78 research outputs found

    Quantum physics and consciousness: a (strong) defense of panpsychism

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    Probably the crux of quantum science is the relationship between consciousness and reality. The name for that relation is varied, and points out to a most fundamental problem, namely the possibility to overcome dualism. In science and philosophy at large, determinism and reductionism have already been tackled, if not superseded. The trouble though remains with dualism. This paper argues in favor of a radical relationship between reality and consciousness based on quantum theory. Such a relation is panpsychism, which can be translated and grasped in various other forms. The arguments are provided and some conclusions are drawn

    Integration without Integrated Models or Theories

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    It is traditionally thought that integration in cognitive science requires combining different perspectives, elements, and insights into an integrated model or theory of the target phenomenon. In this paper I argue that this type of integration is frequently not possible in cognitive science due to our reliance on using different idealizing and simplifying assumptions in our models and theories. Despite this, I argue that we can still have integration in cognitive science and attain all the benefits that integrated models would provide, without the need for their construction. Models which make incompatible idealizing assumptions about the target phenomenon can still be integrated by understanding how to draw coherent and compatible inferences across them. I discuss how this is possible, and demonstrate how this supports a different kind of integration. This sense of integration allows us to use collections of contradictory models to develop a consistent, comprehensive and non-contradictory understanding of a single unified phenomenon without the need for a single integrated model or theory

    Unsterblichkeit 2.0

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    Das in diesem Aufsatz vorgebrachte Argumentationsmuster hat folgende Schritte: 1. Der menschliche Geist ist vom Körper nicht trennbar, sie bilden ein Kontinuum. 2. Unser Bewusstsein und alle darauf aufbauenden geistigen PhÀnomene sind die Emanation eines materiellen Prozesses, den ein komplexes System verursacht. 3. Komplexe Systeme lassen sich mathematisch nicht modellieren und nicht kausal verstehen. 4. Computer sind Turing-Maschinen. Sie können nur mathematische Modelle berechnen. Es wird niemals Hyper-Turing Maschinen geben, und wenn es sie gÀbe, könnten sie auch nur mathematische Modelle berechnen. 5. Es ist nicht möglich, den Körper als Substrat des Geistes durch einen Computer zu ersetzen. Die digitale Unsterblichkeit ist demzufolge ein Ding der Unmöglichkeit

    Certifiable AI

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    Implicit stochastic models, including both ‘deep neural networks’ (dNNs) and the more recent unsupervised foundational models, cannot be explained. That is, it cannot be determined how they work, because the interactions of the millions or billions of terms that are contained in their equations cannot be captured in the form of a causal model. Because users of stochastic AI systems would like to understand how they operate in order to be able to use them safely and reliably, there has emerged a new field called ‘explainable AI’ (XAI). When we examine the XAI literature, however, it becomes apparent that its protagonists have redefined the term ‘explanation’ to mean something else, namely: ‘interpretation’. Interpretations are indeed sometimes possible, but we show that they give at best only a subjective understanding of how a model works. We propose an alternative to XAI, namely certified AI (CAI), and describe how an AI can be specified, realized, and tested in order to become certified. The resulting approach combines ontologies and formal logic with statistical learning to obtain reliable AI systems which can be safely used in technical applications

    Not all computational methods are effective methods

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    An effective method is a computational method that might, in principle, be executed by a human. In this paper, I argue that there are methods for computing that are not effective methods. The examples I consider are taken primarily from quantum computing, but these are only meant to be illustrative of a much wider class. Quantum inference and quantum parallelism involve steps that might be implemented in multiple physical systems, but cannot be implemented, or at least not at will, by an idealised human. Recognising that not all computational methods are effective methods is important for at least two reasons. First, it is needed to correctly state the results of Turing and other founders of computation theory. Turing is sometimes said to have offered a replacement for the informal notion of an effective method with the formal notion of a Turing machine. I argue that such a view only holds under limited circumstances. Second, not distinguishing between computational methods and effective methods can lead to mistakes when quantifying over the class of all possible computational methods. Such quantification is common in philosophy of mind in the context of thought experiments that explore the limits of computational functionalism. I argue that these ‘homuncular’ thought experiments should not be treated as valid

    Cosmovisions and Realities - the each one's philosophy

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    Cosmovision is a term that should mean a set of foundations from which emerges a systemic understanding of the Universe, its components as life, the world we live in, nature, the human phenomenon, and their relationships. It is, therefore, a field of analytical philosophy fed by the sciences, whose objective is this aggregated and epistemologically sustainable knowledge about everything that we are and contain, that surrounds us, and that relates to us in any way. It is something as old as human thought and, in addition to using elements of scientific cosmology, it encompasses everything in philosophy and science that refers to the universe and life. A cosmovision is not a set of ideas, hypotheses, and assumptions but a system based on observation, analysis, evidence, and demonstration. No cosmovision intends to define, establish, propose but only understand, analyze and interpret. Each of us builds and transports his cosmovision throughout life, without establishing forms, as a background for our thinking and behavior. Linguistically, the term “cosmovision” would derive from the German, equivalent to the concept of “ Weltanschauung,” as used by several philosophers. However, this linguistic relationship is not applicable because it contradicts what we propose as a cosmovision. This German word refers to a pre-logical or proto- experimental vision of reality, with an intuitive context and far from critical knowledge still non-existent at the time of its formulation. Undoubtedly, cosmovisions, in the sense in which we understand them, house and use these proto-experimental or pre-logical elements that include history, the collective unconscious, and all the archetypes we carry. However, in the concept that we apply here, the cosmovision goes far beyond this content, firstly by constantly submitting it to present critical thinking, and finally by making the analytic experience ( and not the thought itself or intuition) its actual universe. António Lopes expose the breadth of this content: "Cosmovisions are not the product of thought. They do not spring from the simple desire to know. The apprehension of reality is an important moment in its configuration, but, nevertheless, it is only one. It comes from the vital conduct, from the experience of life's evaluation, from the structure of our psychic totality. The elevation of life to consciousness in the knowledge of reality, in the valuation, and in the volitional reality is the slow and arduous work that humanity has done in the development of the conceptions of life. (W. Dilthey, 1992 [1911]: 120)”(1) In this work, we seek to outline a cosmovision based on the realities that science offers today. We do not propose, at any time, to do science; or theorize philosophy, but we will always seek to be supported by them or, at least, protected by them from the cognitive distortions that we usually carry. ________________________________________________ (1) Lopes , Antonio – “ Weltanschauung (Cosmovision)” (2009 ) in Carlos Ceia's E-Dictionary of Literary Terms

    Intuition: The Experience of Formal Research

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    A new concept of Intuition, the Deep Unconscious is considered on the basis of the Paradigm of limiting generalizations. The book describes a high-level sketch. The results of the study can be used in education, economics, medicine, artificial intelligence, and the management of complex systems of various natures

    When No Laughing Matter Is No Laughing Matter: The Challenges in Developing a Cognitive Theory of Humor

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    This paper explores the current obstacles that a cognitive theory of humor faces. More specifically, I argue that the nebulous and ill-defined nature of humor makes it difficult to tell what counts as clear instances of, and deficits in, the phenomenon.Without getting clear on this, we cannot identify the underlying cognitive mechanisms responsible for humor. Moreover, being too quick to draw generalizations regarding the ubiquity of humor, or its uniqueness to humans, without substantially clarifying the phenomenon and its occurrences is not only unwise but can actually be a detriment to our study of humor. As such, these sorts of claims must be resisted. I conclude the paper by pointing the way forward to addressing these obstacles

    Is the church turing thesis a red herring for cognitive science?

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    This paper considers whether computational formalisms beyond the Church Turing Thesis (CTT) could be helpful in understanding the mind. We argue that they may be, and that the way that the CTT has been invoked in Cognitive Science may therefore act as a Red Herring. That is, the way the CTT is invoked in Cognitive Science may mislead and perhaps contribute to premature abandonment of possibly fruitful research directions in Cognitive Science. We do not suggest some sort of “hypercomputation’. Whilst it is possible to use a rich interactive machine to implement a simple function this does not lead to new computable functions. In other words, the CTT is valid even if more sophisticated machinery is employed. It is the other direction that is the core of this paper: When considering more sophisticated computational tasks, then standard Turing machines (and their mode of operation) are not sufficient to explore the range of possibilities. The CTT is commonly interpreted as stating that the intuitive concept of computability is fully captured by Turing machines or any equivalent formalism (such as recursive functions, the lamba calculus, Post production rules, and many others). The CTT implies that if a function is (intuitively) computable, then it can be computed by a Turing machine. Conversely, if a Turing machine cannot compute a function, it is not computable by any mechanism whatsoever. We suggest an inadvertent error that has been made which is the claim that relatively simple computational formalisms like Turing Machines can do anything that more complex computional formalisms can do. To show this we present the landscape of computability within and beyond the bounds covered by the mathematical CTT. This shows that in regions of the computational landscape beyond the CTT there may be hierarchies of increasingly powerful computational formalisms. Erroneously interpreting CTT as enforcing a ‘one size fits all’ interpretation to computational formalisms leads to extreme reductionism that means contemporary computationalism is viewed as inadequate to explaining many phenomena related to thought and mind in living systems. Once this Red Herring interpretation for CTT is avoided this leaves the way open to exploring how richer kinds of computation that may possess many shades of expressivity can form part of Cognitive Science explanations
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