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|Title: ||Knowing Instruments: Design, Reliability, and Scientific Practice|
|Authors: ||Record, Isaac|
|Advisor: ||Chakravartty, Anjan|
|Department: ||History and Philosophy of Science and Technology|
|Keywords: ||scientific instruments|
|Issue Date: ||26-Mar-2012|
|Abstract: ||This dissertation is an attempt to understand the role of instruments in the process of knowledge production in science. I ask: how can we trust scientific instruments and what do we learn about when we use them? The dissertation has four parts.
First, I construct a novel account of “epistemic possibility,” the possibility of knowing, that captures the dependency of knowledge on action, and I introduce the notion of “technological possibility,” which depends on the availability of material and conceptual means to bring about a desired state of affairs. I argue that, under certain circumstances, technological possibility is a condition for epistemic possibility.
Second, I ask how instruments become reliable. I argue that when the material capacities and conceptual functions of a scientific instrument correspond, the instrument is a reliable component of the process of knowledge production. I then describe how the instrument design process can result in just such a correspondence. Instrument design produces the material device, a functional concept of the device revised in light of experience, a measure of the closeness of fit between material and function, and practices of trust such as calibration routines.
Third, I ask what we learn from instruments such as those used for experimentation and simulation. I argue that in experiments, instruments function to inform us about the material capacities of the object of investigation, while in simulations, instruments function to inform us about the conceptual model of the object of investigation.
Fourth, I put these philosophical distinctions into historical context through a case study of Monte Carlo simulations run on digital electronic computers in the 1940s-70s. I argue that digital electronic computers made the practice of Monte Carlo simulation technologically possible, but that the new method did not meet existing scientific standards. Consequently, Monte Carlo design practices were revised to address the worries of potential practitioners.|
|Appears in Collections:||Doctoral|
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