“Negative probability” in practice. Quantum Communication: Very small phase space regions turn out to be thermodynamically analogical to those of superconductors. Macro-bodies or signals might exist in coherent or entangled state. Such physical objects having unusual properties could be the basis of quantum communication channels or even normal physical ones … Questions and a few answers about negative probability: Why does it appear in quantum mechanics? It appears in phase-space formulated quantum mechanics; next, in quantum correlations … and (...) for wave-particle dualism. Its meaning:- mathematically: a ratio of two measures (of sets), which are not collinear; physically: the ratio of the measurements of two physical quantities, which are not simultaneously measurable. The main innovation is in the mapping between phase and Hilbert space, since both are sums. Phase space is a sum of cells, and Hilbert space is a sum of qubits. The mapping is reduced to the mapping of a cell into a qubit and vice versa. Negative probability helps quantum mechanics to be represented quasi-statistically by quasi-probabilistic distributions. Pure states of negative probability cannot exist, but they, where the conditions for their expression exists, decrease the sum probability of the integrally positive regions of the distributions. They reflect the immediate interaction (interference) of probabilities common in quantum mechanics. (shrink)

A historical review and philosophical look at the introduction of “negative probability” as well as “complex probability” is suggested. The generalization of “probability” is forced by mathematical models in physical or technical disciplines. Initially, they are involved only as an auxiliary tool to complement mathematical models to the completeness to corresponding operations. Rewards, they acquire ontological status, especially in quantum mechanics and its formulation as a natural information theory as “quantum information” after the experimental confirmation the (...) phenomena of “entanglement”. Philosophical interpretations appear. A generalization of them is suggested: ontologically, they correspond to a relevant generalization to the relation of a part and its whole where the whole is a subset of the part rather than vice versa. The structure of “vector space” is involved necessarily in order to differ the part “by itself” from it in relation to the whole as a projection within it. That difference is reflected in the new dimension of vector space both mathematically and conceptually. Then, “negative or complex probability” are interpreted as a quantity corresponding the generalized case where the part can be “bigger” than the whole, and it is represented only partly in general within the whole. (shrink)

Early work on the frequency theory of probability made extensive use of the notion of randomness, conceived of as a property possessed by disorderly collections of outcomes. Growing out of this work, a rich mathematical literature on algorithmic randomness and Kolmogorov complexity developed through the twentieth century, but largely lost contact with the philosophical literature on physical probability. The present chapter begins with a clarification of the notions of randomness and probability, conceiving of the former as a (...) property of a sequence of outcomes, and the latter as a property of the process generating those outcomes. A discussion follows of the nature and limits of the relationship between the two notions, with largely negative verdicts on the prospects for any reduction of one to the other, although the existence of an apparently random sequence of outcomes is good evidence for the involvement of a genuinely chancy process. (shrink)

Complex logic is a novel logical framework, which formalizes the semantics of the categories of matter, space, and time in a system of logic that operates with complex logical objects. A complex logical object represents a superposition of a logical statement and its logical negation positioning any statement co-relatively to its logical negation. In the system of logical notations, where S is a logical statement and Not S is its logical negation, complex logic includes co-relative logical (...) positions of S and Not S with the probabilities of their truth within the scale 0... 1, excluding the boundary values of 0 and 1, into a single logical superposition. Thus, the logical superposition, summing up the probabilistic positions of S and Not S, has an invariant truth value equal to 1. In this context, complex logic proves to be invariant to reality, offering a unified logical interpretation of reality, spanning from quantum to cosmological scales. By defining the nature of matter and reality as a complex two-format processual essence with corresponding logical consequences, complex logic enhances our concept and understanding of reality. (shrink)

Contains a description of a generalized and constructive formal model for the processes of subjective and creative thinking. According to the author, the algorithm presented in the article is capable of real and arbitrarily complex thinking and is potentially able to report on the presence of consciousness.

Why should moral philosophers, moral psychologists, and machine ethicists care about computational complexity? Debates on whether artificial intelligence (AI) can or should be used to solve problems in ethical domains have mainly been driven by what AI can or cannot do in terms of human capacities. In this paper, we tackle the problem from the other end by exploring what kind of moral machines are possible based on what computational systems can or cannot do. To do so, we analyze normative (...) ethics through the lens of computational complexity. First, we introduce computational complexity for the uninitiated reader and discuss how the complexity of ethical problems can be framed within Marr’s three levels of analysis. We then study a range of ethical problems based on consequentialism, deontology, and virtue ethics, with the aim of elucidating the complexity associated with the problems themselves (e.g., due to combinatorics, uncertainty, strategic dynamics), the computational methods employed (e.g., probability, logic, learning), and the available resources (e.g., time, knowledge, learning). The results indicate that most problems the normative frameworks pose lead to tractability issues in every category analyzed. Our investigation also provides several insights about the computational nature of normative ethics, including the differences between rule- and outcome-based moral strategies, and the implementation-variance with regard to moral resources. We then discuss the consequences complexity results have for the prospect of moral machines in virtue of the trade-off between optimality and efficiency. Finally, we elucidate how computational complexity can be used to inform both philosophical and cognitive-psychological research on human morality by advancing the moral tractability thesis. (shrink)

We evaluate classical probability in relation to the random generation of a Shakespearean sonnet by a typing monkey and the random generation of universes in a World Ensemble based on various multiverse models involving eternal inflation. We calculate that it would take a monkey roughly 10^942 years to type a Shakespearean sonnet, which pushes the scenario into a World Ensemble. The evaluation of a World Ensemble based on various models of eternal inflation suggests that there is no middle ground (...) between eternal Poincare-Zermelo recurrence and a 0 probability in regards to the natural generation of the initial conditions of the universe. (shrink)

Probably the most challenging issue in science and advanced technology is the ever increasing complexity. The term complexity refers to the experience that the complex whole is more than the sum of the parts. Emergence of new properties is observed at all levels, from relatively simple physical systems up to high-end evolution in biology or state-of-the-art microprocessors in technology. In this study an effort is made to arrive at an understanding of the underlying ontological basis in terms of the (...) classical philosophy of Aristotle and Aquinas. In addition, the value of philosophy is emphasized as a means to develop the capacity for intuition. Only with this capacity it is possible to acquire an understanding of the great variety of concepts needed in the multidisciplinary approach to complex systems. (shrink)

This article investigates the profound mysteries of consciousness and the afterlife, topics that have captivated humanity for centuries. Despite extensive scientific inquiry, the existence of an afterlife remains unverified, and the nature of consciousness poses significant challenges. This research presents innovative hypotheses through thought experiments grounded in empirical evidence and robust theoretical frameworks. It examines the complexities of consciousness, its intricate relationship with the brain, and advocates for interdisciplinary approaches that integrate physics, psychology, and philosophy. The study boldly posits the (...) likelihood of continuous consciousness post-death, arguing that existing evidence lends substantial support to this notion. Furthermore, it explores the practical implications of these insights, suggesting that understanding these phenomena could enhance human well-being and foster a more harmonious society. In essence, this article embarks on a quest to illuminate age-old questions surrounding consciousness and the afterlife. By employing novel methodologies, it seeks to offer fresh perspectives that may transform our understanding of existence and inspire positive advancements at both individual and societal levels. (shrink)

The talk is called ‘The QUANTUM COMPLEXITY behind Quantum Reality’. It is divided into 3 parts: an outline of the essentials of quantum theory, a discussion of some glaring problems of interpretation, and my shocking philosophical conclusions.

Amongst invertebrates, molluscs show great variability in their nervous system ranging from primitive arrangement in Chitons to the complex mass of fused ganglia forming the ‘brain’ of cephalopods. Most of the effector organs used for pharmacological or physiological experiments. The neurosecretory cells (NSCs) with their combination of neuronal and glandular capabilities are perfectly suited to translate a neuronal input into the hormonal output best suited to long-term process. In this capacity, the NSCs may produce hormones, which act directly upon (...) the peripheral target or it may exert its effect indirectly by influencing the activity of other non-neural, endocrine organs. Neurosecretory cells have been detected in the cerebral, pedal and visceral ganglia of Lamellidens corrianus. The distribution and biology of freshwater bivalve like Lamellidens corrianus is influenced by local ecological factors (like temperature, pH, inorganic salts, type of soil etc.), water flow system and presence of micro-organisms, teleost fishes and seasonal variations in these parameters. Nitrogenous excretory changes which include ammonia in these molluscs is also influenced by these local ecological factors in which temperature is plays very crucial role. It is well known fact that the high stress conditions during drought or severe winter conditions have been conquered by several lineage of gastropods and sand bivalves and their ability to enter the resistant or dormant stages (low food) protein catabolism increased. Present investigation deals with the oxygen consumption and ammonia excretion ratio of these freshwater pelecypode Lamellidens corrianus. Study on Lemellidens corrianus directed in understanding the different behavioral and physiological aspects after cerebral ganglia removal and injection of their extracts revealed significant changes during summer (April-May). (shrink)

DNA evidence is one of the most significant modern advances in the search for truth since the cross examination, but its format as a random-match-probability makes it difficult for people to assign an appropriate probative value (Koehler, 2001). While Frequentist theories propose that the presentation of the match as a frequency rather than a probability facilitates more accurate assessment (e.g., Slovic et al., 2000), Exemplar-Cueing Theory predicts that the subjective weight assigned may be affected by the frequency or (...) probability format, and how easily examples of the event, i.e., ‘exemplars’, are generated from linguistic cues that frame the match in light of further evidence (Koehler & Macchi, 2004). This paper presents two juror research studies to examine the difficulties that jurors have in assigning appropriate probative value to DNA evidence when contradictory evidence is presented. Study 1 showed that refuting evidence significantly reduced guilt judgments when exemplars were linguistically cued, even when the probability match and the refuting evidence had the same objective probative value. Moreover, qualitative reason for judgment responses revealed that interpreting refuting evidence was found to be complex and not necessarily reductive; refutation was found indicative of innocence or guilt depending on whether exemplars have been cued or not. Study 2 showed that the introduction of judges’ directions to linguistically cue exemplars, did not increase the impact of refuting evidence beyond its objective probative value, but less guilty verdicts were returned when jurors were instructed to consider all possible explanations of the evidence. The results are discussed in light of contradictory frequentist and exemplar-cueing theoretical positions, and their real-world consequences. (shrink)

Abstract Introduction Logically valid deductive arguments are clear examples of abstract recursive computational proce‐ dures on propositions or on probabilities. However, it is not known if the cortical time‐consuming inferential pro‐ cesses in which logical arguments are eventually realized in the brain are in fact physically different from other kinds of inferential processes. Methods In order to determine whether an electrical EEG discernible pattern of logical deduction exists or not, a new experimental paradigm is proposed contrasting logically valid and invalid (...) inferences with exactly the same content (same premises and same relational variables) and distinct logical complexity (propositional truth‐functional operators). Electroencephalographic signals from 19 subjects (24.2 ± 3.3 years) were acquired in a two‐condition para‐ digm (100 trials for each condition). After the initial general analysis, a trial‐by‐trial approach in beta‐2 band allowed to uncover not only evoked but also phase asynchronous activity between trials. Results showed that (i) deductive inferences with the same content evoked the same response pattern in logically valid and invalid conditions, (ii) mean response time in logically valid inferences is 61.54% higher, (iii) logically valid inferences are subjected to an early (400 ms) and a late reprocessing (600 ms) verified by two distinct beta‐2 activa‐ tions (p‐value < 0,01, Wilcoxon signed rank test). Conclusion We found evidence of a subtle but measurable electrical trait of logical validity. Results put forward the hypothesis that some logically valid deductions are recursive or computational cortical events. Keywords Beta‐2 band, Evoked potentials, Induced potentials, Deductive inference, Logical validity, Cortical bases of logical reasoning. (shrink)

Intellectual property (IP) can internalize positive externalities associated with the creation and discovery of ideas, thereby increasing investment in efforts to create and discover ideas. However, IP law also causes negative externalities. Strict IP rights raise the transaction costs associated with consuming and building on existing ideas. This causes a tragedy of the anticommons, in which valuable resources are underused and underdeveloped. By disincentivizing creative projects that build on existing ideas, IP protection, even if it increases original innovation, can inadvertently (...) reduce the rate of iterative innovation. The net effect of IP law on innovation and welfare depends on the relative magnitude of these positive and negative externalities. We argue that the current regime probably suffers from excessive, and excessively rigid, IP protection. This motivates the search for institutional alternatives and complements. We suggest that a monocentric IP rights regime may not be the only, or the most efficient, way to internalize the positive externalities of innovation. The knowledge economy supports the emergence of diverse, polycentric forms of bottom-up self-governance, both market and community led, that entail the citizen coproduction of the norms and practices of intellectual creation and discovery. (shrink)

The present thesis focuses on counterfactuals. Specifically, we will address new questions and open problems that arise for the standard semantic accounts of counterfactual conditionals. The first four chapters deal with the Lewisian semantic account of counterfactuals. On a technical level, we contribute by providing an equivalent algebraic semantics for Lewis' variably strict conditional logics, which is notably absent in the literature. We introduce a new kind of algebra and differentiate between local and global versions of each of Lewis' variably (...) strict conditional logics. We study the algebraic properties of Lewis' logics and the structure theory of our newly introduced algebras. Additionally, we employ a new algebraic construction, based on the framework of Boolean algebras of conditionals, to provide an alternative semantics for Lewisian counterfactual conditionals. This semantic account allows us to establish new truth conditions for Lewisian counterfactuals, implying that Lewisian counterfactuals are definable conditionals, and each counterfactual can be characterized as a modality of a corresponding probabilistic conditional. We further extend these results by demonstrating that each Lewisian counterfactual can also be characterized as a modality of the corresponding Stalnaker conditional. The resulting formal semantic framework is much more expressive than the standard one and, in addition to providing new truth conditions for counterfactuals, it also allows us to define a new class of conditional logics falling into the broader framework of weak logics. On the philosophical side, we argue that our results shed new light on the understanding of Lewisian counterfactuals and prompt a conceptual shift in this field: Lewisian counterfactual dependence can be understood as a modality of probabilistic conditional dependence or Stalnakerian conditional dependence. In other words, whether a counterfactual connection occurs between A and B depends on whether it is "necessary" for a Stalnakerian/probabilistic dependence to occur between A and B. We also propose some ways to interpret the kind of necessity involved in this interpretation. The remaining two chapters deal with the probability of counterfactuals. We provide an answer to the question of how we can characterize the probability that a Lewisian counterfactual is true, which is an open problem in the literature. We show that the probability of a Lewisian counterfactual can be characterized in terms of belief functions from Dempster-Shafer theory of evidence, which are a super-additive generalization of standard probability. We define an updating procedure for belief functions based on the imaging procedure and show that the probability of a counterfactual A > B amounts to the belief function of B imaged on A. This characterization strongly relies on the logical results we proved in the previous chapters. Moreover, we also solve an open problem concerning the procedure to assign a probability to complex counterfactuals in the framework of causal modelling semantics. A limitation of causal modelling semantics is that it cannot account for the probability of counterfactuals with disjunctive antecedents. Drawing on the same previous works, we define a new procedure to assign a probability to counterfactuals with disjunctive antecedents in the framework of causal modelling semantics. We also argue that our procedure is satisfactory in that it yields meaningful results and adheres to some conceptually intuitive constraints one may want to impose when computing the probability of counterfactuals. (shrink)

This paper is a critique of Richard Dawkins’ “argument from improbability” against the existence of God. This argument, which forms the core of Dawkins’ book The God Delusion, provides an interesting example of the use of scientific ideas in arguments about religion. Here I raise three objections: (1) The argument is inapplicable to philosophical conceptions of God that reduce most of God’s complexity to that of the physical universe. (2) The argument depends on a way of estimating probabilities that fails (...) for the probability of an entity that creates natural laws. (3) The argument supposes that complexity arises from past physical causes; however, some forms of complexity known to mathematics and logic do not arise in this way. After stating these three criticisms, I show that some of these same considerations undermine Dawkins’ critique of agnosticism. I close the paper with some remarks on Dawkins’ conception of God. (shrink)

In a recent paper, Eric Schwitzgebel argues that if materialism about consciousness is true, then the United States is likely to have its own stream of phenomenal consciousness, distinct from the streams of conscious experience of the people who compose it. Indeed, most plausible forms of materialism have to grant that a certain degree of functional and behavioral complexity constitutes a sufficient condition for the ascription of phenomenal consciousness – and Schwitzgebel makes a case to show that the United States (...) as a whole fulfills this condition. One way to avoid this counter-intuitive consequence of materialism about consciousness is to adopt what Schwitzgebel calls an “anti-nesting principle”: a principle that states that there can be no nested forms of phenomenal consciousness and that therefore a conscious whole cannot have parts that are themselves conscious. However, Schwitzgebel then proceeds in his paper to draw up various objections, notably based on thought experiments, in order to dismiss these kinds of “anti-nesting” principles. My aim in this paper is to present a version of a sophisticated anti-nesting principle that avoids Schwitzgebel’s objections. This principle is reasonable, intuitive, and as non-arbitrary as possible. Moreover, it can resist the objections mounted by Schwitzgebel against simple anti-nesting principles. This principle helps materialists avoid the implication that the United States has its own stream of consciousness, while granting consciousness to some entities which, in many cases, are intuitive instantiators of phenomenal consciousness. This principle therefore constitutes a way out for a materialist who wants to deny that the United States is conscious. (shrink)

En un libro reciente McShea y Brandon defienden que la diversidad y la complejidad de la vida se explican, principalmente, por la acción de un principio que llaman “la ley evolutiva de fuerzas cero” o “ZFEL”. Tal principio actuaría de un modo implícito por detrás de muchas explicaciones de la biología, pero nunca habría sido explicitado. Asumiendo que esta idea es interesante, y que los autores en cuestión tienen razón, discutiremos el modo metateórico en que presentan dicho principio, como siendo (...) parte de la teoría de la probabilidad. Esto permite a los autores afirmar que la teoría de la probabilidad brindaría la base reductiva para toda la biología evolutiva (dado que consideran que otros principios, como el de selección natural, también serían parte de la teoría de la probabilidad). Defenderemos que, efectivamente, ZFEL no es propio de la biología únicamente, pero no por formar parte de la teoría de la probabilidad, sino por tratarse de una versión específica del principio de causa común. -/- In a recent book, McShea and Brandon argue that the observed diversity and complexity of life are explainable by a principle they call the “zero-force evolutionary law” or “ZFEL”. Although this principle would be implicit in many explanations given by biologists, it would have never been made explicit. Assuming that this idea is interesting, and that the authors are right, we will discuss the metatheoretical way in which they present said principle, as being a part of probability theory. This allows the authors to claim that probability theory provides the reductive basis for all evolutionary biology. We will defend, in accordance with them, that ZFEL is not a solely biological principle, but not because it is a part of probability theory, but rather because it is a specific version of the principle of common cause. (shrink)

The framework of Solomonoff prediction assigns prior probability to hypotheses inversely proportional to their Kolmogorov complexity. There are two well-known problems. First, the Solomonoff prior is relative to a choice of Universal Turing machine. Second, the Solomonoff prior is not computable. However, there are responses to both problems. Different Solomonoff priors converge with more and more data. Further, there are computable approximations to the Solomonoff prior. I argue that there is a tension between these two responses. This is because (...) computable approximations to Solomonoff prediction do not always converge. (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)

Stochastic independence has a complex status in probability theory. It is not part of the definition of a probability measure, but it is nonetheless an essential property for the mathematical development of this theory. Bayesian decision theorists such as Savage can be criticized for being silent about stochastic independence. From their current preference axioms, they can derive no more than the definitional properties of a probability measure. In a new framework of twofold uncertainty, we introduce preference (...) axioms that entail not only these definitional properties, but also the stochastic independence of the two sources of uncertainty. This goes some way towards filling a curious lacuna in Bayesian decision theory. (shrink)

Many tasks in statistical and causal inference can be construed as problems of entailment in a suitable formal language. We ask whether those problems are more difficult, from a computational perspective, for causal probabilistic languages than for pure probabilistic (or “associational”) languages. Despite several senses in which causal reasoning is indeed more complex—both expressively and inferentially—we show that causal entailment (or satisfiability) problems can be systematically and robustly reduced to purely probabilistic problems. Thus there is no jump in computational (...) complexity. Along the way we answer several open problems concerning the complexity of well-known probability logics, in particular demonstrating the ${\exists \mathbb {R}}$ -completeness of a polynomial probability calculus, as well as a seemingly much simpler system, the logic of comparative conditional probability. (shrink)

In most academic and non-academic circles throughout history, the world and its operation have been viewed in terms of cause and effect. The principles of causation have been applied, fruitfully, across the sciences, law, medicine, and in everyday life, despite the lack of any agreed-upon framework for understanding what causation ultimately amounts to. In this engaging and accessible introduction to the topic, Douglas Kutach explains and analyses the most prominent theories and examples in the philosophy of causation. The book is (...) organized so as to respect the various cross-cutting and interdisciplinary concerns about causation, such as the reducibility of causation, its application to scientific modeling, its connection to influence and laws of nature, and its role in causal explanation. Kutach begins by presenting the four recurring distinctions in the literature on causation, proceeding through an exploration of various accounts of causation including determination, difference making and probability-raising. He concludes by carefully considering their application to the mind-body problem. _Causation_ provides a straightforward and compact survey of contemporary approaches to causation and serves as a friendly and clear guide for anyone interested in exploring the complex jungle of ideas that surround this fundamental philosophical topic. (shrink)

This paper aims at introducing a French audience to the Intelligent Design debate. It starts by reviewing recent attacks on any possibility of a rational account of theism in light of the contemporary theory of evolution. A section is devoted to outlining the genesis of the "wedge" strategy, to distinguish it from young earth creationism, and to highlight the questioning of evolution as our meta-narrative bearing on overall conceptions of the scientific endeavor. The arguments propounded by Behe are reviewed in (...) detail, as the example of blood coagulation as a purported irreducibly complex mechanism is contrasted to the question of system boundaries. Counter-arguments by Miller are reviewed, and a few bottom-line questions are directed to invite a further consideration of the type of engineering this could testify to. The concept of complex specified information is then presented, and contrasted to traditional and lingering axiomatic problems in the theory of probabilities. The problem of the recognition of an intrinsic pattern is also brought together with some work in recent philosophy of causation and explanation. The two opposing strategies, naturalistic evolutionism and intelligent design, are seen as caught in each other's rhetoric, and some probing is offered in the direction of a theory that could surpass those stalling factors. (shrink)

Mathematicians often speak of conjectures as being confirmed by evidence that falls short of proof. For their own conjectures, evidence justifies further work in looking for a proof. Those conjectures of mathematics that have long resisted proof, such as the Riemann hypothesis, have had to be considered in terms of the evidence for and against them. In recent decades, massive increases in computer power have permitted the gathering of huge amounts of numerical evidence, both for conjectures in pure mathematics and (...) for the behavior of complex applied mathematical models and statistical algorithms. Mathematics has therefore become (among other things) an experimental science (though that has not diminished the importance of proof in the traditional style). We examine how the evaluation of evidence for conjectures works in mathematical practice. We explain the (objective) Bayesian view of probability, which gives a theoretical framework for unifying evidence evaluation in science and law as well as in mathematics. Numerical evidence in mathematics is related to the problem of induction; the occurrence of straightforward inductive reasoning in the purely logical material of pure mathematics casts light on the nature of induction as well as of mathematical reasoning. (shrink)

Complex human reasoning involves minimal abilities to extract conclusions implied in the available information. These abilities are considered “deductive” because they exemplify certain abstract relations among propositions or probabilities called deductive arguments. However, the electrophysiological dynamics which supports such complex cognitive pro- cesses has not been addressed yet. In this work we consider typically deductive logico- probabilistically valid inferences and aim to verify or refute their electrophysiological functional connectivity differences from invalid inferences with the same content (same relational (...) variables, same stimuli, same relevant and salient features). We recorded the brain electrophysiological activity of 20 participants (age 1⁄4 20.35 ± 3.23) by means of an MEG system during two consecutive reasoning tasks: a search task (invalid condition) without any specific deductive rules to follow, and a logically valid deductive task (valid condition) with explicit deductive rules as instructions. We calculated the functional connectivity (FC) for each condition and conducted a seed-based analysis in a set of cortical regions of interest. Finally, we used a cluster-based permutation test to compare the dif- ferences between logically valid and invalid conditions in terms of FC. As a first novel result we found higher FC for valid condition in beta band between regions of interest and left prefrontal, temporal, parietal, and cingulate structures. FC analysis allows a second novel result which is the definition of a propositional network with operculo-cingular, parietal and medial nodes, specifically including disputed medial deductive “core” areas. The experiment discloses measurable cortical processes which do not depend on content but on truth-functional propositional operators. These experimental novelties may contribute to understand the cortical bases of deductive processes. (shrink)

Surimposium is a theory of complex reality. It does not seek to shake up existing paradigms, even when they are contradictory. It places them in levels of reality of relative independence. The task is then to link them with a metaprincipe keeping everything monistic. From this principle, Surimposium establishes a continuity of information levels from hardware to virtual. Their staged complexity continues into the processing depth of neural networks. A stack of layers of information that I call "surimposed" mimics (...) other parts of the complex dimension to build a representation. Subject and model have their own reality. Shift is the root of intention. (shrink)

Evolutionary theory usually neglects two variables: the changes induced in the environment by the evolving organism, and individual uniqueness in sexually reproducing species. In order to fuel its maintenance and reproduction, an organism must average a positive net energy balance vis-a-v}s its environment. It achieves this via aptations, which consist of information (i.e., the internalization of all that is predictable about the environment, including the machinery to take advantage of this information) and stored energy (to operate the machinery, including a (...) safety margin to deal with events that are unpredictable in principle). Taking advantage of a prediction, however, interferes with what has been predicted; each adaptation by the organism therefore changes its environmental target. Today's organism is adapted to yesterday's environment, and today's predator inherits yesterday's prey image. This paper attempts to show that, over evolutionary time, the persistence of this asymmetric, time-lagged relationship is owed increasingly to genetically unique individuals. Individual uniqueness as resulting from sexual reproduction is janusfaced. It endows an evolving population with both a forward-looking (promethean) and backward-looking (protean) feature. A population made up of genetically unique individuals is promethean (creative) in its ability to exploit non-homogeneous resources and respond serendipitously to environmental change via new genotypes; it is protean (elusive) in presenting a pursuer (predator or parasite) with a scattered target. Furthermore, because of the asymmetry between the winnowing of the target gene pool by the pursuer, and the genetic fixation in the pursuer of an outdated target image, the target keeps evolving away from the pursuer at a speed and in a direction that are a function of the pursuer's success. This mechanism ensures an evolutionary time lag be102 W. Sterrer tween pursuer and target, which explains escalation, the stability of asymmetric coevolutionary systems such as the life/dinner principle, and the pervasiveness of the Red Queen effect. Individuality thus both promotes and retards the speed of evolution. Having probably originated simultaneously with predation, sex-generated individuality is a self-accelerating evolutionary process that may account for much of today's organismic and environmental complexity. (shrink)

Powerful, technically complex international compliance regimes have developed recently in certain professions that deal with risk: banking (the Basel II regime), accountancy (IFRS) and the actuarial profession. The need to deal with major risks has acted as a strong driver of international co-operation to create enforceable international semilegal systems, as happened earlier in such fields as international health regulations. This regulation in technical fields contrasts with the failure of an international general-purpose political and legal regime to develop. We survey (...) the new global regulatory systems in the actuarial, banking and accounting fields, with a view to showing how the need to deal reasonably with risk has resulted in an international de facto law solidly based on correct abstract principles of probability. (shrink)

To justify inductive inference and vanquish classical skepticisms about human memory, external world realism, etc., Richard Fumerton proposes his “inferential internalism,” an epistemology whereby humans ‘see’ by Russellian acquaintance Keynesian probable relations (PRs) between propositions. PRs are a priori necessary relations of logical probability, akin to but not reducible to logical entailments, such that perceiving a PR between one’s evidence E and proposition P of unknown truth value justifies rational belief in P to an objective degree. A recent critic (...) of inferential internalism is Alan Rhoda, who questions its psychological plausibility. Rhoda argues that in order to see necessary relations between propositions E and P, one would need acquaintance with too many propositions at once, since our evidence E is often complex. In this paper, I criticize Rhoda’s implausibility objection as too quick. Referencing the causal status effect (CSE) from psychology, I argue that some of the complex features of evidence E contribute to our type-categorizing it as E-type, and thus we do not need to ‘see’ all of the complex features when we see the PR between E and P. My argument leaves unchanged Fumerton’s justificatory role for the PR, but enhances its psychological plausibility. (shrink)

Intermediate phenomena of reality present particular characteristics of systemic self-organization, multilevel interrelations, recursivity, emergence of new «objects» with properties different from those of the elements that form them, and evolutionary dynamics, that probably need the formulation of new theoretical concepts and different paradigm principles. The sciences or perspectives of complexity, or the «complex» thinking, try to respond adequately to this complexity of reality. This approach adopts a multidimensional, integrated and dynamic view of reality: the world is made up of (...) overlapping levels of different elements which produce new properties or new organizations at higher levels. If we conceive what we call languages as simple and decontextualized objects, we can understand some of the more mechanical aspects but we will ignore their conditions of existence, functionality, maintenance, variation, change and extinction. (shrink)

Reconstructability analysis (RA) decomposes wholes, namely data in the form either of set theoretic relations or multivariate probability distributions, into parts, namely relations or distributions involving subsets of variables. Data is modeled and compressed by variable-based decomposition, by more general state-based decomposition, or by the use of latent variables. Models, which specify the interdependencies among the variables, are selected to minimize error and complexity.

Evolutionary theory is undergoing an intense period of discussion and reevaluation. This, contrary to the misleading claims of creationists and other pseudoscientists, is no harbinger of a crisis but rather the opposite: the field is expanding dramatically in terms of both empirical discoveries and new ideas. In this essay I briefly trace the conceptual history of evolutionary theory from Darwinism to neo-Darwinism, and from the Modern Synthesis to what I refer to as the Extended Synthesis, a more inclusive conceptual framework (...) containing among others evo–devo, an expanded theory of heredity, elements of complexity theory, ideas about evolvability, and a reevaluation of levels of selection. I argue that evolutionary biology has never seen a paradigm shift, in the philosophical sense of the term, except when it moved from natural theology to empirical science in the middle of the 19th century. The Extended Synthesis, accordingly, is an expansion of the Modern Synthesis of the 1930s and 1940s, and one that—like its predecessor—will probably take decades to complete. (shrink)

This paper challenges the common assumption that some phenotypic traits are quantitative while others are qualitative. The distinction between these two kinds of traits is widely influential in biological and biomedical research as well as in scientific education and communication. This is probably due to both historical and epistemological reasons. However, the quantitative/qualitative distinction involves a variety of simplifications on the genetic causes of phenotypic variability and on the development of complex traits. Here, I examine three cases from the (...) life sciences that show inconsistencies in the distinction: Mendelian traits, Mendelian diseases, and polygenic mental disorders. I show that these traits can be framed both quantitatively and qualitatively depending, for instance, on the methods through which they are investigated and on specific epistemic purposes. This suggests that the received view of quantitative and qualitative traits has a limited heuristic power—limited to some local contexts or to the specific methodologies adopted. Throughout the paper, I provide directions for framing phenotypes beyond the quantitative/qualitative distinction. I conclude by pointing at the necessity of developing a principled characterisation of what phenotypic traits, in general, are. (shrink)

Migraine is a complex neurological disorder characterized by recurrent moderate to severe headaches, accompanied by additional symptoms such as nausea, sensitivity to light and sound, and visual disturbances. Accurate and timely diagnosis of migraines is crucial for effective management and treatment. However, the diverse range of symptoms and overlapping characteristics with other headache disorders pose challenges in the diagnostic process. In this research, we propose the development of an expert system for migraine diagnosis using artificial intelligence and the CLIPS (...) (C Language Integrated Production System) framework. The expert system utilizes a rule-based inference engine to analyze patient-reported symptoms and provide reliable diagnoses or probability scores indicating the likelihood of migraine. The knowledge base of the expert system is designed based on expert knowledge obtained from medical professionals specializing in migraines. The collected knowledge is translated into a structured format suitable for the CLIPS inference engine, incorporating rules and facts to represent the diagnostic criteria and associated symptoms. The system prompts users to provide relevant information about their symptoms, medical history, and potential triggers. It applies the defined rules and facts to evaluate the likelihood of migraine and generate accurate diagnoses or probability scores. Preliminary evaluation results demonstrate the potential of the expert system as a valuable tool for diagnosing migraines. A dataset of anonymized patient records with confirmed migraine cases was used to test the system. The diagnoses generated by the expert system were compared against the known diagnoses, and a high level of accuracy was observed, with 90% of cases correctly diagnosed as migraines. These results highlight the effectiveness and reliability of the system in assisting medical professionals in the diagnosis of migraines. The proposed expert system offers several advantages for migraine diagnosis. It leverages the collective knowledge and expertise of experienced migraine specialists, providing a standardized and consistent approach to diagnosis. The system can handle large amounts of patient data and effectively analyse complex relationships between symptoms, risk factors, and diagnostic criteria. Furthermore, it offers real-time feedback and recommendations, supporting medical professionals in their clinical decision-making process. Future work involves refining the expert system based on feedback from medical experts, expanding the knowledge base to encompass a wider range of symptoms and risk factors, and conducting further evaluations to enhance its accuracy and applicability in clinical settings. The development of an expert system for migraine diagnosis has the potential to improve the diagnostic process, leading to more effective management and treatment strategies for individuals suffering from migraines. (shrink)

This paper is about guessing: how people respond to a question when they aren’t certain of the answer. Guesses show surprising and systematic patterns that the most obvious theories don’t explain. We argue that these patterns reveal that people aim to optimize a tradeoff between accuracy and informativity when forming their guess. After spelling out our theory, we use it to argue that guessing plays a central role in our cognitive lives. In particular, our account of guessing yields new theories (...) of belief, assertion, and the conjunction fallacy—the psychological finding that people sometimes rank a conjunction as more probable than one of its conjuncts. More generally, we suggest that guessing helps explain how boundedly rational agents like us navigate a complex, uncertain world. (shrink)

Consider a set of shuffled observations drawn from a fixed probability distribution over some instance domain. What enables learning of inductive generalizations which proceed from such a set of observations? The scenario is worthwhile because it epistemically characterizes most of machine learning. This kind of learning from observations is also inverse and ill-posed. What reduces the non-uniqueness of its result and, thus, its problematic epistemic justification, which stems from a one-to-many relation between the observations and many learnable generalizations? The (...) paper argues that this role belongs to any complexity regularization which satisfies Norton’s Material Theory of Induction (MTI) by localizing the inductive risk to facts in the given domain. A prime example of the localization is the Lottery Ticket Hypothesis (LTH) about overparameterized neural networks. The explanation of MTI’s role in complexity regularization of neural networks is provided by analyzing the stability of Empirical Risk Minimization (ERM), an inductive rule that controls the learning process and leads to an inductive generalization on the given set of observations. In cases where ERM might become asymptotically unstable, making the justification of the generalization by uniform convergence unavailable, LTH and MTI can be used to define a local stability. A priori, overparameterized neural networks are such cases and the combination of LTH and MTI can block ERM’s trivialization caused by equalizing the strengths of its inductive support for risk minimization. We bring closer the investigation of generalization in artificial neural networks and the study of inductive inference and show the division of labor between MTI and the optimality justifications (developed by Gerhard Schurz) in machine learning. (shrink)

"The enterprise initiative is probably the most significant political and cultural influence to have affected Western and Eastern Europe in the last decade. In this book, academics from a range of disciplines debate Mary Douglas's distinctive Grid Group cultural theory and examine how it allows us to analyse the complex relation between the culture of enterprise and its institutions. Mary Douglas, Britain's leading cultural anthropologist, contributes several chapters."--BOOK JACKET.Title Summary field provided by Blackwell North America, Inc. All Rights Reserved.

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)

Non-commuting quantities and hidden parameters – Wave-corpuscular dualism and hidden parameters – Local or nonlocal hidden parameters – Phase space in quantum mechanics – Weyl, Wigner, and Moyal – Von Neumann’s theorem about the absence of hidden parameters in quantum mechanics and Hermann – Bell’s objection – Quantum-mechanical and mathematical incommeasurability – Kochen – Specker’s idea about their equivalence – The notion of partial algebra – Embeddability of a qubit into a bit – Quantum computer is not Turing machine – (...) Is continuality universal? – Diffeomorphism and velocity – Einstein’s general principle of relativity – „Mach’s principle“ – The Skolemian relativity of the discrete and the continuous – The counterexample in § 6 of their paper – About the classical tautology which is untrue being replaced by the statements about commeasurable quantum-mechanical quantities – Logical hidden parameters – The undecidability of the hypothesis about hidden parameters – Wigner’s work and и Weyl’s previous one – Lie groups, representations, and psi-function – From a qualitative to a quantitative expression of relativity − psi-function, or the discrete by the random – Bartlett’s approach − psi-function as the characteristic function of random quantity – Discrete and/ or continual description – Quantity and its “digitalized projection“ – The idea of „velocity−probability“ – The notion of probability and the light speed postulate – Generalized probability and its physical interpretation – A quantum description of macro-world – The period of the as-sociated de Broglie wave and the length of now – Causality equivalently replaced by chance – The philosophy of quantum information and religion – Einstein’s thesis about “the consubstantiality of inertia ant weight“ – Again about the interpretation of complex velocity – The speed of time – Newton’s law of inertia and Lagrange’s formulation of mechanics – Force and effect – The theory of tachyons and general relativity – Riesz’s representation theorem – The notion of covariant world line – Encoding a world line by psi-function – Spacetime and qubit − psi-function by qubits – About the physical interpretation of both the complex axes of a qubit – The interpretation of the self-adjoint operators components – The world line of an arbitrary quantity – The invariance of the physical laws towards quantum object and apparatus – Hilbert space and that of Minkowski – The relationship between the coefficients of -function and the qubits – World line = psi-function + self-adjoint operator – Reality and description – Does a „curved“ Hilbert space exist? – The axiom of choice, or when is possible a flattening of Hilbert space? – But why not to flatten also pseudo-Riemannian space? – The commutator of conjugate quantities – Relative mass – The strokes of self-movement and its philosophical interpretation – The self-perfection of the universe – The generalization of quantity in quantum physics – An analogy of the Feynman formalism – Feynman and many-world interpretation – The psi-function of various objects – Countable and uncountable basis – Generalized continuum and arithmetization – Field and entanglement – Function as coding – The idea of „curved“ Descartes product – The environment of a function – Another view to the notion of velocity-probability – Reality and description – Hilbert space as a model both of object and description – The notion of holistic logic – Physical quantity as the information about it – Cross-temporal correlations – The forecasting of future – Description in separable and inseparable Hilbert space – „Forces“ or „miracles“ – Velocity or time – The notion of non-finite set – Dasein or Dazeit – The trajectory of the whole – Ontological and onto-theological difference – An analogy of the Feynman and many-world interpretation − psi-function as physical quantity – Things in the world and instances in time – The generation of the physi-cal by mathematical – The generalized notion of observer – Subjective or objective probability – Energy as the change of probability per the unite of time – The generalized principle of least action from a new view-point – The exception of two dimensions and Fermat’s last theorem. (shrink)

The paper considers the significance of F. A. Hayek’s writings on the study of complex phenomena for the study of the very complex phenom- ena of Hayek’s own life and career. It is argued that the methodological principle which Hayek recommended for the investigation of complex phenomena is applicable to explanations of his own intellectual develop- ment. Indeed, it is argued that the extent to which a Hayek scholar re- spects this principle in their attempts to explain (...) Hayek’s life and career is the first criterion by which such attempts should be evaluated. As Hayek himself might have put it, an explanation of some part of his career that neglects its inherent complexity is “probably merely of necessity false” (Hayek, [1964] 2014, 263). (shrink)

The use of evidence to resolve uncertainties is key to many endeavours, most conspicuously science and law. Despite this, the logic of uncertainty is seldom taught explicitly, and often seems misunderstood. Traditional educational practice even fails to encourage students to identify uncertainty when they express knowledge, though mark schemes that reward the identification of reliable and uncertain responses have long been shown to encourage more insightful understanding. In our information-rich society the ability to identify uncertainty is often more important than (...) the possession of knowledge itself. In both science and law there are fundamentally different kinds of uncertainty at issue. There is uncertainty whether a particular hypothesis is correct, and there is uncertainty about observable data that may be generated if a particular hypothesis is correct. Both are expressed in terms of probabilities. Each has its own domain of application and its own logic, but the inter-relationship is complex and sometimes misunderstood. Hypothesis probabilities are always open to error through possible failure to take account of realistic alternatives, while the proper inferences that can be drawn from data probabilities (often in the context of significance testing) are quite limited and easily over-interpreted. When considering these two kinds of probability in a court of law it is possible to interpret the phrase 'reasonable doubt' in different ways. It can be seen as addressing data uncertainty: whether such incriminating evidence might with reasonable probability arise to confront an innocent person. Or (the more conventional view) it can be seen as some sort of threshold level on the probability that the defendant is guilty (a hypothesis probability). Each typically involves elements of subjective judgement, but fewer issues and uncertainties arise when considering the data probability and it is argued that this is often the more critical and proper issue for a jury to address. This has particular repercussions for cases involving identification of a suspect through trawl of a DNA or other database. (shrink)

The scientific study of living organisms is permeated by machine and design metaphors. Genes are thought of as the ‘‘blueprint’’ of an organism, organisms are ‘‘reverse engineered’’ to discover their functionality, and living cells are compared to biochemical factories, complete with assembly lines, transport systems, messenger circuits, etc. Although the notion of design is indispensable to think about adaptations, and engineering analogies have considerable heuristic value (e.g., optimality assumptions), we argue they are limited in several important respects. In particular, the (...) analogy with human-made machines falters when we move down to the level of molecular biology and genetics. Living organisms are far more messy and less transparent than human-made machines. Notoriously, evolution is an opportunistic tinkerer, blindly stumbling on ‘‘designs’’ that no sensible engineer would come up with. Despite impressive technological innovation, the prospect of artificially designing new life forms from scratch has proven more difficult than the superficial analogy with ‘‘programming’’ the right ‘‘software’’ would suggest. The idea of applying straightforward engineering approaches to living systems and their genomes— isolating functional components, designing new parts from scratch, recombining and assembling them into novel life forms—pushes the analogy with human artifacts beyond its limits. In the absence of a one-to-one correspondence between genotype and phenotype, there is no straightforward way to implement novel biological functions and design new life forms. Both the developmental complexity of gene expression and the multifarious interactions of genes and environments are serious obstacles for ‘‘engineering’’ a particular phenotype. The problem of reverse-engineering a desired phenotype to its genetic ‘‘instructions’’ is probably intractable for any but the most simple phenotypes. Recent developments in the field of bio-engineering and synthetic biology reflect these limitations. Instead of genetically engineering a desired trait from scratch, as the machine/engineering metaphor promises, researchers are making greater strides by co-opting natural selection to ‘‘search’’ for a suitable genotype, or by borrowing and recombining genetic material from extant life forms. (shrink)

The semantic theory of expressivism has been applied within metaethics to evaluative words like ‘good’ and ‘wrong’, within epistemology to words like ‘knows’, and within the philosophy of language, to words like ‘true’, to epistemic modals like ‘might’, ‘must’, and ‘probably’, and to indicative conditionals. For each topic, expressivism promises the advantage of giving us the resources to say what sentences involving these words mean by telling us what it is to believe these things, rather than by telling us what (...) it would be for them to be true. This, in turn, absolves these theories of the burden of holding that there is any general answer to what it is for these sentences to be true. However, expressivism is famously subject to a deep and general problem about how to account for the meanings of complex sentences – a problem variously known as the ‘Frege-Geach’ or ‘embedding’ problem. In this paper I will be interested in whether there are reasons to think that the embedding problem looks less difficult for some of these applications for expressivism, than for others. In particular, in this paper I will be interested in the prospects for expressivism about what I will call epistemics – a class which I take to include epistemic modals like ‘might’ and ‘must’, sentential adverbs like ‘probably’, adjectives like ‘likely’ and ‘improbable’, and so-called ‘open’ indicative conditionals like ‘if the Fed doesn’t intervene, then the economy will enter a deflationary spiral’. There are several reasons to be particularly interested in expressivism about epistemics, relating both to the philosophical payoffs of such a view, and relating to the technical prospects for making it work. In other work I’ve touched on the especially interesting philosophical payoffs which make expressivism about epistemics interesting; in this paper I will be interested primarily in evaluating the possibility that there are better prospects for making expressivism about epistemics work than there are for making expressivism work about other topics. There are two main reasons why one might suspect that expressivism about epistemics will have better prospects than expressivism about many other topics, including in metaethics.. (shrink)

In recent decades, the analysis of phraseology has made use of the exploration of large corpora as a source of quantitative information about language. This paper intends to present the main lines of work in progress based on this empirical approach to linguistic analysis. In particular, we focus our attention on some problems relating to the morpho-syntactic annotation of corpora. The CORIS/CODIS corpus of contemporary written Italian, developed at CILTA – University of Bologna (Rossini Favretti 2000; Rossini Favretti, Tamburini, De (...) Santis in press), is a synchronic 100-million-word corpus and is being lemmatised and annotated with part-of-speech (POS) tags, in order to increase the quantity of information and improve data retrieval procedures (Tamburini 2000). The aim of POS tagging is to assign each lexical unit to the appropriate word class. Usually the set of tags is pre-established by the linguist, who uses his/her competence to identify the different word classes. The very first experiments we made revealed how the traditional part-of-speech distinctions in Italian (generally based on morphological and semantic criteria) are often inadequate to represent the syntactic features of words in context. It is worth noting that the uncertainties in categorisation contained in Italian grammars and dictionaries reflect a growing difficulty as they move from fundamental linguistic classes, such as nouns and verbs, to more complex classes, such as adverbs, pronouns, prepositions and conjunctions. This latter class, that groups together elements traditionally used to express connections between sentences, appears inadequate when describing cohesive relations in Italian. This phenomenon actually seems to involve other elements traditionally assigned to different classes, such as adverbs, pronouns and interjections. Recent studies proposed the class of ‘connectives’, grouping all words that, apart from their traditional word class, have the function of connecting phrases and contributing to textual cohesion. From this point of view, conjunctions can be considered as part of phrasal connectives, that can in turn be included in the wider category of textual connectives. The aim of this study is to identify elements that can be included in the class of phrasal connectives, using quantitative methods. According to Shannon and Weaver’s (1949) observation that words are linked by dependent probabilities, corroborated by Halliday’s (1991) argument that the grammatical “system” (in Firth’s sense of the term) is essentially probabilistic, quantitative data are introduced in order to provide evidence of relative frequencies. Section 2 presents a description of word-class categorisation from the point of view of grammars and dictionaries arguing that the traditional category of conjunctions is inadequate for capturing the notion of phrasal connective. Section 3 examines the notion of ‘connective’ and suggests a truth-function interpretation of connective behaviour. Section 4 describes the quantitative methods proposed for analysing the distributional properties of lexical units, and section 5 comments on the results obtained by applying such methods drawing some provisional conclusions. (shrink)

Many authors have proposed constraining the behaviour of intelligent systems with ‘machine ethics’ to ensure positive social outcomes from the development of such systems. This paper critically analyses the prospects for machine ethics, identifying several inherent limitations. While machine ethics may increase the probability of ethical behaviour in some situations, it cannot guarantee it due to the nature of ethics, the computational limitations of computational agents and the complexity of the world. In addition, machine ethics, even if it were (...) to be ‘solved’ at a technical level, would be insufficient to ensure positive social outcomes from intelligent systems. (shrink)

We attribute knowledge to institutions on a daily basis, saying things like "the government knew about the threat" or "the university did not act upon the knowledge it had about the harassment". Institutions can also attribute knowledge to themselves, like when Maybank Global Banking claims that it offers its customers "deep expertise and vast knowledge" of the Southeast Asia region, or when the United States Geological Survey states that it understands complex natural science phenomena like the probability of (...) earthquakes occurring along a given fault line. This article aims to discover when we can correctly attribute knowledge to an institution. I find this an interesting question, especially because when something does go wrong, all too often the official line of response from institutions is that they were unaware of the situation: in other words, they did not have enough information at their disposal. I will argue that institutions have fewer excuses for being ignorant than individuals do, and that many admissions of institutional knowledge are too modest. I begin by discussing a real-life example of the latter, before turning my attention to the usually fragmented nature of institutional knowledge. I also discuss the robustness of this knowledge, offering a distinction between two types of institutional knowledge. I then discuss knowledge parameters and why institutions have fewer excuses for not knowing about something than individuals do. I round off the chapter by examining institutional knowledge on climate change. (shrink)

We propose a nonmonotonic Description Logic of typicality able to account for the phenomenon of combining prototypical concepts, an open problem in the fields of AI and cognitive modelling. Our logic extends the logic of typicality ALC + TR, based on the notion of rational closure, by inclusions p :: T(C) v D (“we have probability p that typical Cs are Ds”), coming from the distributed semantics of probabilistic Description Logics. Additionally, it embeds a set of cognitive heuristics for (...) concept combination. We show that the complexity of reasoning in our logic is EXPTIME-complete as in ALC. (shrink)

The aim of this work was to elaborate on the author’s previously published hypothesis of the Soul of Multiverse, a suggested cosmic phenomenon that also appears to imbue the human Soul across its individual and noospheric scales. Without alternatives, the method of analysis continued to rely on the approach of cosmological neuroscience, which integrates scientific facts, religious insights, philosophical suggestions, engineering rules and artistic tools to grasp the complexity of the multidimensional phenomenon of Soul. The result of this examination was (...) the multilayered thought that just as the central medium of human Soul, the hypothesized prefrontal cortical supercircuitry of Self-Ken, seems to comprise domains representing Identity, Conscience, Will and Mission, analogous domains may also function in the noospheric and cosmic Souls. Regarding the human Soul, its four domains appear to be determined by both hereditary genetic and encountered environmental factors to present its host with a Mission enabling his or her mental engine and physical features to integrate into the surrounding society and space-time in the most meaningful and dignified way—if that way is undertaken. Regarding the noospheric Soul, it is made of individual human Souls interacting with the non-living system of interconnected computers to produce functions accessible to humans all over the world through uncontrolled communication across the Internet. Its most probable Mission is to let this global presence acquire its own Identity, develop its own Conscience and refine its own Will, so that their coherent, superior whole can be ready for sensing the cosmic Soul. Regarding the cosmic Soul, the hypothesized Soul of the Multiverse, its Identity appears to express the Laws of Mystery of Endlessness, Coexistence in Diversity, and Truth in Complexity. Further, its Conscience seems to be moved by the Law of Divine—Evil Asymmetry, its Will by the Law of Determination with Uncertainty, and its Mission by the Law of Lives to Transcend. (shrink)