Can we trust Big Data? Applying philosophy of science to software
dc.contributor.author | Symons, John | |
dc.contributor.author | Alvarado, Ramón | |
dc.date.accessioned | 2018-12-14T19:37:05Z | |
dc.date.available | 2018-12-14T19:37:05Z | |
dc.date.issued | 2016-09-02 | |
dc.identifier.citation | Symons, J., & Alvarado, R. (2016). Can we trust Big Data? Applying philosophy of science to software. Big Data & Society, 3(2), 2053951716664747. | en_US |
dc.identifier.uri | http://hdl.handle.net/1808/27521 | |
dc.description.abstract | We address some of the epistemological challenges highlighted by the Critical Data Studies literature by reference to some of the key debates in the philosophy of science concerning computational modeling and simulation. We provide a brief overview of these debates focusing particularly on what Paul Humphreys calls epistemic opacity. We argue that debates in Critical Data Studies and philosophy of science have neglected the problem of error management and error detection. This is an especially important feature of the epistemology of Big Data. In “Error” section we explain the main characteristics of error detection and correction along with the relationship between error and path complexity in software. In this section we provide an overview of conventional statistical methods for error detection and review their limitations when faced with the high degree of conditionality inherent to modern software systems. | en_US |
dc.publisher | SAGE Publications | en_US |
dc.rights | Creative Commons NonCommercial-NoDerivs CC-BY-NC-ND: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage) | en_US |
dc.rights.uri | http://www.creativecommons.org/licenses/by-nc-nd/3.0/ | en_US |
dc.subject | Big Data | en_US |
dc.subject | Epistemology | en_US |
dc.subject | Software | en_US |
dc.subject | Complexity | en_US |
dc.subject | Error | en_US |
dc.subject | Critical Data Studies | en_US |
dc.title | Can we trust Big Data? Applying philosophy of science to software | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1177/2053951716664747 | en_US |
kusw.oaversion | Scholarly/refereed, publisher version | en_US |
kusw.oapolicy | This item meets KU Open Access policy criteria. | en_US |
dc.rights.accessrights | openAccess | en_US |
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Except where otherwise noted, this item's license is described as: Creative Commons NonCommercial-NoDerivs CC-BY-NC-ND: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage)