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- Volume 113, Issue 1, 2021
Algemeen Nederlands Tijdschrift voor Wijsbegeerte - Volume 113, Issue 1, 2021
Volume 113, Issue 1, 2021
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Who’s the greatest of them all?
More LessAbstractWho’s the greatest of them all? A non-technical explication of Newton’s method in the Principia accompanied by some philosophical reflections
In this essay, I seek to explicate the methodology which Newton used in the Principia in a non-technical way. Close attention will be paid to some important results in Books I and III of the Principia and to Newton’s argument for universal gravitation. Based on their discussion, Newton’s key inferential strategies will be brought to the fore. In addition, it will be explained how Newton’s methodology differed from a standard hypothetico-deductive method.
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Alfred Wegeners theorie van continentendrift en haar rivalen
By Erik WeberAbstractAlfred Wegener’s Theory of Continental Drift and its Rivals. Rational Disagreement and Rational Consensus in the Earth Sciences
Alfred Wegener launched the idea of continental drift (lateral motion of continents on the earth) early in the 20th century. In the period 1915-1930 he did not succeed to convince his fellow earth scientist to leave behind their old permanentist or contractionist theories and adopt his new theory. In the second half of the 20th century – between 1960 and 1975 – continental drift quickly became the dominant theory in the earth sciences. In this paper I analyse both episode by means of methodological concepts developed by Larry Laudan. I argue that the disagreement in the early days as well as the quickly emerging consensus in the second period are rational.
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Beloften en teleurstellingen van artificiële intelligentie voor wetenschappelijke ontdekkingen
More LessAbstractPromises and disappointments of artificial intelligence for scientific discovery
Recent successes within Artificial Intelligence with deep learning techniques in board games gave rise to the ambition to apply these learning methods to scientific discovery. This model for discovering new scientific laws is based on data-driven generalization in large databases with observational data using neural networks. In this study we want to review and critical assess an earlier research programme by the name of BACON. Though BACON was based on different AI technology, we can learn from its limitations and thus adjust our expectations. The BACON program had two ambitions, one descriptive and one normative. On the one hand, it wanted to provide an explanation how philosophers of nature in history arrived at general laws from observational data and on the other hand it also aimed to reconstruct historical discoveries and realize new ones. We will assess the claims of the BACON program by means of two historical cases studies: the discovery of the sine law of refraction in optics and the discovery of Kepler’s third law of planetary motion. I will demonstrate that, despite the formulated claims, BACON did not use the same historical data available to its discoverers and, more importantly, that the model of inductive generalization of observational data does not correspond with the historical methods. Finally I will question the value of data-driven induction for scientific discovery in general.
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Hoe Galileo Galilei de valwet ontdekte, en het verschil dat dit maakt
More LessAbstractHow Galileo Galilei discovered the law of fall, and the difference that this makes
Galileo’s law of fall is one of the crucial building blocks of classical mechanics. The question how this law was discovered has often been a topic of debate. This article offers a reconstruction of the developments within Galileo’s research that led to the discovery of the law. This reconstruction is offered to make a philosophical point regarding the epistemic status of experimental results: Galileo’s experiments can offer sufficient justification for the acceptance of the law of fall only because of their place in a broad research programme.
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Gregor Mendel, Thomas Hunt Morgan en experimenten in de klassieke genetica
More LessAbstractGregor Mendel, Thomas Hunt Morgan and experiments in classical genetics
In the middle of the 19th century, Gregor Mendel performed a series of crosses with pea plants to investigate how hybrids are formed. Decades later, Thomas Hunt Morgan finalized the theory of classical genetics. An important aspect of Mendel’s and Morgan’s scientific approach is that they worked in a systematic, experimental fashion. But how did these experiments proceed? What is the relation between these experiments and Mendel’s and Morgan’s explanatory theories? What was their evidential value? Using present-day insights in the nature of experimentation I will show that the answer to these questions is fascinating but not obvious. Crossings in classical genetics lacked a crucial feature of traditional experiments for causal discovery: manipulation of the purported causes. Hence they were not traditional, ‘manipulative’ experiments, but ‘selective experiments’.
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Hoe zeker is Heisenbergs onzekerheidsprincipe?
Authors: Jeanne Peijnenburg & David AtkinsonAbstractHow certain is Heisenberg’s uncertainty principle?
Heisenberg’s uncertainty principle is at the heart of the orthodox or Copenhagen interpretation of quantum mechanics. We first sketch the history that led up to the formulation of the principle. Then we recall that there are in fact two uncertainty principles, both dating from 1927, one by Werner Heisenberg and one by Earle Kennard. Finally, we explain that recent work in physics gives reason to believe that the principle of Heisenberg is invalid, while that of Kennard still stands.
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Kurt Gödels onvolledigheidsstellingen en de grenzen van de kennis
More LessAbstractKurt Gödel’s incompleteness theorems and the limits of knowledge
In this paper a presentation is given of Kurt Gödel’s pathbreaking results on the incompleteness of formal arithmetic. Some biographical details are provided but the main focus is on the analysis of the theorems themselves. An intermediate level between informal and formal has been sought that allows the reader to get a sufficient taste of the technicalities involved and not lose sight of the philosophical importance of the results. Connections are established with the work of Alan Turing and Hao Wang to show the present-day relevance of Gödel’s research and how it relates to the limitations of human knowledge, mathematical knowledge in particular.
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