Can we trust Big Data? Applying philosophy of science to software
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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2016-08-01
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| Series: | Big Data & Society |
| Online Access: | https://doi.org/10.1177/2053951716664747 |
| _version_ | 1818870439714226176 |
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| author | John Symons Ramón Alvarado |
| author_facet | John Symons Ramón Alvarado |
| author_sort | John Symons |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-19T12:07:03Z |
| format | Article |
| id | doaj.art-f757e16272854939b5c6b5f1c8c60248 |
| institution | Directory Open Access Journal |
| issn | 2053-9517 |
| language | English |
| last_indexed | 2024-12-19T12:07:03Z |
| publishDate | 2016-08-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Big Data & Society |
| spelling | doaj.art-f757e16272854939b5c6b5f1c8c602482022-12-21T20:22:19ZengSAGE PublishingBig Data & Society2053-95172016-08-01310.1177/2053951716664747Can we trust Big Data? Applying philosophy of science to softwareJohn SymonsRamón AlvaradoWe 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.https://doi.org/10.1177/2053951716664747 |
| spellingShingle | John Symons Ramón Alvarado Can we trust Big Data? Applying philosophy of science to software Big Data & Society |
| title | Can we trust Big Data? Applying philosophy of science to software |
| title_full | Can we trust Big Data? Applying philosophy of science to software |
| title_fullStr | Can we trust Big Data? Applying philosophy of science to software |
| title_full_unstemmed | Can we trust Big Data? Applying philosophy of science to software |
| title_short | Can we trust Big Data? Applying philosophy of science to software |
| title_sort | can we trust big data applying philosophy of science to software |
| url | https://doi.org/10.1177/2053951716664747 |
| work_keys_str_mv | AT johnsymons canwetrustbigdataapplyingphilosophyofsciencetosoftware AT ramonalvarado canwetrustbigdataapplyingphilosophyofsciencetosoftware |