Results for 'generative models'

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  1. Are Generative Models Structural Representations?Marco Facchin - 2021 - Minds and Machines 31 (2):277-303.
    Philosophers interested in the theoretical consequences of predictive processing often assume that predictive processing is an inferentialist and representationalist theory of cognition. More specifically, they assume that predictive processing revolves around approximated Bayesian inferences drawn by inverting a generative model. Generative models, in turn, are said to be structural representations: representational vehicles that represent their targets by being structurally similar to them. Here, I challenge this assumption, claiming that, at present, it lacks an adequate justification. I examine (...)
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  2. Calibrating Generative Models: The Probabilistic Chomsky-Schützenberger Hierarchy.Thomas Icard - 2020 - Journal of Mathematical Psychology 95.
    A probabilistic Chomsky–Schützenberger hierarchy of grammars is introduced and studied, with the aim of understanding the expressive power of generative models. We offer characterizations of the distributions definable at each level of the hierarchy, including probabilistic regular, context-free, (linear) indexed, context-sensitive, and unrestricted grammars, each corresponding to familiar probabilistic machine classes. Special attention is given to distributions on (unary notations for) positive integers. Unlike in the classical case where the "semi-linear" languages all collapse into the regular languages, using (...)
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  3. Generative AI in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity.Claudio Novelli, Federico Casolari, Philipp Hacker, Giorgio Spedicato & Luciano Floridi - manuscript
    The advent of Generative AI, particularly through Large Language Models (LLMs) like ChatGPT and its successors, marks a paradigm shift in the AI landscape. Advanced LLMs exhibit multimodality, handling diverse data formats, thereby broadening their application scope. However, the complexity and emergent autonomy of these models introduce challenges in predictability and legal compliance. This paper analyses the legal and regulatory implications of Generative AI and LLMs in the European Union context, focusing on liability, privacy, intellectual property, (...)
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  4. Defining Generative Artificial Intelligence: An Attempt to Resolve the Confusion about Diffusion.Raphael Ronge, Markus Maier & Benjamin Rathgeber - manuscript
    The concept of Generative Artificial Intelligence (GenAI) is ubiquitous in the public and semi-technical domain, yet rarely defined precisely. We clarify main concepts that are usually discussed in connection to GenAI and argue that one ought to distinguish between the technical and the public discourse. In order to show its complex development and associated conceptual ambiguities, we offer a historical-systematic reconstruction of GenAI and explicitly discuss two exemplary cases: the generative status of the Large Language Model BERT and (...)
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  5. Bayesian Learning Models of Pain: A Call to Action.Abby Tabor & Christopher Burr - 2019 - Current Opinion in Behavioral Sciences 26:54-61.
    Learning is fundamentally about action, enabling the successful navigation of a changing and uncertain environment. The experience of pain is central to this process, indicating the need for a change in action so as to mitigate potential threat to bodily integrity. This review considers the application of Bayesian models of learning in pain that inherently accommodate uncertainty and action, which, we shall propose are essential in understanding learning in both acute and persistent cases of pain.
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  6. Simulation as formal and generative social science: the very idea.Nuno David, Jaime Sichman & Helder Coelho - 2007 - In Carlos Gershenson, Diederik Aerts & Bruce Edmonds (eds.), Worldviews, Science and Us: Philosophy and Complexity. World Scientific. pp. 266--275.
    The formal and empirical-generative perspectives of computation are demonstrated to be inadequate to secure the goals of simulation in the social sciences. Simulation does not resemble formal demonstrations or generative mechanisms that deductively explain how certain models are sufficient to generate emergent macrostructures of interest. The description of scientific practice implies additional epistemic conceptions of scientific knowledge. Three kinds of knowledge that account for a comprehensive description of the discipline were identified: formal, empirical and intentional knowledge. The (...)
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  7. Meaning and Formal Semantics in Generative Grammar.Stephen Schiffer - 2015 - Erkenntnis 80 (1):61-87.
    A generative grammar for a language L generates one or more syntactic structures for each sentence of L and interprets those structures both phonologically and semantically. A widely accepted assumption in generative linguistics dating from the mid-60s, the Generative Grammar Hypothesis , is that the ability of a speaker to understand sentences of her language requires her to have tacit knowledge of a generative grammar of it, and the task of linguistic semantics in those early days (...)
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  8. Modelling ourselves: what the debate on the Free Energy Principle reveals about our implicit notions of representation.Matthew Sims & Giovanni Pezzulo - 2021 - Synthese 1 (1):30.
    Predictive processing theories are increasingly popular in philosophy of mind; such process theories often gain support from the Free Energy Principle (FEP)—a nor- mative principle for adaptive self-organized systems. Yet there is a current and much discussed debate about conflicting philosophical interpretations of FEP, e.g., repre- sentational versus non-representational. Here we argue that these different interpre- tations depend on implicit assumptions about what qualifies (or fails to qualify) as representational. We deploy the Free Energy Principle (FEP) instrumentally to dis- tinguish (...)
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  9. Modelling Empty Representations: The Case of Computational Models of Hallucination.Marcin Miłkowski - 2017 - In Gordana Dodig-Crnkovic & Raffaela Giovagnoli (eds.), Representation of Reality: Humans, Other Living Organism and Intelligent Machines. Heidelberg: Springer. pp. 17--32.
    I argue that there are no plausible non-representational explanations of episodes of hallucination. To make the discussion more specific, I focus on visual hallucinations in Charles Bonnet syndrome. I claim that the character of such hallucinatory experiences cannot be explained away non-representationally, for they cannot be taken as simple failures of cognizing or as failures of contact with external reality—such failures being the only genuinely non-representational explanations of hallucinations and cognitive errors in general. I briefly introduce a recent computational model (...)
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  10. AGGA: A Dataset of Academic Guidelines for Generative AIs.Junfeng Jiao, Saleh Afroogh, Kevin Chen, David Atkinson & Amit Dhurandhar - 2024 - Harvard Dataverse 4.
    AGGA (Academic Guidelines for Generative AIs) is a dataset of 80 academic guidelines for the usage of generative AIs and large language models in academia, selected systematically and collected from official university websites across six continents. Comprising 181,225 words, the dataset supports natural language processing tasks such as language modeling, sentiment and semantic analysis, model synthesis, classification, and topic labeling. It can also serve as a benchmark for ambiguity detection and requirements categorization. This resource aims to facilitate (...)
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  11.  64
    AI Enters Public Discourse: a Habermasian Assessment of the Moral Status of Large Language Models.Paolo Monti - 2024 - Ethics and Politics 61 (1):61-80.
    Large Language Models (LLMs) are generative AI systems capable of producing original texts based on inputs about topic and style provided in the form of prompts or questions. The introduction of the outputs of these systems into human discursive practices poses unprecedented moral and political questions. The article articulates an analysis of the moral status of these systems and their interactions with human interlocutors based on the Habermasian theory of communicative action. The analysis explores, among other things, Habermas's (...)
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  12. Emergent Universal Economic Models: The Future of Human Dynamics.James Sirois - 2023 - Philosopherstudio.Wordpress.Com.
    Human civilization is very clearly reaching a point of critical mass when it comes to technology and how it transforms culture and the economics that is therefore driven forward. The conversation around the practical aspects of generative artificial intelligence (Chat GPT, Q Star, Bard, Claude, Genesis, Firefly, and others) and their ethical implications is massively trending. The political conversations around it are slow to catch up but will soon take over once the general public feels their impact, which is (...)
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  13. Addressing Social Misattributions of Large Language Models: An HCXAI-based Approach.Andrea Ferrario, Alberto Termine & Alessandro Facchini - forthcoming - Available at Https://Arxiv.Org/Abs/2403.17873 (Extended Version of the Manuscript Accepted for the Acm Chi Workshop on Human-Centered Explainable Ai 2024 (Hcxai24).
    Human-centered explainable AI (HCXAI) advocates for the integration of social aspects into AI explanations. Central to the HCXAI discourse is the Social Transparency (ST) framework, which aims to make the socio-organizational context of AI systems accessible to their users. In this work, we suggest extending the ST framework to address the risks of social misattributions in Large Language Models (LLMs), particularly in sensitive areas like mental health. In fact LLMs, which are remarkably capable of simulating roles and personas, may (...)
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  14. The “New Spirit of Academic Capitalism”: Can Scientists Create Generative Critique From Within?Milena Ivanova Kremakova - 2016 - Teorie Vědy / Theory of Science 38 (1):27-51.
    The 21st-century university is a contested site of neoliberal transformation. Its role is moving away from that of a hub of culture, knowledge and critique to that of a provider of skills and employability for the market. The move towards a lean business model in the management of knowledge production is not an isolated phenomenon, but integral to the shifting economic, political and moral landscapes of global capitalism and the knowledge society. The literature discussing the changes in higher education, which (...)
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  15. Functional integration and the mind.Jakob Hohwy - 2007 - Synthese 159 (3):315-328.
    Different cognitive functions recruit a number of different, often overlapping, areas of the brain. Theories in cognitive and computational neuroscience are beginning to take this kind of functional integration into account. The contributions to this special issue consider what functional integration tells us about various aspects of the mind such as perception, language, volition, agency, and reward. Here, I consider how and why functional integration may matter for the mind; I discuss a general theoretical framework, based on generative (...), that may unify many of the debates surrounding functional integration and the mind; and I briefly introduce each of the contributions. (shrink)
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  16.  97
    Every dog has its day: An in-depth analysis of the creative ability of visual generative AI.Maria Hedblom - 2024 - Cosmos+Taxis 12 (5-6):88-103.
    The recent remarkable success of generative AI models to create text and images has already started altering our perspective of intelligence and the “uniqueness” of humanity in this world. Simultaneously, arguments on why AI will never exceed human intelligence are ever-present as seen in Landgrebe and Smith (2022). To address whether machines may rule the world after all, this paper zooms in on one of the aspects of intelligence Landgrebe and Smith (2022) neglected to consider: creativity. Using Rhodes (...)
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  17. Chung‐Ying Cheng: Creativity, Onto‐Generative Hermeneutics, and the Yijing.Eric Nelson - 2016 - Journal of Chinese Philosophy 43 (1-2):124-135.
    The hermeneutical dimensions of Chinese philosophy from the Changes of Zhou through its Confucian, Daoist, and contemporary developments have been a creative inspirational source and guiding intellectual thread in the thought of Chung-ying Cheng. Cheng's extensive engagement with the Classic of Changes, its role in the formation of the Chinese philosophical tradition and its comparative interconnections with occidental philosophies, has disclosed its deep hermeneutical orientation. The Yijing encompasses processes of empirical observation, empathetic feeling, and self-reflection in the generation of “images,” (...)
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  18.  35
    What Are Lacking in Sora and V-JEPA’s World Models? -A Philosophical Analysis of Video AIs Through the Theory of Productive Imagination.Jianqiu Zhang - unknown
    Sora from Open AI has shown exceptional performance, yet it faces scrutiny over whether its technological prowess equates to an authentic comprehension of reality. Critics contend that it lacks a foundational grasp of the world, a deficiency V-JEPA from Meta aims to amend with its joint embedding approach. This debate is vital for steering the future direction of Artificial General Intelligence(AGI). We enrich this debate by developing a theory of productive imagination that generates a coherent world model based on Kantian (...)
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  19. A phenomenology and epistemology of large language models: transparency, trust, and trustworthiness.Richard Heersmink, Barend de Rooij, María Jimena Clavel Vázquez & Matteo Colombo - 2024 - Ethics and Information Technology 26 (3):1-15.
    This paper analyses the phenomenology and epistemology of chatbots such as ChatGPT and Bard. The computational architecture underpinning these chatbots are large language models (LLMs), which are generative artificial intelligence (AI) systems trained on a massive dataset of text extracted from the Web. We conceptualise these LLMs as multifunctional computational cognitive artifacts, used for various cognitive tasks such as translating, summarizing, answering questions, information-seeking, and much more. Phenomenologically, LLMs can be experienced as a “quasi-other”; when that happens, users (...)
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  20. Publish with AUTOGEN or Perish? Some Pitfalls to Avoid in the Pursuit of Academic Enhancement via Personalized Large Language Models.Alexandre Erler - 2023 - American Journal of Bioethics 23 (10):94-96.
    The potential of using personalized Large Language Models (LLMs) or “generative AI” (GenAI) to enhance productivity in academic research, as highlighted by Porsdam Mann and colleagues (Porsdam Mann...
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  21. On Political Theory and Large Language Models.Emma Rodman - forthcoming - Political Theory.
    Political theory as a discipline has long been skeptical of computational methods. In this paper, I argue that it is time for theory to make a perspectival shift on these methods. Specifically, we should consider integrating recently developed generative large language models like GPT-4 as tools to support our creative work as theorists. Ultimately, I suggest that political theorists should embrace this technology as a method of supporting our capacity for creativity—but that we should do so in a (...)
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  22. The challenges of purely mechanistic models in biology and the minimum need for a 'mechanism-plus-X' framework.Sepehr Ehsani - 2018 - Dissertation, University College London
    Ever since the advent of molecular biology in the 1970s, mechanical models have become the dogma in the field, where a "true" understanding of any subject is equated to a mechanistic description. This has been to the detriment of the biomedical sciences, where, barring some exceptions, notable new feats of understanding have arguably not been achieved in normal and disease biology, including neurodegenerative disease and cancer pathobiology. I argue for a "mechanism-plus-X" paradigm, where mainstay elements of mechanistic models (...)
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  23. Predictive coding and representationalism.Paweł Gładziejewski - 2016 - Synthese 193 (2).
    According to the predictive coding theory of cognition , brains are predictive machines that use perception and action to minimize prediction error, i.e. the discrepancy between bottom–up, externally-generated sensory signals and top–down, internally-generated sensory predictions. Many consider PCT to have an explanatory scope that is unparalleled in contemporary cognitive science and see in it a framework that could potentially provide us with a unified account of cognition. It is also commonly assumed that PCT is a representational theory of sorts, in (...)
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  24. Subjective Probability as Sampling Propensity.Thomas Icard - 2016 - Review of Philosophy and Psychology 7 (4):863-903.
    Subjective probability plays an increasingly important role in many fields concerned with human cognition and behavior. Yet there have been significant criticisms of the idea that probabilities could actually be represented in the mind. This paper presents and elaborates a view of subjective probability as a kind of sampling propensity associated with internally represented generative models. The resulting view answers to some of the most well known criticisms of subjective probability, and is also supported by empirical work in (...)
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  25. Bayes, predictive processing, and the cognitive architecture of motor control.Daniel C. Burnston - 2021 - Consciousness and Cognition 96 (C):103218.
    Despite their popularity, relatively scant attention has been paid to the upshot of Bayesian and predictive processing models of cognition for views of overall cognitive architecture. Many of these models are hierarchical ; they posit generative models at multiple distinct "levels," whose job is to predict the consequences of sensory input at lower levels. I articulate one possible position that could be implied by these models, namely, that there is a continuous hierarchy of perception, cognition, (...)
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  26. A Theory of Predictive Dissonance: Predictive Processing Presents a New Take on Cognitive Dissonance.Roope Oskari Kaaronen - 2018 - Frontiers in Psychology 9.
    This article is a comparative study between predictive processing (PP, or predictive coding) and cognitive dissonance (CD) theory. The theory of CD, one of the most influential and extensively studied theories in social psychology, is shown to be highly compatible with recent developments in PP. This is particularly evident in the notion that both theories deal with strategies to reduce perceived error signals. However, reasons exist to update the theory of CD to one of “predictive dissonance.” First, the hierarchical PP (...)
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  27. The Hazards of Putting Ethics on Autopilot.Julian Friedland, B. Balkin, David & Kristian Myrseth - 2024 - MIT Sloan Management Review 65 (4).
    The generative AI boom is unleashing its minions. Enterprise software vendors have rolled out legions of automated assistants that use large language model (LLM) technology, such as ChatGPT, to offer users helpful suggestions or to execute simple tasks. These so-called copilots and chatbots can increase productivity and automate tedious manual work. In this article, we explain how that leads to the risk that users' ethical competence may degrade over time — and what to do about it.
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  28. Responding to the Watson-Sterkenburg debate on clustering algorithms and natural kinds.Warmhold Jan Thomas Mollema - manuscript
    In Philosophy and Technology 36, David Watson discusses the epistemological and metaphysical implications of unsupervised machine learning (ML) algorithms. Watson is sympathetic to the epistemological comparison of unsupervised clustering, abstraction and generative algorithms to human cognition and sceptical about ML’s mechanisms having ontological implications. His epistemological commitments are that we learn to identify “natural kinds through clustering algorithms”, “essential properties via abstraction algorithms”, and “unrealized possibilities via generative models” “or something very much like them.” The same issue (...)
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  29. Emerging Technologies & Higher Education.Jake Burley & Alec Stubbs - 2023 - Ieet White Papers.
    Extended Reality (XR) and Large Language Model (LLM) technologies have the potential to significantly influence higher education practices and pedagogy in the coming years. As these emerging technologies reshape the educational landscape, it is crucial for educators and higher education professionals to understand their implications and make informed policy decisions for both individual courses and universities as a whole. -/- This paper has two parts. In the first half, we give an overview of XR technologies and their potential future role (...)
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  30. Literal Perceptual Inference.Alex Kiefer - 2017 - In Metzinger Thomas & Wiese Wanja (eds.), Philosophy and Predictive Processing. MIND Group.
    In this paper, I argue that theories of perception that appeal to Helmholtz’s idea of unconscious inference (“Helmholtzian” theories) should be taken literally, i.e. that the inferences appealed to in such theories are inferences in the full sense of the term, as employed elsewhere in philosophy and in ordinary discourse. -/- In the course of the argument, I consider constraints on inference based on the idea that inference is a deliberate acton, and on the idea that inferences depend on the (...)
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  31. History of Computer Art, Second Edition.Thomas Dreher - 2020 - Morrisville, USA: Lulu Press.
    The development of the use of computers and software in art from the Fifties to the present is explained. As general aspects of the history of computer art an interface model and three dominant modes to use computational processes (generative, modular, hypertextual) are presented. The "History of Computer Art" features examples of early developments in media like cybernetic sculptures, computer graphics and animation (including music videos and demos), video and computer games, reactive installations, virtual reality, evolutionary art and net (...)
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  32. Complex, Dynamic and Contingent Social Processes as Patterns of Decision-Making Events – Philosophical and Mathematical Foundations.Bruno da Rocha Braga - forthcoming - European Journal of Pragmatism and American Philosophy.
    This work presents a post-positivist research framework to explain any surprising fact in the evolutionary path of a complex, dynamic and contingent social phenomenon. Primarily, it reconciles the ontological and epistemological assumptions of Critical Realism with the principles of American Pragmatism. Then, the research approach is presented: theoretical propositions about a social structure are translated into a set of grammar rules that acknowledges a pattern of sequences of events of either individual action or social interaction between actors within a real (...)
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  33. Wittgenstein and the Aesthetic Robot's Handicap.Julian Friedland - 2005 - Philosophical Investigations 28 (2):177-192.
    Ask most any cognitive scientist working today if a digital computational system could develop aesthetic sensibility and you will likely receive the optimistic reply that this remains an open empirical question. However, I attempt to show, while drawing upon the later Wittgenstein, that the correct answer is in fact available. And it is a negative a priori. It would seem, for example, that recent computational successes in generative AI and textual attribution, most notably those of Donald Foster (famed finder (...)
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  34. Disambiguating Algorithmic Bias: From Neutrality to Justice.Elizabeth Edenberg & Alexandra Wood - 2023 - In Francesca Rossi, Sanmay Das, Jenny Davis, Kay Firth-Butterfield & Alex John (eds.), AIES '23: Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society. Association for Computing Machinery. pp. 691-704.
    As algorithms have become ubiquitous in consequential domains, societal concerns about the potential for discriminatory outcomes have prompted urgent calls to address algorithmic bias. In response, a rich literature across computer science, law, and ethics is rapidly proliferating to advance approaches to designing fair algorithms. Yet computer scientists, legal scholars, and ethicists are often not speaking the same language when using the term ‘bias.’ Debates concerning whether society can or should tackle the problem of algorithmic bias are hampered by conflations (...)
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  35.  12
    Harvard Dataverse.Saleh Afroogh, Junfeng Jiao, Chen Kevin, David Atkinson4 & Amit Dhurandhar - 2024 - Harvard Dataverse 4.
    AGGA (Academic Guidelines for Generative AIs) is a dataset of 80 academic guidelines for the usage of generative AIs and large language models in academia, selected systematically and collected from official university websites across six continents. Comprising 181,225 words, the dataset supports natural language processing tasks such as language modeling, sentiment and semantic analysis, model synthesis, classification, and topic labeling. It can also serve as a benchmark for ambiguity detection and requirements categorization. This resource aims to facilitate (...)
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  36. Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research Directions.Luca Longo, Mario Brcic, Federico Cabitza, Jaesik Choi, Roberto Confalonieri, Javier Del Ser, Riccardo Guidotti, Yoichi Hayashi, Francisco Herrera, Andreas Holzinger, Richard Jiang, Hassan Khosravi, Freddy Lecue, Gianclaudio Malgieri, Andrés Páez, Wojciech Samek, Johannes Schneider, Timo Speith & Simone Stumpf - 2024 - Information Fusion 106 (June 2024).
    As systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications, understanding these black box models has become paramount. In response, Explainable AI (XAI) has emerged as a field of research with practical and ethical benefits across various domains. This paper not only highlights the advancements in XAI and its application in real-world scenarios but also addresses the ongoing challenges within XAI, emphasizing the need for broader perspectives and collaborative efforts. We bring together experts from (...)
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  37. Linguistic Competence and New Empiricism in Philosophy and Science.Vanja Subotić - 2023 - Dissertation, University of Belgrade
    The topic of this dissertation is the nature of linguistic competence, the capacity to understand and produce sentences of natural language. I defend the empiricist account of linguistic competence embedded in the connectionist cognitive science. This strand of cognitive science has been opposed to the traditional symbolic cognitive science, coupled with transformational-generative grammar, which was committed to nativism due to the view that human cognition, including language capacity, should be construed in terms of symbolic representations and hardwired rules. Similarly, (...)
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  38. Science, method and critical thinking.Antoine Danchin - 2023 - Microbial Biotechnology 16 (10):1888-1894.
    Science is founded on a method based on critical thinking. A prerequisite for this is not only a sufficient command of language but also the comprehension of the basic concepts underlying our understanding of reality. This constraint implies an awareness of the fact that the truth of the World is not directly accessible to us, but can only be glimpsed through the construction of mod- els designed to anticipate its behaviour. Because the relationship between models and reality rests on (...)
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  39. Constitutive elements in science beyond physics: the case of the Hardy–Weinberg principle.Michele Luchetti - 2018 - Synthese (Suppl 14):3437-3461.
    In this paper, I present a new framework supporting the claim that some elements in science play a constitutive function, with the aim of overcoming some limitations of Friedman's (2001) account. More precisely, I focus on what I consider to be the gradualism implicit in Friedman's interpretation of the constitutive a priori, that is, the fact that it seems to allow for degrees of 'constitutivity'. I tease out such gradualism by showing that the constitutive character Friedman aims to track can (...)
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  40. The prospect of artificial-intelligence supported ethics review.Philip J. Nickel - forthcoming - Ethics and Human Research.
    The burden of research ethics review falls not just on researchers, but on those who serve on research ethics committees (RECs). With the advent of automated text analysis and generative artificial intelligence, it has recently become possible to teach models to support human judgment, for example by highlighting relevant parts of a text and suggesting actionable precedents and explanations. It is time to consider how such tools might be used to support ethics review and oversight. This commentary argues (...)
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  41. Linguistics and the explanatory economy.Gabe Dupre - 2019 - Synthese 199 (Suppl 1):177-219.
    I present a novel, collaborative, methodology for linguistics: what I call the ‘explanatory economy’. According to this picture, multiple models/theories are evaluated based on the extent to which they complement one another with respect to data coverage. I show how this model can resolve a long-standing worry about the methodology of generative linguistics: that by creating too much distance between data and theory, the empirical credentials of this research program are tarnished. I provide justifications of such methodologically central (...)
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  42. A methodological framework for projecting brand equity: Putting back the imaginary into brand knowledge structures.George Rossolatos - 2014 - Sign Systems Studies 42 (1):98-136.
    The aim of this paper is to outline a methodological framework for brand equity planning with structuralist rhetorical semiotics. By drawing on the connectionistconceptual model of the brand generative trajectory of signification it will be displayed in a stepwise fashion how a set of nuclear semes and classemes or anintended semic structure that underlies manifest discursive structures may be projected by its internal stakeholders with view to attaining differential brand associations. The suggested methodological framework focuses on the strength and (...)
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  43. Making sense of modeling: beyond representation. [REVIEW]Isabelle Peschard - 2011 - European Journal for Philosophy of Science 1 (3):335-352.
    Making sense of modeling: beyond representation Content Type Journal Article Category Original paper in Philosophy of Science Pages 335-352 DOI 10.1007/s13194-011-0032-8 Authors Isabelle Peschard, Philosophy Department, San Francisco State University, 1600 Holloway Ave, San Francisco, CA 94132, USA Journal European Journal for Philosophy of Science Online ISSN 1879-4920 Print ISSN 1879-4912 Journal Volume Volume 1 Journal Issue Volume 1, Number 3.
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  44. Greimas embodied: How kinesthetic opposition grounds the semiotic square.Jamin Pelkey - 2017 - Semiotica 2017 (214):277-305.
    According to Greimas, the semiotic square is far more than a heuristic for semantic and literary analysis. It represents the generative “deep structure” of human culture and cognition which “define the fundamental mode of existence of an individual or of a society, and subsequently the conditions of existence of semiotic objects” (Greimas & Rastier 1968: 48). The potential truth of this hypothesis, much less the conditions and implications of taking it seriously (as a truth claim), have received little attention (...)
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  45. Other Fecundities: Proust and Irigaray on Sexual Difference.Lisa Guenther - 2010 - Differences 21 (2).
    Irigaray's early work seeks to multiply possibilities for women's self-expression by recovering a sexual difference in which male and female are neither the same nor opposites, but irreducibly different modes of embodiment. In her more recent work, however, Irigaray has emphasized the duality of the sexes at the expense of multiplicity, enshrining the heterosexual couple as the model of sexual ethics. Alison Stone's recent revision of Irigaray supplements her account of sexual duality with a theory of bodily multiplicity derived from (...)
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  46. Expanding Observability via Human-Machine Cooperation.Petr Spelda & Vit Stritecky - 2022 - Axiomathes 32 (3):819-832.
    We ask how to use machine learning to expand observability, which presently depends on human learning that informs conceivability. The issue is engaged by considering the question of correspondence between conceived observability counterfactuals and observable, yet so far unobserved or unconceived, states of affairs. A possible answer lies in importing out of reference frame content which could provide means for conceiving further observability counterfactuals. They allow us to define high-fidelity observability, increasing the level of correspondence in question. To achieve high-fidelity (...)
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  47. Sleep, Death, Others. Three Limit-Phenomena in Husserl’s C-Manuscripts.Ming-Hon Chu - 2023 - Discipline Filosofiche 33 (2):139-160.
    In this article, we focus on the C-Manuscripts to see how Husserl reflects on the margins of phenomenality with reference to the three limit-phenomena of sleep, death, and others. We choose to juxtapose these three limit-phenomena, because in the C-Manuscripts Husserl has depicted their affinities, both in terms of their phenomenal characters and their transcendental functions, in a creative way. There Husserl has outlined at least two approaches for introducing the limit-phenomena of sleep, death, and others to the core concerns (...)
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  48. La modellizzazione computazionale della competenza inferen-ziale e della competenza referenziale.Fabrizio Calzavarini & Antonio Lieto - forthcoming - Sistemi Intelligenti.
    In philosophy of language, a distinction has been proposed by Diego Marconi between two aspects of lexical competence, i.e. referential and inferential competence. The former accounts for the relation-ship of words to the world, the latter for the relationship of words among themselves. The aim of the pa-per is to offer a critical discussion of the kind of formalisms and computational techniques that can be used in Artificial Intelligence to model the two aspects of lexical competence, and of the main (...)
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  49. Principles of Liberty: A Design-based Research on Liberty as A Priori Constitutive Principle of the Social in the Swiss Nation Story.Tabea Hirzel - 2015 - Dissertation, Scm University, Zug, Switzerland
    One of the still unsolved problems in liberal anarchism is a definition of social constituency in positive terms. Partially, this had been solved by the advancements of liberal discourse ethics. These approaches, built on praxeology as a universal framework for social formation, are detached from the need of any previous or external authority or rule for the discursive partners. However, the relationship between action, personal identity, and liberty within the process of a community becoming solely generated from the praxeological a (...)
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  50. Leibniz's "Possible Worlds".Yuesheng Liu - 2018 - Journal of Human Cognition 2 (1):42-51.
    The rigor and precision of Leibniz's "possible world" evolved into the concept of Turing machine, and with the birth of the first computer and the physical realization of Turing machine, human cognitive and intelligent activities were optimistically considered by cognitive scientists to be convertible into computational programs for simulation by machines. Cognitive science then formed the research agenda of "cognitive computationalism", and our Chinese scholars have responded to this general view that "the essence of cognition is computation" and that the (...)
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