Fusing algorithms and analysts: open-source intelligence in the age of ‘Big Data’

Christopher Alan Eldridge; Christopher Hobbs; Matthew James Moran

Fusing algorithms and analysts: open-source intelligence in the age of ‘Big Data’

Christopher Alan Eldridge, Christopher Hobbs, Matthew James Moran

War Studies

Research output: Contribution to journal › Article › peer-review

27 Citations (Scopus)

1015 Downloads (Pure)

Abstract

In the age of ‘Big Data’, the potential value of open-source information for intelligence-related purposes is widely recognised. Of late, progress in this space has increasingly become associated with software that can expand our ability to gather, filter, interrelate and manipulate data through automated processes. The trend towards automation is both innovative and necessary. However, techno-centric efforts to replace human analysts with finely crafted algorithms across the board, from collection to synthesis and analysis of information, risk limiting the potential of OSINT rather than increasing its scope and impact. Effective OSINT systems must be carefully designed to facilitate complementarity, exploit the strengths, and mitigate the weaknesses of both human analysts and software solutions, obtaining the best contribution from both. Drawing on insights from the field of cognitive engineering, this article considers at a conceptual level how this might be achieved.

Original language	English
Journal	Intelligence and National Security
Publication status	E-pub ahead of print - 2017

Keywords

OSINT
Big Data
open source

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Fusing Algorithms and Analysts_ELDRIDGE_Published Online 2017 _GREEN AAMAccepted author manuscript, 430 KB

Cite this

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AB - In the age of ‘Big Data’, the potential value of open-source information for intelligence-related purposes is widely recognised. Of late, progress in this space has increasingly become associated with software that can expand our ability to gather, filter, interrelate and manipulate data through automated processes. The trend towards automation is both innovative and necessary. However, techno-centric efforts to replace human analysts with finely crafted algorithms across the board, from collection to synthesis and analysis of information, risk limiting the potential of OSINT rather than increasing its scope and impact. Effective OSINT systems must be carefully designed to facilitate complementarity, exploit the strengths, and mitigate the weaknesses of both human analysts and software solutions, obtaining the best contribution from both. Drawing on insights from the field of cognitive engineering, this article considers at a conceptual level how this might be achieved.

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KW - Big Data

KW - open source

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M3 - Article

SN - 0268-4527

JO - Intelligence and National Security

JF - Intelligence and National Security

ER -

Fusing algorithms and analysts: open-source intelligence in the age of ‘Big Data’

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Keywords

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