9,913 research outputs found

    The problem of induction and Artificial Intelligence

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    Methods in Psychological Research

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    Psychologists collect empirical data with various methods for different reasons. These diverse methods have their strengths as well as weaknesses. Nonetheless, it is possible to rank them in terms of different critieria. For example, the experimental method is used to obtain the least ambiguous conclusion. Hence, it is the best suited to corroborate conceptual, explanatory hypotheses. The interview method, on the other hand, gives the research participants a kind of emphatic experience that may be important to them. It is for the reason the best method to use in a clinical setting. All non-experimental methods owe their origin to the interview method. Quasi-experiments are suited for answering practical questions when ecological validity is importa

    Hume, the Philosophy of Science and the Scientific Tradition

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    Although the main focus of Hume’s career was in the humanities, his work also has an observable role in the historical development of natural sciences after his time. To show this, I shall center on the relation between Hume and two major figures in the history of the natural sciences: Charles Darwin (1809–1882) and Albert Einstein (1879–1955). Both of these scientists read Hume. They also found parts of Hume’s work useful to their sciences. Inquiring into the relations between Hume and the two scientists shows that his philosophical positions had a partial but constructive role in the formation of modern biology and physics. This is accordingly a clear indication of Hume’s impact on the scientific tradition. Before proceeding to analyze Hume’s contribution to the history of science, it is important to address his broader role in the history of philosophy of science. Hume’s discussions concerning the topics of causation, induction, the distinction between mathematical and empirical propositions, and laws of nature have been important for the philosophy of science of the nineteenth and twentieth centuries

    Human-machine scientific discovery

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    International audienceHumanity is facing existential, societal challenges related to food security, ecosystem conservation, antimicrobial resistance, etc, and Artificial Intelligence (AI) is already playing an important role in tackling these new challenges. Most current AI approaches are limited when it comes to ‘knowledge transfer’ with humans, i.e. it is difficult to incorporate existing human knowledge and also the output knowledge is not human comprehensible. In this chapter we demonstrate how a combination of comprehensible machine learning, text-mining and domain knowledge could enhance human-machine collaboration for the purpose of automated scientific discovery where humans and computers jointly develop and evaluate scientific theories. As a case study, we describe a combination of logic-based machine learning (which included human-encoded ecological background knowledge) and text-mining from scientific publications (to verify machine-learned hypotheses) for the purpose of automated discovery of ecological interaction networks (food-webs) to detect change in agricultural ecosystems using the Farm Scale Evaluations (FSEs) of genetically modified herbicide-tolerant (GMHT) crops dataset. The results included novel food-web hypotheses, some confirmed by subsequent experimental studies (e.g. DNA analysis) and published in scientific journals. These machine-leaned food-webs were also used as the basis of a recent study revealing resilience of agro-ecosystems to changes in farming management using GMHT crops

    Reasoning, Science, and the Ghost Hunt

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    This paper details how ghost hunting, as a set of learning activities, can be used to enhance critical thinking and philosophy of science classes. We describe in some detail our own work with ghost hunting, and reflect on both intended and unintended consequences of this pedagogical choice. This choice was partly motivated by students’ lack of familiarity with science and philosophic questions about it. We offer reflections on our three different implementations of the ghost hunting activities. In addition, we discuss the practical nuances of implementing these activities, as well the relation of ghost hunting to our course content, including informal fallacies and some models for scientific inference. We conclude that employing ghost hunting along-side traditional activities and content of critical thinking and philosophy of science offers a number of benefits, including being fun, increasing student attendance, enhancing student learning, and providing a platform for campus wide dialogues about philosophy

    The distinction between falsification and refutation in the demarcation problem of Karl Popper

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    Despite the criticism of Karl Popper's falsifiability theory for the demarcation between science and non-science, mainly pseudo-science, this criterion is still very useful, and perfectly valid after it was perfected by Popper and his followers. Moreover, even in his original version, considered by Lakatos as "dogmatic", Popper did not assert that this methodology is an absolute demarcation criterion: a single counter-example is not enough to falsify a theory; a theory can legitimately be saved from falsification by introducing an auxiliary hypothesis. Compared to Kuhn's theory of revolutions, which he himself later dissociated from it transforming it into a theory of "micro-revolutions," I consider that Popper's demarcation methodology, along with the subsequent development proposed by him, including the corroboration and the verisimilitude, though imperfect, is not only valid today, but it is still the best demarcation methodology. For argumentation, I used the main works of Popper dealing with this issue, and his main critics and supporters. After a brief presentation of Karl Popper, and an introduction to the demarcation problem and the falsification methodology, I review the main criticisms and the arguments of his supporters, emphasizing the idea that Popper has never put the sign of equality between falsification and rejection. Finally, I present my own conclusions on this issue. CONTENTS Abstract Introduction 1 The demarcation problem 2 Pseudoscience 3 Falsifiability 4 Falsification and refutation 5 Extension of falsifiability 6 Criticism of falsifiability 7 Support of falsifiability 8 The current trend Conclusions Bibliography Notes DOI: 10.13140/RG.2.2.22522.5472

    Doing evolution in economic geography

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    Evolutionary approaches in economic geography face questions about the relationships between their concepts, theories, methods, politics, and policy implications. Amidst the growing but unsettled consensus that evolutionary approaches should employ plural methodologies, the aims here are, first, to identify some of the difficult issues confronting those working with different frameworks. The concerns comprise specifying and connecting research objects, subjects, and levels; handling agency and context; engaging and integrating the quantitative and the qualitative; comparing cases; and, considering politics, policy, and praxis. Second, the purpose is to articulate a distinctive geographical political economy approach, methods, and illustrative examples in addressing these issues. Bringing different views of evolution in economic geography into dialogue and disagreement renders methodological pluralism a means toward improved understanding and explanation rather than an end in itself. Confronting such thorny matters needs to be embedded in our research practices and supported by greater openness; more and better substantiation of our conceptual, theoretical, and empirical claims; enhanced critical reflection; and deeper engagement with politics, policy, and praxis

    An Analysis of the Falsification Criterion of Karl Popper: A Critical Review

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    Karl Popper identified ‘falsifiability’ as the criterion in demarcating science from non-science. The method of induction, which uses the (debated) principle of uniformity of nature, was rejected by Popper. He instead suggested that a scientific theory cannot be ‘verifiable’ but only ‘falsifiable’; one counter-example to the claims made by the theory would falsify it. The paper conducts a survey of the extant literature to understand the concept, the methodology as suggested by Popper to operationalize the concept, and possible limitations, both conceptual and methodological. The extant literature points out inherent ambiguities in the Popperian concept of falsifiabilty. One recurring theme is that Popper, the deductivist, uses the much critiqued inductivistic method among his methodological suite
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