Can we trust Big Data? Applying philosophy of science to software
Bibliographic Data
| ID | 5260507 |
|---|---|
| Authors | John Symons (0000-0001-8173-2948), Ramón Alvarado (0000-0002-0028-4192) |
| Year | 2016 |
| Volume | 3 |
| Issue | 2 |
| Publication date | 2016-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Big Data & Society (JOURNAL) |
| Journal identifiers | ISSN: 2053-9517 • E-ISSN: 2053-9517 |
| Publisher | SAGE Publications Inc (PUBLISHER) |
| DOI | 10.1177/2053951716664747 |
| OpenAlex | W2511674954 |
| Language | EN |
| Citations received | 21 |
| References cited | 42 |
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
Big data · Computer security · Data mining · Data science · Epistemology · Philosophy of science · Computer Science · Data Visualization and Analytics · Explainable Artificial Intelligence (XAI · Philosophy · Scientific Computing and Data Management · Software
Nichtwissen bei maschinellem Lernen
Données brutes ou hypersymboles ? Signification et données numériques, entre processus discursif et procédure machinique
Through the Looking Glass
Catch Me if You Can
Arbeit und Spiel
The (dis)embodied gaze
Urban Vitality Measurement Through Big Data and Internet of Things Technologies
Artificial intelligence and big data-driven evaluation research and practices
Introduction to the Special Issue — Social Media and Inquiry into Political Change
A big data state of mind
On computational historical linguistics in the 21st century
Whose Privacy, What Surveillance? Dimensions of the Mental Models for Privacy and Security
Articulating AI futures for Brazil
The epistemological foundations of data science
Opacity thought through
Epistemic injustice and data science technologies
Humanistic interpretation and machine learning
The locus of legitimate interpretation in Big Data sciences
Critical data studies
Raw data or hypersymbols? Meaning-making with digital data, between discursive processes and machinic procedures
Exploring the data turn of philosophy of language in the era of big data
Science in the Age of Computer Simulation
Simulation and Similarity
The Philosophy of Software
Predicting consumer behavior with Web search
The Parable of Google Flu
The structure of scientific revolutions
Science as Social Knowledge
Big Data and Their Epistemological Challenge
Software Intensive Science
Reply to Angius and Primiero on Software Intensive Science
Security and the incalculable
The philosophy of simulation
Computer simulations as experiments
The philosophical novelty of computer simulation methods
On malfunctioning software
About the warrants of computer-based empirical knowledge
Computer simulation through an error-statistical lens
The philosophy of simulation
A General Black Box Theory
Critical Questions for Big Data
Big Data, new epistemologies and paradigm shifts
Data Derivatives
| Unique citing works | 21 |
|---|---|
| Citations per year | 2,1 |
| Citation span | 2016 - 2025 (10) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 17 |