Alien Reasoning: Is a Major Change in Scientific Research Underway?
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Alien Reasoning: Is a Major Change in Scientific Research Underway? Thomas Nickles1
© Springer Science+Business Media B.V., part of Springer Nature 2018
Abstract Are we entering a major new phase of modern science, one in which our standard, human modes of reasoning and understanding, including heuristics, have decreasing value? The new methods challenge human intelligibility. The digital revolution (deep connectionist machine learning, big data, cloud computing, simulation, etc.) inspires such claims, but they are not new. During several historical periods, scientific progress has challenged traditional concepts of reasoning and rationality, intelligence and intelligibility, explanation and knowledge. The increasing intelligence of machine learning and networking is a deliberately sought, somewhat alien intelligence. As such, it challenges the traditional, heuristic foresight of expert researchers. Nonetheless, science remains human-centered in important ways—and yet many of our ordinary human epistemic activities are alien to ourselves. This fact has always been the source of “the discovery problem”. It generalizes to the problem of understanding expert scientific practice. Ironically, scientific progress plunges us ever deeper into complexities beyond our grasp. But how is progress possible without traditional realism and the intelligibility realism requires? Pragmatic flexibility offers an answer. Keywords The end of traditional science · Scientific reasoning · Heuristics · Big data · Deep neural networks · Alien intelligence · Intelligibility · Scientific realism · Scientific progress · Expertise [T]here are probably some truths not made to be perceived by the eyes of our mind, just as there are objects, that those of our body will never perceive. —Émilie Du Châtelet, Foundations of Physics (1740/2009, Preface, VII)1 If a lion could speak, we could not understand him. —Ludwig Wittgenstein (1953, p. 223)
1 Is the Digital Revolution Transforming Scientific Reasoning? In the early days, a primary ambition of what we might call “the discovery program” in artificial intelligence was to build computer programs that solved problems in the same way that people seemingly do. The first programs consisted of logic plus a few, general, content-neutral heuristics, extracted from step-by-step protocols of classrooms of people attempting to * Thomas Nickles [email protected] 1
Department of Philosophy Emeritus, University of Nevada, Reno, Reno, NV 89557, USA
solve fairly simple problems of various kinds (Newell and Simon 1972). The “maker’s knowledge” background to that idea was that, since we can understand what we have made, we would finally understand the logic of scientific discovery and of some other forms of creativity, for discovery is essentially problem solving, basically computational search through problem spaces. At that time, most of us philosopher “friends of discovery” had focused on history of science and were slow to tap into what the AI experts were doing. We were skeptical that such a strong goal c
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