Results for 'genetic algorithm'

999 found
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  1.  67
    Neutrosophic Genetic Algorithm for solving the Vehicle Routing Problem with uncertain travel times.Rafael Rojas-Gualdron & Florentin Smarandache - 2022 - Neutrosophic Sets and Systems 52.
    The Vehicle Routing Problem (VRP) has been extensively studied by different researchers from all over the world in recent years. Multiple solutions have been proposed for different variations of the problem, such as Capacitive Vehicle Routing Problem (CVRP), Vehicle Routing Problem with Time Windows (VRP-TW), Vehicle Routing Problem with Pickup and Delivery (VRPPD), among others, all of them with deterministic times. In the last years, researchers have been interested in including in their different models the variations that travel times may (...)
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  2. Evolutionary Theory and Computerised Genetic Algorithms.Derek Philip Hough - 2018 - Researchgate.
    Neo-Darwinism can be usefully studied with the help of a Computerised Genetic Algorithm. Only a mathematical approach can reveal the shortcomings of the current dogma and point the way to a revised definition of the theory of evolution.
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  3. Environmental Variability and the Emergence of Meaning: Simulational Studies across Imitation, Genetic Algorithms, and Neural Nets.Patrick Grim - 2006 - In Angelo Loula & Ricardo Gudwin (eds.), Artificial Cognition Systems. Idea Group. pp. 284-326.
    A crucial question for artificial cognition systems is what meaning is and how it arises. In pursuit of that question, this paper extends earlier work in which we show that emergence of simple signaling in biologically inspired models using arrays of locally interactive agents. Communities of "communicators" develop in an environment of wandering food sources and predators using any of a variety of mechanisms: imitation of successful neighbors, localized genetic algorithms and partial neural net training on successful neighbors. Here (...)
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  4. Coding the Self: The Infopolitics and Biopolitics of Genetic Sciences.Colin Koopman - 2020 - Hastings Center Report 50 (S1):6-14.
    This article compares three models for conceptualizing the political and ethical challenges of contemporary genetics, genomics, and postgenomics. The three analytical approaches are referred to as the state-politics model, the biopolitical model, and the infopolitical model. Each of these models is valuable for different purposes. But comparing these models in terms of their influence in contemporary discussions, the first is by far the dominant approach, the second is gaining in importance, and the third is almost entirely neglected. The widespread neglect (...)
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  5. Comparative Networks beyond Algorithms.Keith Elkin - manuscript
    This draft investigates Genetic Networks as a special case with comparisons to other networks. The intention is to discover the mapping between generic and abstract network properties and specific case studies.
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  6. Global Optimization Studies on the 1-D Phase Problem.Jim Marsh, Martin Zwick & Byrne Lovell - 1996 - Int. J. Of General Systems 25 (1):47-59.
    The Genetic Algorithm (GA) and Simulated Annealing (SA), two techniques for global optimization, were applied to a reduced (simplified) form of the phase problem (RPP) in computational crystallography. Results were compared with those of "enhanced pair flipping" (EPF), a more elaborate problem-specific algorithm incorporating local and global searches. Not surprisingly, EPF did better than the GA or SA approaches, but the existence of GA and SA techniques more advanced than those used in this study suggest that these (...)
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  7. Guest editor's introduction: artificial intelligence.Varol Akman - 2001 - Turkish Journal of Electrical Engineering and Computer Sciences 9 (1).
    Founded in 1993, ELEKTRIK: Turkish Journal of Electrical Engineering and Computer Sciences, has gradually become better known and is fast establishing itself as a research oriented publication outlet with high academic standards. In a modest attempt to advance this trend, this special issue of ELEKTRIK brings together five papers exemplifying the state of the art in artificial intelligence (AI). Written by experts, the papers are especially aimed at readers interested in gaining a better appraisal of the applications side of the (...)
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  8. Simulating Grice: Emergent Pragmatics in Spatialized Game Theory.Patrick Grim - 2011 - In Anton Benz, Christian Ebert & Robert van Rooij (eds.), Language, Games, and Evolution. Springer-Verlag.
    How do conventions of communication emerge? How do sounds or gestures take on a semantic meaning, and how do pragmatic conventions emerge regarding the passing of adequate, reliable, and relevant information? My colleagues and I have attempted in earlier work to extend spatialized game theory to questions of semantics. Agent-based simulations indicate that simple signaling systems emerge fairly naturally on the basis of individual information maximization in environments of wandering food sources and predators. Simple signaling emerges by means of any (...)
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  9. Making Meaning Happen.Patrick Grim - 2004 - Journal for Experimental and Theoretical Artificial Intelligence 16:209-244.
    What is it for a sound or gesture to have a meaning, and how does it come to have one? In this paper, a range of simulations are used to extend the tradition of theories of meaning as use. The authors work throughout with large spatialized arrays of sessile individuals in an environment of wandering food sources and predators. Individuals gain points by feeding and lose points when they are hit by a predator and are not hiding. They can also (...)
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  10. Boom and Bust: Environmental Variability Favors the Emergence of Communication.Patrick Grim & Trina Kokalis - 2004 - In Jordan Pollack, Mark Bedau, Phil Husbands, Takashi Ikegami & Richard A. Watson (eds.), Artificial Life IX: Proceedings of the Ninth International Conference on Artificial Life. MIT Press. pp. 164-170.
    Environmental variability has been proposed as an important mechanism in behavioral psychology, in ecology and evolution, and in cultural anthropology. Here we demonstrate its importance in simulational studies as well. In earlier work we have shown the emergence of communication in a spatialized environment of wandering food sources and predators, using a variety of mechanisms for strategy change: imitation (Grim, Kokalis, Tafti & Kilb 2000), localized genetic algorithm (Grim, Kokalis, Tafti & Kilb 2001), and partial training of neural (...)
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  11. SAR-BSO meta-heuristic hybridization for feature selection and classification using DBNover stream data.Dharani Talapula, Kiran Ravulakollu, Manoj Kumar & Adarsh Kumar - forthcoming - Artificial Intelligence Review.
    Advancements in cloud technologies have increased the infrastructural needs of data centers due to storage needs and processing of extensive dimensional data. Many service providers envisage anomaly detection criteria to guarantee availability to avoid breakdowns and complexities caused due to large-scale operations. The streaming log data generated is associated with multi-dimensional complexity and thus poses a considerable challenge to detect the anomalies or unusual occurrences in the data. In this research, a hybrid model is proposed that is motivated by deep (...)
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  12. Sex and the elimination of copying errors.Derek Philip Hough - 2021 - ResearchGate.
    This paper explores two separate elements of sex, namely sexual selection and crossover. A simple computerised genetic algorithm can confirm a possible connection between sexual selection and the elimination of copying errors.
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  13. The Origins of Darwin's 'unknown laws of variation'.Derek Hough - 2021 - Researchgate.
    The goal of this project is to encourage biologists to exclude any mention of 'copying errors' from the latest definition of the theory of evolution. Instead, it should be accepted that evolutionary change is facilitated by an evolved system of variety-maintenance and variety-generation which in turn leads to novel structures and complexity.
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  14. The "history" of biodiversity. A Bergsonian look at the theory of evolution.Mathilde Tahar - 2021 - Thaumàzein 8:89-106.
    Neo-Darwinism, through the combination of natural selection and genetics, has made possible an explanation of adaptive phenomena that claims to be devoid of metaphysical presuppositions. What Bergson already deplored and what we explore in this paper is the implicit finalism of such evolutionary explanations, which turn living beings into closed and static systems rather than understanding biological evolution as a process characterized by its interactions and temporal openness. Without denying the heuristic efficiency of the explanation resting upon natural selection, we (...)
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  15. An Improbable God Between Simplicity and Complexity: Thinking about Dawkins’s Challenge.Philippe Gagnon - 2013 - International Philosophical Quarterly 53 (4):409-433.
    Richard Dawkins has popularized an argument that he thinks sound for showing that there is almost certainly no God. It rests on the assumptions (1) that complex and statistically improbable things are more difficult to explain than those that are not and (2) that an explanatory mechanism must show how this complexity can be built up from simpler means. But what justifies claims about the designer’s own complexity? One comes to a different understanding of order and of simplicity when one (...)
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  16. Genotype–phenotype mapping and the end of the ‘genes as blueprint’ metaphor.Massimo Pigliucci - 2010 - Philosophical Transactions Royal Society B 365:557–566.
    In a now classic paper published in 1991, Alberch introduced the concept of genotype–phenotype (G!P) mapping to provide a framework for a more sophisticated discussion of the integration between genetics and developmental biology that was then available. The advent of evo-devo first and of the genomic era later would seem to have superseded talk of transitions in phenotypic space and the like, central to Alberch’s approach. On the contrary, this paper shows that recent empirical and theoretical advances have only sharpened (...)
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  17. Bioeconomics, biopolitics and bioethics: evolutionary semantics of evolutionary risk (anthropological essay).V. T. Cheshko - 2016 - Bioeconomics and Ecobiopolitic (1 (2)).
    Attempt of trans-disciplinary analysis of the evolutionary value of bioethics is realized. Currently, there are High Tech schemes for management and control of genetic, socio-cultural and mental evolution of Homo sapiens (NBIC, High Hume, etc.). The biological, socio-cultural and technological factors are included in the fabric of modern theories and technologies of social and political control and manipulation. However, the basic philosophical and ideological systems of modern civilization formed mainly in the 17–18 centuries and are experiencing ever-increasing and destabilizing (...)
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  18. Beyond categorical definitions of life: a data-driven approach to assessing lifeness.Christophe Malaterre & Jean-François Chartier - 2019 - Synthese 198 (5):4543-4572.
    The concept of “life” certainly is of some use to distinguish birds and beavers from water and stones. This pragmatic usefulness has led to its construal as a categorical predicate that can sift out living entities from non-living ones depending on their possessing specific properties—reproduction, metabolism, evolvability etc. In this paper, we argue against this binary construal of life. Using text-mining methods across over 30,000 scientific articles, we defend instead a degrees-of-life view and show how these methods can contribute to (...)
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  19. The mind, the lab, and the field: Three kinds of populations in scientific practice.Rasmus Grønfeldt Winther, Ryan Giordano, Michael D. Edge & Rasmus Nielsen - 2015 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 52:12-21.
    Scientists use models to understand the natural world, and it is important not to conflate model and nature. As an illustration, we distinguish three different kinds of populations in studies of ecology and evolution: theoretical, laboratory, and natural populations, exemplified by the work of R.A. Fisher, Thomas Park, and David Lack, respectively. Biologists are rightly concerned with all three types of populations. We examine the interplay between these different kinds of populations, and their pertinent models, in three examples: the notion (...)
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  20. die physik, das leben und die seele.Alfred Gierer - 1985 - Muenchen, Germany: piper.
    This book (in German) on "Physics, life and mind" is on the physical foundations of modern biology. The basic features of living systems, reproduction, mutation and metabolism, can be explained in terms of molecular processes involving nucleic acids as genetic material, and proteins as catalysts. The generation of structure and form in each generation results from spatiotemporal gene regulation in conjunction with the de novo formation of spatial order in which interplays of activation and inhibition play a crucial part. (...)
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  21. Stepping Beyond the Newtonian Paradigm in Biology. Towards an Integrable Model of Life: Accelerating Discovery in the Biological Foundations of Science.Plamen L. Simeonov, Edwin Brezina, Ron Cottam, Andreé C. Ehresmann, Arran Gare, Ted Goranson, Jaime Gomez‐Ramirez, Brian D. Josephson, Bruno Marchal, Koichiro Matsuno, Robert S. Root-­Bernstein, Otto E. Rössler, Stanley N. Salthe, Marcin Schroeder, Bill Seaman & Pridi Siregar - 2012 - In Plamen L. Simeonov, Leslie S. Smith & Andreé C. Ehresmann (eds.), Integral Biomathics: Tracing the Road to Reality. Springer. pp. 328-427.
    The INBIOSA project brings together a group of experts across many disciplines who believe that science requires a revolutionary transformative step in order to address many of the vexing challenges presented by the world. It is INBIOSA’s purpose to enable the focused collaboration of an interdisciplinary community of original thinkers. This paper sets out the case for support for this effort. The focus of the transformative research program proposal is biology-centric. We admit that biology to date has been more fact-oriented (...)
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  22. An evolutionary metaphysics of human enhancement technologies.Valentin Cheshko - manuscript
    The monograph is an English, expanded and revised version of the book Cheshko, V. T., Ivanitskaya, L.V., & Glazko, V.I. (2018). Anthropocene. Philosophy of Biotechnology. Moscow, Course. The manuscript was completed by me on November 15, 2019. It is a study devoted to the development of the concept of a stable evolutionary human strategy as a unique phenomenon of global evolution. The name “An Evolutionary Metaphysics (Cheshko, 2012; Glazko et al., 2016). With equal rights, this study could be entitled “Biotechnology (...)
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  23. Anthropocene: The philosophy of Biotechnology.Valentin Cheshko, Glazko Valery & Ivanitskaya Lida - 2018 - Moscow, Russia: Kurs INFRA-M.
    The theory of evolution of complex, including the humans system and algorithm for its constructing are a synthesis of evolutionary epistemology, philosophical anthropology and concrete scientific empirical basis in modern science,. In other words, natural philosophy is regaining the status bar element theoretical science in the era of technology-driven evolution. The co-evolutionary concept of 3-modal stable evolutionary strategy of Homo sapiens is developed. The concept based on the principle of evolutionary complementarity of anthropogenesis: value of evolutionary risk and evolutionary (...)
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  24. Developing Ian Hacking's ‘Styles Project’: Towards a ‘Theory of Styles of Reasoning’.Luca Sciortino - 2023 - New York: Palgrave-McMillan.
    This chapter expounds Hacking’s project of styles of reasoning more systematically than Hacking himself has done, while the following chapters examine its philosophical implications. I shall show that, in addition to the statistical and the laboratory style described in Chap. 3, there exist other four styles of reasoning that share a set of common characterizing features: the algorithmic, the postulational, the historico-genetic and the taxonomic style of reasoning. All the differences notwithstanding, striking parallels can be drawn between these different (...)
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  25. The transition to civilization and symbolically stored genomes.Jon Beach - 2003 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 34 (1):109-141.
    The study of culture and cultural selection from a biological perspective has been hampered by the lack of any firm theoretical basis for how the information for cultural traits is stored and transmitted. In addition, the study of any living system with a decentralized or multi-level information structure has been somewhat restricted due to the focus in genetics on the gene and the particular hereditary structure of multicellular organisms. Here a different perspective is used, one which regards living systems as (...)
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  26. The Logical Structure of the Cognitive Mechanisms Guiding Psychological Development.George Osborne - 1995 - Dissertation, University of Cambridge
    This Thesis presents a model of cognitive development inspired by Piaget's "Genetic Epistemology". It is observed that the epigenetic process described by Piaget posess mechanisms and behaviour that characterise complex adaptive systems. A model of bipedal motion based around the "Bucket Brigade" algorithm of Holland is presened to explore this relationship.
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  27. Return of Logos: Ontological Memory → Information → Time.Vladimir Rogozhin - 2013 - FQXi Contest 2013:00-08.
    Total ontological unification of matter at all levels of reality as a whole, its “grasp” of its dialectical structure, space dimensionality and structure of the language of nature – “house of Being” [1], gives the opportunity to see the “place” and to understand the nature of information as a phenomenon of Ontological (structural) Memory (OntoMemory), the measure of being of the whole, “the soul of matter”, qualitative quantity of the absolute forms of existence of matter (absolute states). “Information” and “time” (...)
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  28. Algorithmic neutrality.Milo Phillips-Brown - manuscript
    Algorithms wield increasing control over our lives—over the jobs we get, the loans we're granted, the information we see online. Algorithms can and often do wield their power in a biased way, and much work has been devoted to algorithmic bias. In contrast, algorithmic neutrality has been largely neglected. I investigate algorithmic neutrality, tackling three questions: What is algorithmic neutrality? Is it possible? And when we have it in mind, what can we learn about algorithmic bias?
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  29. Genetic enhancement, human extinction, and the best interests of posthumanity.Jon Rueda - 2022 - Bioethics (6):529-538.
    The cumulative impact of enhancement technologies may alter the human species in the very long-term future. In this article, I will start showing how radical genetic enhancements may accelerate the conversion into a novel species. I will also clarify the concepts of ‘biological species’, ‘transhuman’ and ‘posthuman’. Then, I will summarize some ethical arguments for creating a transhuman or posthuman species with a substantially higher level of well-being than the human one. In particular, I will present what I shall (...)
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  30. Algorithmic Profiling as a Source of Hermeneutical Injustice.Silvia Milano & Carina Prunkl - forthcoming - Philosophical Studies:1-19.
    It is well-established that algorithms can be instruments of injustice. It is less frequently discussed, however, how current modes of AI deployment often make the very discovery of injustice difficult, if not impossible. In this article, we focus on the effects of algorithmic profiling on epistemic agency. We show how algorithmic profiling can give rise to epistemic injustice through the depletion of epistemic resources that are needed to interpret and evaluate certain experiences. By doing so, we not only demonstrate how (...)
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  31. Algorithms for Ethical Decision-Making in the Clinic: A Proof of Concept.Lukas J. Meier, Alice Hein, Klaus Diepold & Alena Buyx - 2022 - American Journal of Bioethics 22 (7):4-20.
    Machine intelligence already helps medical staff with a number of tasks. Ethical decision-making, however, has not been handed over to computers. In this proof-of-concept study, we show how an algorithm based on Beauchamp and Childress’ prima-facie principles could be employed to advise on a range of moral dilemma situations that occur in medical institutions. We explain why we chose fuzzy cognitive maps to set up the advisory system and how we utilized machine learning to train it. We report on (...)
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  32. 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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  33. Democratizing Algorithmic Fairness.Pak-Hang Wong - 2020 - Philosophy and Technology 33 (2):225-244.
    Algorithms can now identify patterns and correlations in the (big) datasets, and predict outcomes based on those identified patterns and correlations with the use of machine learning techniques and big data, decisions can then be made by algorithms themselves in accordance with the predicted outcomes. Yet, algorithms can inherit questionable values from the datasets and acquire biases in the course of (machine) learning, and automated algorithmic decision-making makes it more difficult for people to see algorithms as biased. While researchers have (...)
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  34. Algorithmic Fairness from a Non-ideal Perspective.Sina Fazelpour & Zachary C. Lipton - 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society.
    Inspired by recent breakthroughs in predictive modeling, practitioners in both industry and government have turned to machine learning with hopes of operationalizing predictions to drive automated decisions. Unfortunately, many social desiderata concerning consequential decisions, such as justice or fairness, have no natural formulation within a purely predictive framework. In efforts to mitigate these problems, researchers have proposed a variety of metrics for quantifying deviations from various statistical parities that we might expect to observe in a fair world and offered a (...)
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  35. Evolution of Genetic Information without Error Replication.Guenther Witzany - 2020 - In Theoretical Information Studies. Singapur: pp. 295-319.
    Darwinian evolutionary theory has two key terms, variations and biological selection, which finally lead to survival of the fittest variant. With the rise of molecular genetics, variations were explained as results of error replications out of the genetic master templates. For more than half a century, it has been accepted that new genetic information is mostly derived from random error-based events. But the error replication narrative has problems explaining the sudden emergence of new species, new phenotypic traits, and (...)
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  36. The Algorithmic Leviathan: Arbitrariness, Fairness, and Opportunity in Algorithmic Decision-Making Systems.Kathleen Creel & Deborah Hellman - 2022 - Canadian Journal of Philosophy 52 (1):26-43.
    This article examines the complaint that arbitrary algorithmic decisions wrong those whom they affect. It makes three contributions. First, it provides an analysis of what arbitrariness means in this context. Second, it argues that arbitrariness is not of moral concern except when special circumstances apply. However, when the same algorithm or different algorithms based on the same data are used in multiple contexts, a person may be arbitrarily excluded from a broad range of opportunities. The third contribution is to (...)
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  37. The ethics of algorithms: mapping the debate.Brent Mittelstadt, Patrick Allo, Mariarosaria Taddeo, Sandra Wachter & Luciano Floridi - 2016 - Big Data and Society 3 (2):2053951716679679.
    In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences (...)
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  38. Algorithms and the Individual in Criminal Law.Renée Jorgensen - 2022 - Canadian Journal of Philosophy 52 (1):1-17.
    Law-enforcement agencies are increasingly able to leverage crime statistics to make risk predictions for particular individuals, employing a form of inference that some condemn as violating the right to be “treated as an individual.” I suggest that the right encodes agents’ entitlement to a fair distribution of the burdens and benefits of the rule of law. Rather than precluding statistical prediction, it requires that citizens be able to anticipate which variables will be used as predictors and act intentionally to avoid (...)
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  39. Crash Algorithms for Autonomous Cars: How the Trolley Problem Can Move Us Beyond Harm Minimisation.Dietmar Hübner & Lucie White - 2018 - Ethical Theory and Moral Practice 21 (3):685-698.
    The prospective introduction of autonomous cars into public traffic raises the question of how such systems should behave when an accident is inevitable. Due to concerns with self-interest and liberal legitimacy that have become paramount in the emerging debate, a contractarian framework seems to provide a particularly attractive means of approaching this problem. We examine one such attempt, which derives a harm minimisation rule from the assumptions of rational self-interest and ignorance of one’s position in a future accident. We contend, (...)
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  40. Algorithms, Agency, and Respect for Persons.Alan Rubel, Clinton Castro & Adam Pham - 2020 - Social Theory and Practice 46 (3):547-572.
    Algorithmic systems and predictive analytics play an increasingly important role in various aspects of modern life. Scholarship on the moral ramifications of such systems is in its early stages, and much of it focuses on bias and harm. This paper argues that in understanding the moral salience of algorithmic systems it is essential to understand the relation between algorithms, autonomy, and agency. We draw on several recent cases in criminal sentencing and K–12 teacher evaluation to outline four key ways in (...)
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  41. Ameliorating Algorithmic Bias, or Why Explainable AI Needs Feminist Philosophy.Linus Ta-Lun Huang, Hsiang-Yun Chen, Ying-Tung Lin, Tsung-Ren Huang & Tzu-Wei Hung - 2022 - Feminist Philosophy Quarterly 8 (3).
    Artificial intelligence (AI) systems are increasingly adopted to make decisions in domains such as business, education, health care, and criminal justice. However, such algorithmic decision systems can have prevalent biases against marginalized social groups and undermine social justice. Explainable artificial intelligence (XAI) is a recent development aiming to make an AI system’s decision processes less opaque and to expose its problematic biases. This paper argues against technical XAI, according to which the detection and interpretation of algorithmic bias can be handled (...)
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  42. Algorithmic decision-making: the right to explanation and the significance of stakes.Lauritz Munch, Jens Christian Bjerring & Jakob Mainz - forthcoming - Big Data and Society.
    The stakes associated with an algorithmic decision are often said to play a role in determining whether the decision engenders a right to an explanation. More specifically, “high stakes” decisions are often said to engender such a right to explanation whereas “low stakes” or “non-high” stakes decisions do not. While the overall gist of these ideas is clear enough, the details are lacking. In this paper, we aim to provide these details through a detailed investigation of what we will call (...)
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  43. Algorithmic paranoia: the temporal governmentality of predictive policing.Bonnie Sheehey - 2019 - Ethics and Information Technology 21 (1):49-58.
    In light of the recent emergence of predictive techniques in law enforcement to forecast crimes before they occur, this paper examines the temporal operation of power exercised by predictive policing algorithms. I argue that predictive policing exercises power through a paranoid style that constitutes a form of temporal governmentality. Temporality is especially pertinent to understanding what is ethically at stake in predictive policing as it is continuous with a historical racialized practice of organizing, managing, controlling, and stealing time. After first (...)
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  44. On statistical criteria of algorithmic fairness.Brian Hedden - 2021 - Philosophy and Public Affairs 49 (2):209-231.
    Predictive algorithms are playing an increasingly prominent role in society, being used to predict recidivism, loan repayment, job performance, and so on. With this increasing influence has come an increasing concern with the ways in which they might be unfair or biased against individuals in virtue of their race, gender, or, more generally, their group membership. Many purported criteria of algorithmic fairness concern statistical relationships between the algorithm’s predictions and the actual outcomes, for instance requiring that the rate of (...)
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  45. Algorithmic Colonization of Love.Hao Wang - 2023 - Techné Research in Philosophy and Technology 27 (2):260-280.
    Love is often seen as the most intimate aspect of our lives, but it is increasingly engineered by a few programmers with Artificial Intelligence (AI). Nowadays, numerous dating platforms are deploying so-called smart algorithms to identify a greater number of potential matches for a user. These AI-enabled matchmaking systems, driven by a rich trove of data, can not only predict what a user might prefer but also deeply shape how people choose their partners. This paper draws on Jürgen Habermas’s “colonization (...)
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  46. The algorithm audit: Scoring the algorithms that score us.Jovana Davidovic, Shea Brown & Ali Hasan - 2021 - Big Data and Society 8 (1).
    In recent years, the ethical impact of AI has been increasingly scrutinized, with public scandals emerging over biased outcomes, lack of transparency, and the misuse of data. This has led to a growing mistrust of AI and increased calls for mandated ethical audits of algorithms. Current proposals for ethical assessment of algorithms are either too high level to be put into practice without further guidance, or they focus on very specific and technical notions of fairness or transparency that do not (...)
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  47. Algorithm exploitation: humans are keen to exploit benevolent AI.Jurgis Karpus, Adrian Krüger, Julia Tovar Verba, Bahador Bahrami & Ophelia Deroy - 2021 - iScience 24 (6):102679.
    We cooperate with other people despite the risk of being exploited or hurt. If future artificial intelligence (AI) systems are benevolent and cooperative toward us, what will we do in return? Here we show that our cooperative dispositions are weaker when we interact with AI. In nine experiments, humans interacted with either another human or an AI agent in four classic social dilemma economic games and a newly designed game of Reciprocity that we introduce here. Contrary to the hypothesis that (...)
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  48.  24
    Algorithm Evaluation Without Autonomy.Scott Hill - forthcoming - AI and Ethics.
    In Algorithms & Autonomy, Rubel, Castro, and Pham (hereafter RCP), argue that the concept of autonomy is especially central to understanding important moral problems about algorithms. In particular, autonomy plays a role in analyzing the version of social contract theory that they endorse. I argue that although RCP are largely correct in their diagnosis of what is wrong with the algorithms they consider, those diagnoses can be appropriated by moral theories RCP see as in competition with their autonomy based theory. (...)
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  49. Algorithmic Bias and Risk Assessments: Lessons from Practice.Ali Hasan, Shea Brown, Jovana Davidovic, Benjamin Lange & Mitt Regan - 2022 - Digital Society 1 (1):1-15.
    In this paper, we distinguish between different sorts of assessments of algorithmic systems, describe our process of assessing such systems for ethical risk, and share some key challenges and lessons for future algorithm assessments and audits. Given the distinctive nature and function of a third-party audit, and the uncertain and shifting regulatory landscape, we suggest that second-party assessments are currently the primary mechanisms for analyzing the social impacts of systems that incorporate artificial intelligence. We then discuss two kinds of (...)
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  50. Algorithmic Political Bias Can Reduce Political Polarization.Uwe Peters - 2022 - Philosophy and Technology 35 (3):1-7.
    Does algorithmic political bias contribute to an entrenchment and polarization of political positions? Franke argues that it may do so because the bias involves classifications of people as liberals, conservatives, etc., and individuals often conform to the ways in which they are classified. I provide a novel example of this phenomenon in human–computer interactions and introduce a social psychological mechanism that has been overlooked in this context but should be experimentally explored. Furthermore, while Franke proposes that algorithmic political classifications entrench (...)
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