance has recently been challenged by Mark McEvoy, who claims that computer calculations can constitute a priori mathematical proofs, even in cases where the calculations made by the computer are too numerous to be (...) surveyed by human agents. In this article we point out the deficits of the traditional literature that has called for McEvoy’s correction. We also explain why McEvoy’s defence of mathematical apriorism fails and we discuss how the debate over the epistemological status of computer-assisted mathematics contains several unfortunate conceptual reductions. (shrink)

The computational mind paradigm proposes that the mind is an information-processing system equivalent to a Turing machine. Some proponents of this view hope to emulate the mind using methods such as symbolism, connectionism or more biological models. In the present work, the following question is posed: is a computational mind capable of deciding (yes or no) whether a proposed emulation of the mind is indeed an emulation of the mind? It is argued that this is not possible. Intuitively, (...) the reason a computational mind cannot recognize an emulation of itself is for much the same reason that a set of scales cannot weigh itself. In this article, a formal argument for this stance is given by noticing the following: for a computational mind to recognize an emulation of itself, it must be capable of deciding whether two Turing Machines (namely, itself and the proposed emulation) are functionally equivalent. This task is uncomputable, and thus there cannot exist a computational procedure in the mind that is capable of recognizing an emulation of itself. (shrink)

Our technological lifeworld has become an info-computational media populated by data and algorithms, an artificial environment for life and shared experiences. In this chapter, I tried to sketch three new assumptions for bioethics – it is hardly possible to substantiate ethical guidelines or an idea of normativity in an aprioristic manner; moral status is a function of data entities, not something solely human; agency is plural and thus is shared or sometimes delegated – in order to chart a proposal (...) for a posthuman bioethics. Posthuman is perhaps not the best expression available, but it covers the idea of a shift from a world centered on self-contained and exclusively human agency to a more comprehensive and relational way of thinking. The “posthuman” label should be understood as a rebuttal of biocentrism and anthropocentrism by moving closer to conceptions we encounter in population ethics or in discourse about biosocial and technical systems. Posthuman bioethics is “environmentalist” without losing the humanistic stance. The question regarding how suitable an infocentric bioethics is in practice remains to be settled. The moral principles in bioethics could be reconceived as relying on these new assumptions, in a postindividualistic manner that accepts formal primacy of causal digital artifacts in affording actions in a world of ambient algorithmic intelligence. (shrink)

In philosophical logic and metaphysics there is a long-standing debate around the most appropriate structures to represent indeterministic scenarios concerning the future. We reconstruct here such a debate in a computational setting, focusing on the fundamental difference between moment-based and history-based structures. Our presentation is centered around two versions of an indeterministic scenario in which a programmer wants a machine to perform a given task at some point after a specified time. One of the two versions includes an assumption (...) about the future behaviour of the machine that cannot be encoded in any programming instruction; such version has models over history-based structures but no model over a moment-based structure. Therefore, our work adds a new stance to the debate: moment-based structures can be said to rule out certain indeterministic scenarios that are computationally unfeasible. (shrink)

The “Slicing Problem” is a thought experiment that raises questions for substrate-neutral computational theories of consciousness, including those that specify a certain causal structure for the computation like Integrated Information Theory. The thought experiment uses water-based logic gates to construct a computer in a way that permits cleanly slicing each gate and connection in half, creating two identical computers each instantiating the same computation. The slicing can be reversed and repeated via an on/off switch, without changing the amount of (...) matter in the system. The question is what do different computational theories of consciousness believe is happening to the number and nature of individual conscious units as this switch is toggled. Under a token interpretation, there are now two discrete conscious entities; under a type interpretation, there may remain only one. Both interpretations lead to different implications depending on the adopted theoretical stance. Any route taken either allows mechanisms for “consciousness-multiplying exploits” or requires ambiguous boundaries between conscious entities, raising philosophical and ethical questions for theorists to consider. We discuss resolutions under different theories of consciousness for those unwilling to accept consciousness-multiplying exploits. In particular, we specify three features that may help promising physicalist theories to navigate such thought experiments. (shrink)

Psychologists distinguish between intentional systems which have beliefs and those which are also able to attribute beliefs to others. The ability to do the latter is called having a 'theory of mind', and many cognitive ethologists are hoping to find evidence for this ability in animal behaviour. I argue that Dennett's theory entails that any intentional system that interacts with another intentional system (such as vervet monkeys and chess-playing computers) has a theory of mind, which would make the distinction all (...) but meaningless. This entailment should not be accepted; instead, Dennett's position that intentional behaviour is best predictable via the intentional stance should be rejected in favour of a pluralistic view of behaviour prediction. I introduce an additional method which humans often use to predict intentional and non-intentional behaviour, which could be called the inductive stance. (shrink)

Intentionalism must be distinguished from computational psychology. The former is a mentalist-realist metatheoretical stance vis-a-vis the latter, which is a research programme devoted to the construction of informationally-characterized simulation models for human behavior, perception, cognition, etc. Intentionalism has its attractive aspects, but unfortunately it is plagued by severe conceptual difficulties. Recent attempts to justify the intentionalist interpretation of computational models, by J.A. Fodor and by C. Graves, J.J. Katz et al., fail to secure a conceptually adequate and (...) genuinely intentional sense for the intentional idiom they employ. (shrink)

Interpretation is the process whereby a hearer reasons to an interpretation of a speaker's discourse. The hearer normally adopts a credulous attitude to the discourse, at least for the purposes of interpreting it. That is to say the hearer tries to accommodate the truth of all the speaker's utterances in deriving an intended model. We present a nonmonotonic logical model of this process which defines unique minimal preferred models and efficiently simulates a kind of closed-world reasoning of particular interest for (...) human cognition. Byrne's “suppression” data (Byrne, 1989) are used to illustrate how variants on this logic can capture and motivate subtly different interpretative stances which different subjects adopt, thus indicating where more fine-grained empirical data are required to understand what subjects are doing in this task. We then show that this logical competence model can be implemented in spreading activation network models. A one pass process interprets the textual input by constructing a network which then computes minimal preferred models for (3-valued) valuations of the set of propositions of the text. The neural implementation distinguishes easy forward reasoning from more complex backward reasoning in a way that may be useful in explaining directionality in human reasoning. (shrink)

Interpretation is the process whereby a hearer reasons to an interpretation of a speaker's discourse. The hearer normally adopts a credulous attitude to the discourse, at least for the purposes of interpreting it. That is to say the hearer tries to accommodate the truth of all the speaker's utterances in deriving an intended model. We present a nonmonotonic logical model of this process which defines unique minimal preferred models and efficiently simulates a kind of closed-world reasoning of particular interest for (...) human cognition. Byrne's “suppression” data (Byrne, 1989) are used to illustrate how variants on this logic can capture and motivate subtly different interpretative stances which different subjects adopt, thus indicating where more fine-grained empirical data are required to understand what subjects are doing in this task. We then show that this logical competence model can be implemented in spreading activation network models. A one pass process interprets the textual input by constructing a network which then computes minimal preferred models for (3-valued) valuations of the set of propositions of the text. The neural implementation distinguishes easy forward reasoning from more complex backward reasoning in a way that may be useful in explaining directionality in human reasoning. (shrink)

In recent works, Chomsky has once more endorsed a computational view of rulefollowing, whereby to follow a rule is to operate certain computations on a subject’s mental representations. As is well known, this picture does not conform to what we may call the grammatical conception of rule-following outlined by Wittgenstein, whereby an elucidation of the concept of rule-following is aimed at by isolating grammatical statements regarding the phrase ‘to follow a rule’. As a result, Chomskyan and Wittgensteinian treatments of (...) topics immediately connected with rule-following, namely linguistic competence and understanding, are utterly different from one another. There are two possible stances that computationalists like Chomsky may adopt with regard to the discrepancy between the two aforementioned modes of dealing with rule-following, namely a conciliatory and a non-conciliatory attitude. According to the former attitude, grammatical remarks on and computationallyoriented theories of rule-following investigate one and the same topic although admittedly at different levels, namely a conceptual and an empirical one. According to the latter attitude, grammatical remarks are just a preliminary step in the investigation of rule-following which scientific advancement, presently represented by computationally-oriented theories on this matter, is well entitled to put aside. In what follows, however, I will try to show that both stances are problematic. The conciliatory attitude simply does not work, for it hardly copes with the fact that the concept of rule-following does not supervene, even weakly, on the property of rule-following, namely the property instantiated in the mental/cerebral phenomena that computationally-oriented theories of rule-following study. To take the contrary attitude, on the other hand, is to end up with another disappointing result, namely that the computational treatment of rule-following ultimately deals with something different from that which we wished to gain knowledge of when we began our inquiry into rule-following.. (shrink)

Jablonka & Lamb (J&L) refer only implicitly to aspects of cognitive competence that preceded both evolution of human language and language learning in children. These aspects are important for evolution and development but need to be understood using the design-stance, which the book adopts only for molecular and genetic processes, not for behavioural and symbolic processes. Design-based analyses reveal more routes from genome to behaviour than J&L seem to have considered. This both points to gaps in our understanding of (...) evolution and epigenetic processes and may lead to possible ways of filling the gaps. (shrink)

Artificial agents are progressively becoming more present in everyday-life situations and more sophisticated in their interaction affordances. In some specific cases, like Google Duplex, GPT-3 bots or Deep Mind’s AlphaGo Zero, their capabilities reach or exceed human levels. The use contexts of everyday life necessitate making such agents understandable by laypeople. At the same time, displaying human levels of social behavior has kindled the debate over the adoption of Dennett’s ‘intentional stance’. By means of a comparative analysis of the (...) literature on robots and virtual agents, we defend the thesis that approaching these artificial agents ‘as if’ they had intentions and forms of social, goal-oriented rationality is the only way to deal with their complexity on a daily base. Specifically, we claim that this is the only viable strategy for non-expert users to understand, predict and perhaps learn from artificial agents’ behavior in everyday social contexts. Furthermore, we argue that as long as agents are transparent about their design principles and functionality, attributing intentions to their actions is not only essential, but also ethical. Additionally, we propose design guidelines inspired by the debate over the adoption of the intentional stance. (shrink)

This book examines philosophical and scientific implications of Neodarwinism relative to recent empirical data. It develops explanations of social behavior and cognition through analysis of mental capabilities and consideration of ethical issues. It includes debate within cognitive science among explanations of social and moral phenomena from philosophy, evolutionary and cognitive psychology, neurobiology, linguistics, and computer science. Cognitive Science (CS) provides an original corpus of scholarly work that makes explicit the import of cognitive-science research for philosophical analysis. Topics include the nature, (...) structure, and justification of knowledge, cognitive architectures and development, brain-mind theories, and consciousness. (shrink)

In this book, Dennett determines just how far we can push the idea that mental states are distinguished by intentionality, that is, by the fact that they have content in virtue of being about, or directed towards, the world at large. Intentionality is characteristic of such states as belief and desire, since all belief is belief of something or that something be the case. In contrast to the physical stance and the design stance, the intentional stance is (...) the predictive attitude or strategy philosophers or cognitive scientists adopt when, in order to explain the behavior of a sufficiently complex system, they treat it as if it had beliefs and desires and acted rationally on its beliefs to satisfy its desires. Dennett insists that this stance is essentially a heuristic that informs the formation of scientific theories which are void of mental state terms. For Dennett, the interesting question, whether we are considering mechanical systems, computer systems, enzymes, microorganisms, vervet monkeys, humans, or martians, is just how far should we go in employing the intentional strategy? At what point must we abandon a strict realism about beliefs, desires, and the other concepts of folk psychology? (shrink)

This essay presents arguments for the claim that in the best of all possible worlds (Leibniz) there are sources of unpredictability and creativity for us humans, even given a pancomputational stance. A suggested answer to Chaitin’s questions: “Where do new mathematical and biological ideas come from? How do they emerge?” is that they come from the world and emerge from basic physical (computational) laws. For humans as a tiny subset of the universe, a part of the new ideas (...) comes as the result of the re-configuration and reshaping of already existing elements and another part comes from the outside world as a consequence of openness and interactivity of biological and cognitive systems. For the universe at large it is randomness that is the source of unpredictability on the fundamental level. In order to be able to completely predict the Universe-computer we would need the Universe-computer itself to compute its next state. As Chaitin demonstrated there are incompressible truths, which means truths that cannot be computed by any other computer but the universe itself. (shrink)

Intentionalism must be distinguished from computational psychology. The former is a mentalist-realist metatheoretical stance vis-a-vis the latter, which is a research programme devoted to the construction of informationally-characterized simulation models for human behavior, perception, cognition, etc. Intentionalism has its attractive aspects, but unfortunately it is plagued by severe conceptual difficulties. Recent attempts to justify the intentionalist interpretation of computational models, by J.A. Fodor and by C. Graves, J.J. Katz et al., fail to secure a conceptually adequate and (...) genuinely intentional sense for the intentional idiom they employ. (shrink)

It has been just over 100 years since the birth of Alan Turing and more than 65 years since he published in Mind his seminal paper, Computing Machinery and Intelligence. In the Mind paper, Turing asked a number of questions, including whether computers could ever be said to have the power of “thinking”. Turing also set up a number of criteria—including his imitation game—under which a human could judge whether a computer could be said to be “intelligent”. Turing’s paper, as (...) well as his important mathematical and computational insights of the 1930s and 1940s led to his popular acclaim as the “Father of Artificial Intelligence”. In the years since his paper was published, however, no computational system has fully satisfied Turing’s challenge. In this paper we focus on a different question, ignored in, but inspired by Turing’s work: How might the Artificial Intelligence practitioner implement “intelligence” on a computational device? Over the past 60 years, although the AI community has not produced a general-purpose computational intelligence, it has constructed a large number of important artifacts, as well as taken several philosophical stances able to shed light on the nature and implementation of intelligence. This paper contends that the construction of any human artifact includes an implicit epistemic stance. In AI this stance is found in commitments to particular knowledge representations and search strategies that lead to a product’s successes as well as its limitations. Finally, we suggest that computational and human intelligence are two different natural kinds, in the philosophical sense, and elaborate on this point in the conclusion. (shrink)

This essay presents arguments for the claim that in the best of all possible worlds (Leibniz) there are sources of unpredictability and creativity for us humans, even given a pancomputational stance. A suggested answer to Chaitin’s questions: “Where do new mathematical and biological ideas come from? How do they emerge?” is that they come from the world and emerge from basic physical (computational) laws. For humans as a tiny subset of the universe, a part of the new ideas (...) comes as the result of the re-configuration and reshaping of already existing elements and another part comes from the outside as a consequence of openness and interactivity of the system. For the universe at large it is randomness that is the source of unpredictability on the fundamental level. In order to be able to completely predict the Universe-computer we would need the Universe-computer itself to compute its next state; as Chaitin already demonstrated there are incompressible truths which means truths that cannot be computed by any other computer but the universe itself. (shrink)

(1) Van Gelder's concession that the dynamical hypothesis is not in opposition to computation in general does not agree well with his anticomputational stance. (2) There are problems with the claim that dynamic systems allow for nonrepresentational aspects of computation in a way in which digital computation cannot. (3) There are two senses of the “cognition is computation” claim and van Gelder argues against only one of them. (4) Dynamical systems as characterized in the target article share problems of (...) universal realizability with formal notions of computation, but differ in that there is no solution available for them. (5) The dynamical hypothesis cannot tell us what cognition is, because instantiating a particular dynamical system is neither necessary nor sufficient for being a cognitive agent. (shrink)

Our article examines how journalistic reports and online comments have made sense of computational politics. It treats the discourse around data-driven campaigns as its object of analysis and codifies four main perspectives that have structured the debates about the use of large data sets and data analytics in elections. We study American, British, and German sources on the 2016 United States presidential election, the 2017 United Kingdom general election, and the 2017 German federal election. There, groups of speakers maneuvered (...) between enthusiastic, skeptical, agnostic, or admonitory stances and so cannot be clearly mapped onto these four discursive positions. Coming along with the inconsistent accounts, public sensemaking was marked by an atmosphere of speculation about the substance and effects of computational politics. We conclude that this equivocality helped journalists and commentators to sideline prior reporting on the issue in order to repeatedly rediscover the practices they had already covered. (shrink)

The issue of proper functioning of operative computing and the utility of program verification, both in general and of specific methods, has been discussed a lot. In many of those discussions, attempts have been made to take mathematics as a model of knowledge and certitude achieving, and accordingly infer about the suitable ways to handle computing. I shortly review three approaches to the subject, and then take a stance by considering social factors which affect the epistemic status of both (...) mathematics and computing. I use the analogy between mathematics and computing in reverse—that is to say, I consider operative computing as a form of making mathematics, and so attempt to learn from computing to mathematics in general. I conclude that mathematics engineering is a field to be both developed for practical improvement of doing mathematics and taken into consideration while philosophizing about mathematics as well. (shrink)

One recursively enumerable real α dominates another one β if there are nondecreasing recursive sequences of rational numbers (a[n] : n ∈ ω) approximating α and (b[n] : n ∈ ω) approximating β and a positive constant C such that for all n, C(α − a[n]) ≥ (β − b[n]). See [R. M. Solovay, Draft of a Paper (or Series of Papers) on Chaitin’s Work, manuscript, IBM Thomas J. Watson Research Center, Yorktown Heights, NY, 1974, p. 215] and [G. J. (...) Chaitin, IBM J. Res. Develop., 21 (1977), pp. 350–359]. We show that every recursively enumerable random real dominates all other recursively enumerable reals. We conclude that the recursively enumerable random reals are exactly the Ω-numbers [G. J. Chaitin, IBM J. Res. Develop., 21 (1977), pp. 350–359]. Second, we show that the sets in a universal Martin-Lof test for randomness have random measure, and every recursively enumerable random number is the sum of the measures represented in a universal Martin-Lof test. (shrink)

Since its conception nearly 20 years ago, Logic Programming - the idea of using logic as a programming language - has been developed to the point where it now plays an important role in areas such as database theory, artificial intelligence and software engineering. However, there are still many challenging research issues to be addressed and the UK branch of the Association for Logic Programming was set up to provide a forum where the flourishing research community could discuss important issues (...) of Logic Programming which were often by-passed at the large international conferences. This volume contains the twelve papers which were presented at the ALPUK's 3rd conference which was held in Edinburgh, 10-12 April 1991. The aim of the conference was to give a broad but detailed technical insight into the work currently being done in this field, both in the UK and by researchers as far afield as Canada and Bulgaria. The breadth of interest in this area of Computer Science is reflected in the range of the papers which cover - amongst other areas - massively parallel implementation, constraint logic programming, circuit modelling, algebraic proof of program properties, deductive databases, specialised editors and standardisation. The resulting volume gives a good overview of the current progress being made in the field and will be of interest to researchers and students of any aspects of logic programming, parallel computing or database techniques and management. (shrink)

This book constitutes the strictly refereed post-workshop proceedings of the 11th International Workshop on Computer Science Logic, CSL '97, held as the 1997 Annual Conference of the European Association on Computer Science Logic, EACSL, in Aarhus, Denmark, in August 1997. The volume presents 26 revised full papers selected after two rounds of refereeing from initially 92 submissions; also included are four invited papers. The book addresses all current aspects of computer science logics and its applications and thus presents the state (...) of the art in the area. (shrink)

Computer crime on the Internet poses asignificant threat to the well-being ofbusinesses and individuals, and none are immunefrom the repercussions that can result. Onetype of this unethical and unlawful activity isonline software piracy. In this work, thesignificance of piracy as a topic for academicinquiry is first presented, followed by asummary of the conflicting stances on thisissue. Then, a review of scholarly literaturepreviously conducted in this area is given toprovide a backdrop for the current research. Univariate and bivariate findings from aquantitative (...) study of students are used todemonstrate the incidence, scope, andassociated correlates of Internet piracy in auniversity setting. Technological and ethicalpolicy solutions that an institution mightimplement are suggested and discussed inconclusion. (shrink)

Complexity and Postmodernism explores the notion of complexity in the light of contemporary perspectives from philosophy and science. The book integrates insights from complexity and computational theory with the philosophical position of thinkers including Derrida and Lyotard. Paul Cilliers takes a critical stance towards the use of the analytical method as a tool to cope with complexity, and he rejects Searle's superficial contribution to the debate.

Many materialists believe that we should, in principle, be able to build a conscious computing machine. Others disagree. I favour a sceptical position, but of another variety. The problem isn't that it would be impossible to create a conscious computer. The problem is that we cannot know whether it is possible. There are principled reasons for thinking that we wouldn't ever be able to confirm that allegedly conscious computers were conscious. The proper stance on computational consciousness is agnosticism. (...) Despite this agnosticism, I think we are very close to understanding the material basis of consciousness. Close, but we will never get all the way there. Our understanding of the material basis of consciousness is ineluctably incomplete. That makes me a mysterian. But I am not a defeatist mysterian. I do not think the irresolvable mysteries of consciousness prevent us from formulating concrete empirically grounded theories of consciousness. I will even outline such a theory below. I also think we can identify some properties that are necessary for consciousness, and some that are sufficient. The problem is we cannot find properties that are both. This may sound like a contradiction, but it is not. We can know necessary properties and sufficient properties without knowing necessary and sufficient properties. One can know that drinking two litres of alcohol is sufficient for intoxication, and that at least one teaspoon of alcohol is necessary without knowing the quantity that is both necessary and sufficient. In the case of consciousness, the properties we know to be sufficient are properties that computers lack. The properties we know to be necessary can be possessed by computers, but we don't know whether those properties suffice. We can equip computers with every knowable necessary property and still scratch our heads when asked whether we have managed to create artificial experience. (shrink)

Shanahan’s eloquently argued version of the global workspace theory fits well into the emerging understanding of consciousness as a computational phenomenon. His disinclination toward metaphysics notwithstanding, Shanahan’s book can also be seen as supportive of a particular metaphysical stance on consciousness — the computational identity theory.

The Chinese Room argument is a variant of Turing’s test which enables Searle to defend his biological naturalism, according to which computation is neither sufficient nor constitutive of the mind. In this paper, I examine both strands of his anticomputationalist stance, argue that computation is constitutive of natural language understanding and suggest a path toward the physicalist reduction of intentionality for propositional speech acts.

This book develops a view of logic as a theory of information-driven agency and intelligent interaction between many agents - with conversation, argumentation and games as guiding examples. It provides one uniform account of dynamic logics for acts of inference, observation, questions and communication, that can handle both update of knowledge and revision of beliefs. It then extends the dynamic style of analysis to include changing preferences and goals, temporal processes, group action and strategic interaction in games. Throughout, the book (...) develops a mathematical theory unifying all these systems, and positioning them at the interface of logic, philosophy, computer science and game theory. A series of further chapters explores repercussions of the 'dynamic stance' for these areas, as well as cognitive science. (shrink)

It has been claimed that (1) computer professionals should be held responsible for an undisclosed list of “undesirable events” associated with their work and (2) most if not all computer disasters can be avoided by truly understanding responsibility. Commentators of “A Critique of Positive Responsibility in Computing” argue that this is not Donald Gotterbarn’s view (Gotterbarn, JSEE 14(2):235–239, 2008) but that a critique of the view nevertheless raises significant moral issues within computing such as the ethical goals of a computing (...) profession, the appropriate ethical stance toward bugs, and the public good with respect to computing (Miller, JSEE 14(2):245–249, 2008). Commentators also argue that “A Critique”’s “profitable misreading” demonstrates the “moral ecology” of organizations “dedicated narrowly to financial success” and that other “moral ecologies” that are customer or quality driven can be shown to be more important or preeminent (Huff, JSEE 14(2):241–244, 2008). It is argued here that (1) the hyper-inflated reading of Gotterbarn’s and Ladd’s views on positive responsibility persists despite Gotterbarn’s explicit rejection of it, and that (2) such a reading of positive responsibility cannot be placed within a single moral ecology, nor can a single moral ecology be shown to be any more important or preeminent than others. (shrink)

Big data biology—bioinformatics, computational biology, systems biology (including ‘omics’), and synthetic biology—raises a number of issues for the philosophy of science. This article deals with several such: Is data-intensive biology a new kind of science, presumably post-reductionistic? To what extent is big data biology data-driven? Can data ‘speak for themselves?’ I discuss these issues by way of a reflection on Carl Woese’s worry that “a society that permits biology to become an engineering discipline, that allows that science to slip (...) into the role of changing the living world without trying to understand it, is a danger to itself.” And I argue that scientific perspectivism, a philosophical stance represented prominently by Giere, Van Fraassen, and Wimsatt, according to which science cannot as a matter of principle transcend our human perspective, provides the best resources currently at our disposal to tackle many of the philosophical issues implied in the modeling of complex, multilevel/multiscale phenomena. (shrink)

Philosophical concepts are easier to teach and to learn if students can directly manually and visually manipulate the objects instantiating them. What is needed is a philosophy laboratory in which students learn by experimenting. Games are highly idealized yet concrete structures able to instantiate abstract concepts. I show how to use the Game of Life (a computerized cellular automaton "game") to teach concepts like: individuation; supervenience; the phenomena / noumena distinction; the physical / design / and intentional stances; the argument (...) from design; and models for Leibnizian monads. Such formal games are good ways to use computers to teach philosophy. (shrink)

This paper combines naturalized metaphysics and a philosophical reflection on a recently evolving interdisciplinary branch of quantum chemistry, ab initio molecular dynamics. Bridging the gaps among chemistry, physics, and computer science, this cutting-edge research field explores the structure and dynamics of complex molecular many-body systems through computer simulations. These simulations are allegedly crafted solely by the laws of fundamental physics, and are explicitly designed to capture nature as closely as possible. The models and algorithms employed, however, involve many approximations and (...) significant degrees of idealization of their target systems. Therefore, for philosophers of science the pivotal question of whether relying only on the fundamental laws of physics supports a reductionist or realist stance arises. One conceivable answer to this question is that the irreducible approximations and idealizations support rather anti-realist positions. After reviewing an influential attitude in the philosophy of computer simulations and the debate concerning scientific realism, I offer a fair interpretation of such ab initio modelling in quantum chemistry within a naturalistic metaphysical framework that gives rise to a specific type of ontic structural realism. (shrink)

In recent years, computational sciences such as computational hydrodynamics or computational field theory have supplemented theoretical and experimental investigations in many scientific fields. Often, there is a seemingly fruitful overlap between theory, experiment, and numerics. The computational sciences are highly dynamic and seem a fairly successful endeavor---at least if success is measured in terms of publications or engineering applications. However, for theories, success in application and correctness are two very different things; and just the same may (...) hold for "methodologies" like computer simulations. A lively debate on the epistemic status of computer simulations has thus emerged within the philosophy of science. This paper discusses possible problems when computer simulation and laboratory experiment are intertwined. In present experiments, stochastic methods in the form of Monte Carlo simulations are often involved in generating experimental data. It is questioned as to how far a realistic stance can be maintained when such stochastic elements are involved. Taking experiments in high energy physics as a study case, this paper contends that using these types of entangled material and numerical experiments as a source of new phenomena or for theory testing must presuppose a certain understanding of causality and thus binds us at least to a weak form of realism. (shrink)

From the materialist stance that I find compelling, the metaproblem of consciousness -- explaining why the problem of consciousness seems hard -- is hardly distinct from the 'easy' problem of explaining how the underlying physical/computational system works, and how it gives rise to perceptions of its own functioning. I discuss several confusions that might plausibly arise in that process, and propose that these confusions could create apparent gaps, ontological and epistemic, in materialist accounts of consciousness, thereby making the (...) hard problem hard. Inversely, resolving these confusions may help solve the hard problem. (shrink)

This brief paper aims to underline which are the philosophical limits of mereotopology, when one takes it as a basic unitary theoretical framework for formal ontology. Mereotopology is a first-order theory of the relations among wholes, parts and the boundaries between parts, that combines mereological and topological concepts. Nowadays, with the expression “formal ontology” one intends either the computational (engineering) version, or the philosophical (categorial) one. It is important, then, to avoid terminological confusions. The main philosophical reason that keeps (...) me from developing the connection between computational and philosophical formal ontologies on mereotopological basis is the following: anti-Representationalism and Monism are two ontological stances very difficult to join together, as mereotopology does, if one takes into account the ontological implications of the emerging dynamical dual paradigm in the information theoretic approach to quantum physics. In general, it is this approach to the current fundamental and experimentally extremely successful physical theories about the microphysical realm, namely Quantum Mechanics and Quantum Field Theory, that allows to overcome the “gap” between the two disciplinary fields of formal ontology, making information a physical magnitude. I do not oppose anti-Representationalism, but its connection with the monistic stance, because of the fact that nowadays information appears as a basic component of the microphysical realm just like energy-matter. This fact justifies a realistic but information-matter dual ontology as the proper formal ontology of the emerging paradigm in the information theoretic approach to contemporary quantum physics. The primacy that Aristotle gives to the theory of principle (act/potency) as to the theory of categories is a very helpful tool to solve the main question that arises within a realistic dual ontological theoretical framework: the question of the non-stable nature of the categories, that reflect the increasingly complexity of the physical dynamic realistic orders. Here is the importance of an historical approach to the topic, given also the fact that mereological formal ontology originates with the works of three authors (Bolzano, Brentano, Husserl) that studied, directly or indirectly, Aristotle’s ontology. (shrink)

Modern logic is undergoing a cognitive turn, side-stepping Frege’s ‘antipsychologism’. Collaborations between logicians and colleagues in more empirical fields are growing, especially in research on reasoning and information update by intelligent agents. We place this border-crossing research in the context of long-standing contacts between logic and empirical facts, since pure normativity has never been a plausible stance. We also discuss what the fall of Frege’s Wall means for a new agenda of logic as a theory of rational agency, and (...) what might then be a viable understanding of ‘psychologism’ as a friend rather than an enemy of logical theory. (shrink)

This paper navigates the relationship between the growing influence of Artificial Intelligence (AI) and the foundational principles of academic integrity. It offers an in-depth analysis of how key academic stakeholders—publishers and universities—are crafting strategies and guidelines to integrate AI into the sphere of scholarly work. These efforts are not merely reactionary but are part of a broader initiative to harness AI’s potential while maintaining ethical standards. The exploration reveals a diverse array of stances, reflecting the varied applications of AI in (...) academic settings. These range from conservative approaches emphasizing the need for stringent AI regulations to more progressive strategies that seek to leverage AI’s capabilities. The paper accentuates the importance of guidelines that are adaptable, transparent, and culturally sensitive, acknowledging the global context of academic research. It also highlights the pressing need for effective implementation and enforcement of these guidelines to ensure that the integration of AI into academia does not compromise the integrity of scholarly work. The conclusion emphasizes the dynamic balance required between embracing AI’s transformative potential and upholding the timeless values of academic rigor and ethical research. This comprehensive analysis aims to provide a detailed perspective on the evolving role of AI in academia, fostering a dialog on how best to navigate this new technological frontier while preserving the sanctity of academic scholarship. (shrink)